This article originally appeared on the Carnegie Mellon School of Design website

2016 has been a complicated year, and circumstances have meant that I have, rather unprofessionally, neglected this blog, my website, and the Design with Intent newsletter (which now has nearly 400 very patient subscribers).

This is just a brief note to say, mainly, that I’ve moved to the US, to Carnegie Mellon School of Design, and that (not unrelatedly) the Design with Intent book is delayed – it should be published by O’Reilly in the second half of 2017. More information on this soon.

In summer 2016 I moved on from the RCA to Carnegie Mellon University, in Pittsburgh, Pennsylvania, to become a tenure-track Assistant Professor in the School of Design. This has meant a huge life upheaval for Harriet and me, moving from a boat on the Thames at Richmond to, eventually, what I must learn to call a duplex in Friendship, a pleasant neighbo(u)rhood in Pittsburgh built for the middle managers of Carnegie Steel. At CMU, in my first semester, I have taught Play Lab, a senior design lab discussed at length here and contributed to a range of other graduate and undergraduate programmes. In the Spring, I will be teaching the junior Environments Studio – an exploratory new studio class – and, with Michael Arnold Mages and Stephen Neely, a required class called Persuasion. I will also be running PhD seminars in Research(ing) by Design(ing), continuing some of Cameron Tonkinwise’s work. (I remain a visiting tutor at the RCA, temporarily at least, to continue to supervise the PhDs of Nazlı TerzioÄŸlu, Chang Hee Lee and Dave Pao; Delfina Fantini van Ditmar passed her PhD in the summer.)

Carnegie Mellon was attractive for many reasons. The School of Design has a vision for design education and research, Transition Design, which is more exciting (and reflectively critical) than simply repeating “we’re number 1”. Transition Design is very relevant to my previous research in design for behaviour change, sustainable design, energy use, designing agency, understanding the systems around us, community-led design and many other areas, and in acknowledging “that we are living in ‘transitional times’” it enables design to be seen as a tool for engaging with complexity, with “an understanding of the interconnectedness of social, economic, political and natural systems”. I wanted to work at a university that had a professional approach to employment and career development for younger faculty, and CMU offers this to an impressive extent, along with proper employment contracts and administrative support to faculty. I wanted to work somewhere that values people’s contributions, has an informed and mature approach to research, teaching and service, that is welcoming, friendly and interested, and where the obsession is with doing things well rather than simply bringing in more and more money, and while CMU brings in plenty of money, there is a genuine commitment to excellence along with it. Most of all, I wanted to work somewhere where I would have a chance to develop and follow a vision for a programme of research and teaching, and where I would be supported and trusted to do so, where a career was possible and encouraged and with a much much flatter hierarchy of management, and I think CMU can deliver this. As an Assistant Professor, I have a lot of freedom and autonomy, much more than I would have (at this level) at any of the UK institutions I have ever worked at. It gave me lots of pride to see my Play Lab students’ work on show at Focus, the senior design exhibition, earlier this month. CMU has been welcoming, exciting, enjoyable and an enthusiastic employer so far, and I want to thank everyone who has made Harriet’s and my first few months so good.

The Britain that Harriet and I left, or rather the pre-23-June Britain, feels like the past, another country now, where, indeed, they do things differently (and with much more decorum and less pride in ignorance). It has been a very strange, and sad thing to watch from abroad as the UK determinedly keeps shooting itself in the same foot so comprehensively and with so much nastiness, and I miss, basically, the idea that the future can be better than the past. I like 1950s cars and design and writing and lots of other things, but I don’t want to live there. But of course, it’s been a very weird time to live in America too, and to see what a hugely divided country it is, and yet also not to have to experience that in everyday life: the milieu of a university professor in the US is not one where I see much opinion other than utter disdain for, and horror at, what has happened. The situation in the US, the UK, and in many other countries where danger is on the rise, leads me to articulate a possible new role / challenge for the field of design for behaviour change, which I will outline in a forthcoming blog post introducing my new lab at CMU, the Imaginaries Lab.

Aside from academic papers, a couple of books have been published:

Springer published Living Labs: Design and Assessment of Sustainable Living, a collection edited by David Keyson, Olivia Guerra-Santin (both TU Delft) and myself, with chapters covering research arising from the SusLabNWE project, a European collaboration on which I worked from 2013-15 at the Helen Hamlyn Centre. My chapters and those co-authored with Flora Bowden and others cover Powerchord, Drawing Energy and Design with Intent. The book is typically expensive for this kind of academic volume, but I am sure you can find a PDF somewhere; if not, please email me.

The Pursuit of Legible Policy: Encouraging Agency and Participation in the Complex Systems of the Contemporary Megalopolis was published by Buró Buró in Mexico City, compiling articles written as part of our British Council Newton Fund / CONACyT-funded collaboration between the RCA, Laboratorio para la Ciudad, Superflux, UNAM, and Future Cities Catapult. The book is a free download and includes a chapter by me (‘Designing Agency in the City’) alongside contributions from people such as Gabriella Gómez-Mont, Anab Jain, Gyorgyi Galik, Laura Ferrarello, John Lynch, Sofia Bosch and Carlos Gershenson.

I’ll have lots more news soon, from a range of projects and some new initiatives, so, until then: take care of each other, and let’s try, however we can, to make 2017 actively better.

First: what’s coming up in 2016?

• On 20 January, I’m talking at Behavior Design Amsterdam – thanks Wilbert Baan and Iskander Smit for the invitation
• In February, I’m off to Mexico City as the RCA lead, working with Laura Ferrarello, for a collaborative Mexico—UK project with Laboratorio para la Ciudad, Superflux, Future Cities Catapult and UNAM. Supported by the British Council’s Newton Fund, we’ll be looking at aspects of how to make policy visible, tangible and interactable-with (agency?), in the city environment, transposing ideas between Mexico City and London and vice versa. Thank you to Dan Hill, Claire Mookerjee, Gabriella Gómez-Mont, and everyone else involved in setting this up.
• From 27—30 June, DRS2016 in Brighton, the Design Research Society conference, is shaping up into an interesting and diverse programme of perspectives on design, research and society. I’m conference experience chair, along with Veronica Ranner, and we’ll be trying to help curate a good experience for everyone taking part. Some thoughts here on how you can help.
• The biggest event in 2016, scheduled for the autumn, will be O’Reilly’s publication of my Design with Intent book – see below for some more details.
• Living Labs, a book arising from the SusLabNWE project, for which I am an editor along with David Keyson and Olivia Guerra Santin from TU Delft, will be published by Springer
• ‘Taking the Code for a Walk’, written by Delfina Fantini van Ditmar and myself for Elisa Giaccardi’s ‘Connected Everyday’ forum in ACM Interactions will be published. This is a brief but exciting article detailing some of the research Delfina has done for her PhD around human interaction with the algorithmic systems of the ‘smart’ home, taking a second-order cybernetic perspective.
• ‘Plans and Speculated Actions’, a chapter that Veronica Ranner and I have written for Jonathan Chapman’s Routledge Handbook of Sustainable Product Design, should be published (though I see as I write this that the intended publication date is actually 2017). We’re exploring what happens when design for behaviour change and speculative design collide, with a sustainability focus.
• At the RCA, Research Culture Action will continue in 2016, a series of informal lunchtime talks bringing together research students and staff from across the College. Our first ‘prototype’ event, in October, featured Daisy Ginsberg, Grit Hartung and Sarah Teasley, and I’m hoping we can have them every couple of months.

In career, personal development, and work-life balance terms, 2016 needs to be very different to 2015. I won’t go into it here, but I have come to the conclusion that I need to heed Mary Dankoski‘s advice outlined here by Kate Clancy:

Dr. Dankoski asked us if we were the type of academic who lived by Plan A: did what we were asked to do and hoped we would have a rewarding fulfilling career while also meeting the promotion and tenure expectations, or Plan B: were proactive, developed a plan and negotiated responsibilities to be sure we will have vitality, find real meaning in our work, and meet promotion expectations.

You can probably guess which type most of us were, and which type Dankoski encouraged us to become. The Plan A academic says yes to most things because she is directionless and is trying to meet expectations, whereas the Plan B academic uses her personal values and interests to define and express her scholarly worth.

I have been trying to follow Plan A for the past few years, because I thought it would lead somewhere, but my resolution for 2016 is Plan B, or something better. And the main part of that is making things. I used to do it, and have done it a bit with things like Powerchord in recent years, but nowhere near to the extent I would like to. Writing papers, and book chapters, and reports that no-one will read, has squeezed out something that I really enjoyed. I need to get back to it, and find a way to make an academic career work that isn’t primarily about being seen to produce outputs, but actually to do things (and have the freedom to think about them too).

2015 certainly involved doing a lot, even if I didn’t make much. It’s strange how in an everyday life so flooded by information and essential updates from everything from household objects to people whom I vaguely remember who added me on LinkedIn, I still forget a lot of what I was doing only a few months ago. Updating my CV recently, I suddenly remembered an entire industry collaboration project I did in summer 2013, with meetings, and diagrams, and presentations and everything, that had completely slipped my mind. So, because I know that I’ll forget them if I don’t record them, below, here’s some of what happened in 2015:

10 years of this blog

The anniversary slipped by unrecorded here, but it was back in November 2005 that I first started this blog, then called Architectures of Control in Design. It changed my life: it led to changing career, doing a PhD, meeting people from all over the world. Still on the same WordPress installation, with layers of tinkering and lots of things that no longer work, the blog probably deserves a bit of attention for its 11th year.

Design with Intent book

In August I signed a contract with O’Reilly to publish a Design with Intent book, which aims to give practitioners a more nuanced approach to design and behaviour, working with people, people’s understanding, and the complexities of everyday human experience. It will build on the toolkit, and my PhD, but also what I’ve learned over the last few years on practical research projects, with people in real contexts, around people’s understanding of, and interaction with, technology and designed systems.

It’s taking longer to write than I had hoped, not due to the content as much as the difficulty of arranging uninterrupted periods of time to concentrate on writing it. That’s certainly not a problem unique to me, but it gives me new (extra) respect for people who manage to write these kinds of books alongside busy jobs, looking after children, and everything else. Publication date should be Autumn 2016: see the website for updates.

Drawing Energy book published

Drawing Energy was published in July by the RCA. Written by Flora Bowden, together with myself, Rama Gheerawo and Clare Brass, and designed by Hannah Montague, the book explores public perceptions of energy, through a drawing project Flora and I ran, in which more than 180 people illustrated their thoughts and reactions to the question ‘What does energy look like?’, as part of the Interreg IVB-funded SusLabNWE project.

You can view the drawings online, download a PDF or order a free copy of the book.

Talks

I’ve done a few talks this year, around design, behaviour, understanding and related subjects, most notably Design for Action 2015 in Washington, DC, the Hans Sauer Foundation’s Social Design Elevation Days in Munich, Product Tank in London, This Happened at Goldsmiths (on “The Power to Act: Exploring agency, design and participation in cities”), Green Sky Thinking week (as part of Max Fordham’s programme), the launch of Keep Britain Tidy’s Centre for Social Innovation. Thanks to Steve Wendel, Zarak Khan, Nynke Tromp, Ralph Boch, Barbara Lersch, Alison Austin, Gyorgyi Galik, Kate Pincott, Henry Pelly, Tim Burns and everyone else involved in these events, for the invitations.

Here’s a video of my talk at Mind The Product’s Product Tank in March.

Guardian Tech Weekly Podcast

In October I was a guest on the Guardian Tech Weekly podcast, hosted by Nathalie Nahaï, talking about dark patterns, along with Cennydd Bowles, and Geoff White from Channel 4 News. Listen to it here (I’m on at about 13 minutes in, and say “kind of” about 20 times during my few minutes of airtime).

 
Left: Relational Materials workshop, Delfina Fantini van Ditmar; Right: Cultural probes around repair, Nazlı Gökçe Terzioğlu

PhD supervision

This year I have been a visiting (i.e. entirely uncontracted adjunct) research tutor for Innovation Design Engineering at the RCA, working mainly with a wonderful group of research students, including five whom I’m supervising:

• Delfina Fantini van Ditmar (2012—2016), ‘The Internet of Dwelling’ (second-order cybernetics and human interaction with IoT and ‘smart’ homes–image above). Supervised with Professor Ashley Hall, RCA Innovation Design Engineering and Dr Paul Pangaro, College for Creative Studies, Detroit
• Dr Dave Pao (MBBS, MRCP, MD) (2013—present), ‘Design as the 3rd voice in the clinician-patient conversation’ (new interfaces for facilitating conversations in sexual health contexts). Supervised with Dr John Stevens, RCA Global Innovation Design
• Nazlı Gökçe TerzioÄŸlu (2013—present), ‘Exploring the Means of Creating New Relationships between Users and Products Through Repair’–image above. Supervised with Clare Brass, SustainRCA
• Hugo Glover (2013—present), ‘Stereoscopic Spatiality: A Practice-based Investigation into the Use of Stereoscopic 3D‐Depth Technologies in Physical and Digital Space’. Supervised with Neil Barron, RCA Innovation Design Engineering
• Chang Hee Lee (2014—present), ‘Synaesthesia Materialisation: Synaesthetic Inputs within the Product Design Industry’. Supervised with Dr John Stevens, RCA Global Innovation Design

Thanks to all the IDE research students for all your enthusiasm and help this year, and well done on everything you’ve achieved. In November, Nazlı Gökçe TerzioÄŸlu and Yoon Choi both presented papers at Sustainable Innovation 2015 on which I was a co-author, covering two intriguing directions in understanding (and changing) people’s relationships with products from a sustainability perspective:

–TerzioÄŸlu, N., Brass, C. & Lockton, D. (2015) ‘Understanding user motivations and drawbacks related to product repair’. Sustainable Innovation 2015, 9-10 November 2015, Epsom, UK. (PDF)

–Choi, Y., Lockton, D., Brass, C., & Stevens, J. (2015) ‘Opportunities for sustainable packaging design: Learning from pregnancy as a metaphor’. Sustainable Innovation 2015, 9-10 November 2015, Epsom, UK. (PDF on ResearchGate)

V&A Design Culture Salon

As my look of terror / staring into nothingness in the above photo (by Jonny Jiang) might suggest, I chaired a Design Culture Salon at the V&A in November, with the title “Is Designing for Behaviour Change ‘Creepy’?” With a fantastic panel of Alison Powell, Phoebe Moore, Jessica Pykett, Peter John and Simon Blyth, we debated issues from the Quantified Self to the Nudge Unit to algorithmic governance: all with a “design and behaviour” theme, too broad really for a single event, but very enjoyable. Thanks to Guy Julier and Leah Armstrong for organising the event, to the panellists, and to so many people who came to see and take part.

Here’s a transcript of my introduction (I’m partly putting it here for future reference), while there are some reflections here from Lucy Kimbell, Jocelyn Bailey and Stephen Feber, collated by Guy Julier, and Phoebe Moore has written up her introductory talk, covering specifically design for behaviour change in the workplace.

The Performance of Nonhuman Behaviour

In June, I ran a workshop at Nordes 2015, at Konstfack, in Stockholm, with Delfina Fantini van Ditmar and Claudia Dutson, looking at conversations between people and machines. We packed a lot into the day, with some great participants, but my part of the workshop was mostly focused on “thinking about how machines think we think”–applying some basic forms from R.D. Laing’s Knots to situations that might arise in the smart home (or other algorithmic developments). We got some nice examples of knot-like scenarios, particularly around people trying to cajole the technology to make different assumptions. I can see why, as Paul Pangaro commented, Gordon Pask liked Knots so much. I am, slowly, working on a paper drawing on some of the ideas generated in the workshop: thank you to all the participants and to Salu Ylirisku for the organisation.

One Another: Empathy and Experience

In October, Dr Katie Gaudion and I ran One Another: Empathy and Experience, a week-long ‘AcrossRCA’ course exploring questions of how we can experience the world as someone (or something) else does. With participants from eight different RCA MA and PhD programmes, over the week, we had a talk from Jon Adams, an autistic artist with synaesthesia, we visited London Zoo to explore the world from animals’ points of view (and human interactions), and through practical experiments, tried to see if we could “generate” empathy for inanimate objects, such as paper tissues, leaves and headphones. We backed up the practical work with some theoretical psychology background around theory of mind, empathy and the fundamental attribution error. The week ended with three really brilliant group projects, which invited participants to try to experience the world through the perspective of another:
– The Human Zoo, by Sarha Hersi, Joey (Jupone) Wang, Saaya Kamita, Mariana Pedrosa
– Obsessions, by Thomas Leech, Faith Wray, Andrea Fischer, Heeju Kim and Chang Hee Lee
– Empathising with Claustrophobia (centre, above), by Anna Dakin, Harry Thompson, Nong Chotipatoomwan and Tess Dumon

Rice University Urban Sustainability and Livability Summer Institute

The end of May and early June saw Flora Bowden, Claudia Dutson, Delfina Fantini van Ditmar and myself run Learning New Ways of Looking at the City, an international summer programme for Rice University’s Urban Sustainability and Livability Summer Institute, at the Danish Institute for Study Abroad, in Copenhagen. With visits over three weeks, working with an impressively enthusiastic and motivated group of Rice students, we used Copenhagen as a setting to explore questions around transport and mobility, tourism, green space, and cultural differences, among other issues, through student research projects. Thanks to Don Ostdiek, Michael Emerson and Julia Grasse for the organisation, and thanks to Anne-Kathrine Kjær Christensen and Larry Toups for visiting contributions.

Kingston University MACE Startup Weekend

At the end of September, I returned to Kingston Business School’s MA Creative Industries and the Creative Economy, to run the Startup Weekend, a two-day workshop right at the start of the course, in which new students on this unique programme, combining design and business (with the practical requirement of creating a business by the end of the course), get a rapid introduction to design research and prototyping and carry out a group project responding to a real-life problem they have identified. In 2014, we looked at the experience of new international students; in 2015 we focused on money, with field research in Kingston town centre, including visiting (and comparing the customer experience at) Metro Bank and some more traditional establishments, and a guest talk from Stephen Wendel via Skype. Groups came up with some clever concepts, including a service that automatically puts change onto a card, new kinds of international money transfer service, and redesigning how Argos works. Thanks to Janja Song, and Mark Passera who originally invited me.

Visit to Carnegie Mellon

In November, I visited Carnegie Mellon University in Pittsburgh, to do a talk / mini-workshop called Design, Behaviour & Understanding, in the School of Design, for Master’s students in Molly Steenson’s Interaction and Service Design class, and a talk called People Don’t Really Use Energy for the Intelligent Workplace team in the School of Architecture. I also got to meet some very interesting people (students and staff), and take part in one of the Design PhD group discussions, which was very enjoyable. Thank you to Cameron Tonkinwise, Kakee Scott, Darlene Scalese, Jane Ditmore, Molly Steenson, Simon King, Terry Irwin, Peter Scupelli, Bruce Hanington, Michael Arnold Mages, Dimeji Onafuwa, and everyone else who arranged my visit and made me feel so welcome.

Good luck everyone for 2016: it’s going to be what we make it!

How can we invert ‘design for behaviour change’ and apply it from below, enabling people to understand, act within, and change the behaviour of the systems of society and the environment?
 

[This article is cross-posted to Medium where there may also be readers’ comments]

As our everyday lives are increasingly pushed and pulled by technology and the systems around us, from infrastructure to quantification to government to horrifying combinations of these, understanding these complex systems, and how to change them, is something we should be paying attention to. In ‘As we may understand’, last year, I looked—at excessive length—at the understanding bit, but not the change. Hopefully here I can address that, to some extent, though my thinking’s moved on a bit.

Paralysis and regret

We are surrounded by, and enmeshed in, complexity which at once causes us paralysis over not being able to take action, and regret over the actions we do take (and continue to take). We simultaneously worry and do nothing about issues such as the military-industrial surveillance state, ageing populations, inequality, war and privatisation of the commons. We fudge our responses to planetary-scale crises such as climate change, pollution or poverty because our understanding of what we are able to do locally does not match our understanding of what is possible at a larger scale. We face a crisis of agency, in the phrase used by Gyorgyi Galik, Natalie Jeremijenko, Zygmunt Bauman and others.

How can ‘we’ (at the level of individual people—and I’m speaking from the position of a middle-class Western consumer, with all that entails) act? We don’t know what to do, and even if we did, we are not individual “micro-resource managers” (to use Yolande Strengers’ phrase), but people acting within the constraints (and enablers) of family, society, social groups, cultural contexts, norms and expectations. We lack the ability to hold different visions of possible futures in mind simultaneously, or even to think through the consequences and possibilities at multiple levels. We are entangled in social traps, double binds and knots around everything from participation in democracy (why bother? it won’t change anything) to dealing with terrorism (be alert, but not scared, because that’s what they want, so still be very very very alert).

What can designers do?

What is designers’ role in this? Both design and sustainability, in its broadest sense, are about “the future”—bringing into being a world where humanity and other forms of life will “flourish on the planet forever” (John Ehrenfeld) or where we can “go about our daily affairs… [knowing] that our activities as civilised beings are expanding our future options and improving our current situation” (Bruce Sterling). Design might be one of the mechanisms by which much of our current predicament has come about (Victor Papanek), but perhaps “the future with a future for “us” can only be reached by design” (Tony Fry).

Designing for behaviour change at the mundane level of helping people recycle things, or use their electrical appliances more efficiently—the sort of thing a lot of my previous work has focused on—might be part of the solution, but it’s clear that design really needs to address things at a much higher, more systemic level, including designing things out of existence. Perhaps, in terms of producing a new generation of designers ready to engage with this degree of challenge, this is what transition design can bring us. I hope so.

Understanding complexity

To engage with this complexity—not destroy its variety, because we can’t and we shouldn’t—requires designers to understand society better. Yes, we need designers to understand people’s lives, and appreciate the realities of situated decision making and subjective experience, but also to understand complexity, connectedness (in a technology sense but a people sense too) and the effects of design, and its politics, to a degree beyond what might previously have been common. We need designers to engage with the invisible ‘dark matter’ (Dan Hill) even though it may often be experienced as an impediment to action.

We need designers to understand (and be allowed to deal with) the wickedness of the problems we are facing: they will not be understood until ‘solutions’ have been attempted (which will in turn create new problems, as John Gall pointed out); there will be no stopping rules; there will be no right or wrong answers; and all attempts to deal with a problem will only highlight its uniqueness and contextual peculiarity. We will not be able to step in the same river twice, nor even once (as Ranulph Glanville suggests), and we must make peace with that. It doesn’t mean we can’t learn from what we’ve done before, but we cannot presume that patterns always transpose effectively. Deterministic top-down approaches promoted by behavioural economics and simplistic notions of the ‘Quantified Self’ and ‘Big Data’ are not going to work.

Understanding how to act

Of course, understanding complexity is not the goal in itself. The real goal is understanding what agency is possible, and how to enact change. So, we need design that enables people to understand the wider contexts of their actions, their agency within society, and how they can act to create different outcomes, different futures.

Understanding how to act to change the systems we’re in is arguably the biggest meta-challenge of our age. We need not just information, but tools for connecting our understanding of how things work and how we can act, around everything from the environment, cities, our own bodies, networked infrastructure to social, civic and political contexts, emerging technologies and plural considerations of the future itself.

This is design for behaviour change, but is not about designers trying to change ‘public behaviour’ as if it were somehow a separate phenomenon. Designers are members of society, and there is only one Earth: we are part of the same systems. It is about design which enables people to change the behaviour of the systems of which they—we—are part.

Ways of doing this

What do we do, then? I imagine a ‘Designing Agency’ research / action programme, which would rethink how we engage with the systems of everyday (and future) life, through developing new approaches to understanding and action. Designing Agency would use ‘design’—in the broadest sense—as a way to:

1. understand the world
2. understand people’s understandings of the world
3. help people understand the world
4. help people understand their agency in the world
5. help people use that agency in the world

We could see these as a progression from understanding to action. But how would we do it in practice? Different techniques would be effective at different levels. Some would be investigatory, some practical, some speculative or critical. Some would give us tools for understanding and learning, some tools for doing, some provocations for reflection. The examples I have here are quite pedestrian.

A ‘comfort timeline’ heating practice diary developed by Natalia Romero Herrera, TU Delft, being used here by a householder in Dartford, UK.

For example, at Level 1, using design to understand the world might involve designing and deploying probes (e.g. the heating diary shown here), and running designed experiments, which investigate phenomena in the world (including society) through gathering data in a way which provides meaningful scaffolding for the next level. This is essentially using design as a way to do science, or social science.

Level 2, in attempting to ‘understand understanding’ (in Heinz von Foerster’s phrase), would take things a stage further: using activities which practically try to explore the different ways in which people imagine, conceptualise and think about how things work. Very basically, we could use techniques such as drawing (as in the image at the top of the article, from the Drawing Energy project), but there’s a whole world of possibilities here. It is partly about making the invisible visible, tangible or legible, from the point of view of people themselves (i.e. what is legible, or not, to them), but also about surfacing people’s different understandings of situations, and how that leads different people to act.

Claustrophobia simulation apparatus, developed by Anna Dakin, Harry Thompson, Nong Chotipatoomwan and Tess Dumon as part of ‘One Another: Empathy and Experience’, AcrossRCA course by Katie Gaudion & Dan Lockton

At Level 3, we’d be designing ways which help change people’s understandings of the world and the systems they’re in. This could take the form of new kinds of interface, designed experiences, educational activities—a range of things.Some of the examples collected by Dieter Zinnbauer’s Ambient Accountability project perhaps fit here. It could be about changing mental models, expanding horizons, reframing of situations, or even trying to facilitate empathy (as in the image). I want to make it clear here that this isn’t about ‘correcting incorrect mental models’ but about enabling and supporting people to construct and refine their own models of the world, experientially, which serve them better. And learning how to reflect on that.

I don’t really know, at this stage, what Level 4 would look like. This is the “let’s see what we can do” of the title. I have some ideas, but they need work: I imagine new forms of interface, new ‘senses’, new metaphors (in the sense suggested by Margaret Mead and also by A. Baki Kocabelli—see below) and new analogues: not just behaviour quantification and data dashboards, but highlighters and contextual explainers of agency. I am very excited about this, and aim to come back to it with another article very soon, once I’ve actually built something. Let’s just say, qualitative interfaces…

At Level 5, among other things, we would pretty much be challenging and inverting common ‘behavioural design’ paradigms. We have a whole load of them, of course, but what can they do if you turn them upside down? What does it look like when the public uses a technique like Commitment & Consistency or Are You Sure? or Watermarking to change the behaviour of a system like policing or energy policy? Can it be more constructive than ‘fighting back’, and actually be about co-designing systems of society that behave more effectively, and work better for more people? Again, these could be applied critically, or provocatively—a what if?—or they could be direct ways of enabling action, empowering people to change the behaviour of the systems in which we live.

At this level, we should be mindful of our roles as designers within the systems we are aiming to help people change. The power dynamics, and our assumptions about the people we are designing with or for, need to be surfaced and questioned. We need to be aware of—and honest about—our inherent subjectivity: as Hugh Dubberly and Paul Pangaro point out:

“Framing wicked problems requires explicit values and viewpoints, accompanied by the responsibility to justify them with explicit arguments, thus incorporating subjectivity and the epistemology of second-order cybernetics.”

In this vein, A. Baki Kocaballi has written very usefully about agency sensitive design, particularly the notion of relationality (recognising that assumptions of neither full technological determinism, nor full social determinism, are useful when understanding agency in context):

“In design processes, the quality of relationality asks for three sensitivities: (i) understanding of mutual influence, shaping and co-constitution of actors and artefacts; (ii) embracing and supporting emergent and improvised action and (iii) consideration of the system as an assemblage/network of actors, artefacts or collective hybrids. In order to develop these sensitivities, we first need to stop formulating design solutions based upon the assumption of a well-defined individual with fixed characteristics and capacities of action. Design solutions should recognize and support the existence of the multiple individuals embodied in one individual and the possibility of multiple enactments of one individual within a network of other human and non-human actors interacting with each other and exhibiting different capacities for action.”

Kocaballi’s six qualities for agency sensitive design—relationality, visibility, multiplicity, configurability, accountability and duality—could be a valuable set of considerations to explore in relation to the design of these ‘Level 5’ attempts to help people use their agency in the world.

What next?

I need to stop writing about things like this, and get back to doing it. I’ve had my own career-related crisis of agency in 2015, but 2016 is going to be better. First up is an amazing opportunity working with Laboratorio para la Ciudad, Superflux, Future Cities Catapult and UNAM on a joint project between Mexico City and London, funded by the British Council’s Newton Fund, in which (I’m hoping) at least a bit of levels 4 and 5 can come into play, in the context of helping people understand their agency, and act in relation to policy in the built environment.

We’ll have to see what we can do.

Thank you to Veronica Ranner, Gyorgyi Galik, Delfina Fantini van Ditmar and Laura Ferrarello for conversations which have led to ideas in this article.

[See also readers’ comments / responses on Medium]

Design is increasingly about people’s behaviour, but this is often considered simplistically. The Design with Intent book aims to give practitioners a more nuanced approach to design and behaviour, working with people, people’s understanding, and the complexities of everyday human experience.

It will build on the toolkit, and my PhD, but also what I’ve learned over the last few years on practical research projects, with people in real contexts, around people’s understanding of, and interaction with, technology and designed systems, including SusLab, Creative Citizens, CarbonCulture at DECC and Creating Sustainable Innovation. The book will also build on examples, good and bad, from all over the world, addressing a wide range of problems and contexts, both social and commercial. It’ll cover design across products, services and environments, physical and digital (and, increasingly, in combination), and I’ll be asking for readers’ suggestions and examples for particular ideas and themes.

I’m hoping that the book will offer a more nuanced approach to designing around people’s behaviour, based on designing and researching with people rather than ‘for’ them, learning from people’s understanding of the world, and embracing the complexities of everyday human experience. As I said last year, I’m increasingly uncomfortable with how I see “design for behaviour change”, and the “behaviour change agenda”, being applied in practice, with simplistic, deterministic and individualist approaches which often seem to be about treating humans as defective components, that need to be constrained or tricked, denying variety, complexity, culture and social context. I started blogging ten years ago specifically to explore and critique the use of design to control and exert power, and that hasn’t gone away.

Writing the book is going to be a big job alongside my work at the RCA, and my plan is to blog the process to keep myself on track–partly also to get suggestions and input along the way. So please do keep an eye on the site, and sign up to the newsletter for updates. Thanks to everyone who gave me the confidence to take the plunge with this!

It’s been a bit of a chaotic time recently, both in family terms and professionally, so my apologies for the lack of updates. In February I started as Visiting Research Tutor in Innovation Design Engineering (IDE) at the RCA, helping develop a programme of research and helping to supervise a group of excellent PhD researchers with a range of very interesting projects. IDE has one of the largest design research cohorts within the RCA, and I am looking forward to helping develop this further, in some new directions, through both academic and industry collaborations.

Part of this, from my point of view, will be reinvigorating and developing the Design & Behaviour Research Network which I started back in 2008, into something more substantial and which can build on other work such such as last year’s Creating Sustainable Innovation project. If you’re interested in collaborating, please get in touch.

At Nordes 2015 at Konstfack in Stockholm in June, I will be running a workshop, The Performance of Nonhuman Behaviour, with Delfina Fantini van Ditmar (IDE PhD candidate) and Claudia Dutson (Architecture PhD candidate). My part of the workshop builds on many of the ideas explored in this blog over the years, around people’s understanding of the systems they interact with, and I’m hoping it will be a fun and useful event. More details in due course.

Some background

I’ll be blunt here: academic career prospects for what are termed “early career researchers” in the UK are not great, particularly in subjects which fall between the cracks of major research councils’ funding scope, and particularly at places like the RCA which don’t have any kind of staff development programme for researchers, and which depend heavily on “visiting” and part-time staff, often with no contract at all. My choices have been, essentially: 1) bring in enough funding to pay my own salary plus all of the overheads which universities require (which I have tried to do, and am trying to do, but which is very difficult starting from a near-zero base); 2) work on others’ projects on a series of short-term contracts, with little strategic input (which I don’t mind doing if I have to, but which is a step backwards); 3) leave and go somewhere with better support for early career staff. The RCA has some fantastic people, both students and staff, so I am trying option 1), as best I can, but I am aware that as an institution, it doesn’t try very hard to hold onto people.

In option 2) terms, working for the Helen Hamlyn Centre together with Vehicle Design at the RCA, I have temporarily (since January) also been project manager for setting up the public engagement work package of GATEway, an £8 million Innovate UK project looking at understanding and demonstrating driverless cars in the UK, led by TRL in conjunction with partners including the Royal Borough of Greenwich, Commonplace, and Shell. The introduction of new technology of this kind, the designed systems, services and infrastructure around it, and the potential effects on everything from urban planning to jobs, is fascinating, and I will be intrigued to see how the project develops and what it finds.

SusLab, Drawing Energy and Powerchord

My job at the Helen Hamlyn Centre as part of the RCA’s role in SusLab has ended when the RCA’s funding ended, although I am still contributing to the project by supporting other partners in analysis and writing up of the results, and co-editing an academic book with Professor David Keyson and Dr Olivia Guerra Santin from TU Delft.

From the UK perspective, our book Drawing Energy, on which Flora Bowden has led, with myself, Clare Brass and Rama Gheerawo as co-authors, should be published in June this year by the Helen Hamlyn Centre. I’ll put more details on the SusLab at the RCA blog when they’re available.

I am going to continue to work on Powerchord, the home energy sonification system, as a personal project. Being freed of the constraints of a major project ought to make this easier and faster, though of course without the benefit of funding. Claire Matthews has produced a brilliant range of sound schemes, and I’m hoping that a Mark II version of Powerchord using Jack Kelly’s approach to extracting CurrentCost/EDF individual appliance monitor data will prove more flexible than the previous approach. More news on this in due course.

Design with Intent

In February, while I was en route to Munich to talk at the wonderful Hans Sauer Foundation Social Design Elevation Days, a PHP upgrade by the webhost, combined with a long outdated version of MediaWiki meant that the Design with Intent website became unusable (blank, basically). My botched attempt to fix it rapidly via FTP, hotspotting from my phone in an airport departure lounge, made things worse. So I have put up a temporary site which has most of the same content, but does not have individual pages for each pattern. Something better is on the way when I get a spare weekend…

In a world of increasingly complex systems, we could enable social and environmental behaviour change by using IoT-type technologies for practical co-creation and constructionist public engagement.

[This article is cross-posted to Medium, where there are some very useful notes attached by readers]

We’re heading into a world of increasingly complex engineered systems in everyday life, from smart cities, smart electricity grids and networked infrastructure on the one hand, to ourselves, personally, being always connected to each other: it’s not going to be just an Internet of Things, but very much an Internet of Things and People, and Communities, too.

Yet there is a disconnect between the potential quality of life benefits for society, and people’s understanding of these—often invisible—systems around us. How do they work? Who runs them? What can they help me do? How can they help my community?

IoT technology and the ecosystems around it could enable behaviour change for social and environmental sustainability in a wide range of areas, from energy use to civic engagement and empowerment. But the systems need to be intelligible, for people to be engaged and make the most of the opportunities and possibilities for innovation and progress.

They need to be designed with people at the heart of the process, and that means designing with people themselves: practical co-creation, and constructionist public engagement where people can explore these systems and learn how they work in the context of everyday life rather than solely in the abstract visions of city planners and technology companies.

Understanding things

The internet, particularly the world-wide web, has done many things, but something it has done particularly well is to enable us to understand the world around us better. From having the sum of human knowledge in our pockets, to generating conversation and empathy between people who would never otherwise have met, to being able to look up how to fix the washing machine, this connectedness, this interactivity, this understanding, has–quickly–led to changes in everyday life, in social practices, habits, routines, decision processes, behaviour, in huge ways, not always predictably.

It’s surfaced information which existed, but which was difficult to find or see, and–most importantly–links between ideas (as Vannevar Bush, and later Ted Nelson, envisaged), at multiple levels of abstraction, in a way which makes discovery more immediate. And it’s linked people in the process, indeed turned them into creators and curators on a vast scale, of photos, videos, games and writing (short-form and longer). It may not all be hand-coding HTML, but perhaps much of it followed, ultimately, from the ability to ‘View Source’, GeoCities, Xoom, et al, and the inspiration to create, adapt and experiment.

But how do things fit into this? How can the Internet of Things, ambient intelligence and ubiquitous, pervasive computing, help people understand the world better? Could they enable more than just clever home automation-via-apps, more-precisely-targeted behavioural advertising, and remote infrastructure monitoring, and actually help people understand and engage with the complex systems around them—the systems we’re part of, that affect what we do and can do, and are in turn affected by what we do? Even as the networks become ever more complex, can the Internet of Things—together with the wider internet—help people realise what they can do, creating opportunities for new forms of civic engagement and empowerment, of social innovation, of sustainability?

In this article, I’m going to meander a bit back and forth between themes and areas. Please bear with me. And this is very much a draft–a rambling, unfocused draft–on which I really do welcome your comments and suggestions.

Design and behaviour change

For the last few years, I’ve been working in the field of what’s come to be known as design for behaviour change, mostly, more specifically, design for sustainable behaviour. This is all about using the design of systems–interfaces, products, services, environments–to enable, motivate, constrain or otherwise influence people to do things in different ways. The overall intention is social and environmental benefit through ‘behaviour change’, which is, I hope, less baldly top-down and individualist than it may sound. I am much more comfortable at the ‘enable’ end of the spectrum than the ‘constrain’. The more I type the phrase ‘behaviour change’, the less I like it, but it’s politically fashionable and has kept a roof over my head for a few years.

As part of my PhD research, I collected together insights and examples from lots of different disciplines that were relevant, and put them into a ‘design pattern’ form, the Design with Intent toolkit, which lots of people seem to have found useful. All of the patterns exemplify particular models of human behaviour–assumptions about ‘what people are like’, what motivates them, how homogeneous they are in their actions and thoughts, and so on–often conflicting, sometimes optimistic about people, sometimes less so. Each design pattern is essentially an argument about human nature. Some of them are nice, some of them are not.

However, in applying some of the (nicer!) ideas in practice, particularly towards influencing more sustainable behaviour at work and at home, around issues such as office occupancy and food choices, as well as energy use, it became clear that the models of people inherent in many kinds of ‘intervention’ are simply not nuanced enough to address the complexity and diversity of real people, making situated decisions in real-life contexts, embedded in the complex webs of social practices that everyday life entails. (This is, I feel, something also lacking in many current behavioural economics-inspired treatments of complex social issues.)

Many of the issues with the ‘behaviour change’ phenomenon can be characterised as deficiencies in inclusion: the extent to which people who are the ‘targets’ of the behaviour change are included in the design process for those ‘interventions’ (this terminology itself is inappropriate), and the extent to which the diversity and complexity of real people’s lives is reflected and accommodated in the measures proposed and implemented. This suggests that a more participatory process, one in which people co-create whatever it is that is intended to help them change behaviour, is preferable to a top-down approach. Designing with people, rather than for people.

Another issue, noted by Carl DiSalvo, Phoebe Sengers and Hrönn Brynjarsdóttir in 2010, is the distinction between modelling “users as the problem” in the first place, and “solving users’ problems” in approaches to design for behaviour change. The common approach assumes that differences in outcome will result from changes to people–‘if only we can make people more motivated’; ‘if only we can persuade people to do this’; ‘if only people would stop doing that’–overcoming cognitive biases, being more attentive, caring about things, being more thoughtful, and so on.

But considering questions of attitude, beliefs or motivations in isolation rather than in context–the person and the social or environmental situation in which someone acts (following Kurt Lewin and Herbert Simon)–can lead to what is known as the fundamental attribution error. Here, for example, some behaviour exhibited by other people–e.g. driving a short distance from office to library–is attributed to ‘incorrect’ attitudes, laziness, lack of motivation, or ignorance, rather than considering the contextual factors which one might use to explain one’s own behaviour in a similar situation–e.g. needing to carry lots of books (this example courtesy of Deborah Du Nann Winter and Susan M. Koger).

So, framing behaviour change as helping people do things better, rather than trying to ‘overcome irrationality’ as if it were something that exists independently of context, offers a much more positive perspective: solving people’s problems–with them–as a way of enacting behaviour change, from the initial viewpoint of trying to understand, in context, the problems that people are trying to solve or overcome in everyday life, rather than adopting a model of defects in people’s attitudes or motivation which need to be ‘fixed’.

Something that has arisen, for me, during ethnographic research and other contextual enquiry around things like interaction with heating systems, energy (electricity and gas) use more widely—and even seemingly unrelated issues such as neighbourhood planning, or a community group’s use of DropBox—is the importance of people’s understanding and perceptions of the systems around them. Questions about perceived agency, mental models of how things work, assumptions about what affects what, conflating one concept or entity with another, and so on, feed into our decision processes, and the differences in understanding can cause conflict or undesired outcomes for different actors within the system.

As Dan Hill puts it, if we can “connect [people’s] behaviour to the performance of the wider systems they exist within” we can help them “begin to understand the relationships between individuals, communities, environments and systems in more detail”.

But it seems as though most approaches to design for behaviour change–and it’s a rapidly growing field under different labels–either ignore questions around understanding entirely, or try to find out about how users (mis)understand things, and then attempt to change users’ understanding to make it ‘correct’. Many, in fact, start straight out to try to change understanding without trying to find anything out about users’ current understanding. A few (but not enough, perhaps) try to adjust the way a system works so that it matches users’ understanding. (This is a development of something I explored in a London IA talk a few years ago.)

Also, I must emphasise at this point that ‘behaviour change’ is not really a thing at all. ‘People doing something differently’ covers so much, across so many fields and contexts, that it’s silly to think it can be assessed properly in a simple way.

If anyone is really an ‘expert’ in ‘behaviour change’, it is parents and teachers and wise elderly raconteurs of lives well lived, children with youthful clarity of insight, people who strike up conversations with strangers on the bus, or talk down people about to jump off bridges: optimistic, experienced (or not) human students of human nature, not someone who sees ‘the public’ as a separate category to him- or herself, ripe for ‘intervention’.

The Internet of Things as an innovation space

One of the nicest things about the Internet of Things phenomenon–and indeed the Quantified Self movement–as opposed to that other, related, topic of our time, the top-down ‘Smart City’, is the extent to which it crosses over with the bottom-up, almost democratic, Maker movement mentality. I’m using ‘the IoT’ here as a broad category for the potential to involve objects and sensors and networks in areas or situations that previously didn’t have them.

The Internet of Things, through initiatives such as Alexandra Deschamps-Sonsino’s IoT meetups and others–while undoubtedly boosted commercially by Gartner Hype Cycle-baiting corporate buzzword PowerPoints–has been to no small extent driven by people doing this stuff for themselves. And helping each other to do it better. The peer support for anyone interested in getting into this area is immense and impressive: you can bet that someone out there will offer assistance, suggest ways round a problem, and share their experience. The barriers to entry are relatively low, and there are organisations and projects springing up whose rationale is based around lowering those barriers further.

The IoT is a huge von Hippel user innovation space, and it involves not just innovation by users, but innovation that is about building things. Its very sustenance is people building things to try out hypotheses, addressing and reframing their own problems responding to their own everyday contexts, modifying and iterating and joining and forking and evolving what they’re doing, putting the output from one project into the input of another, often someone else’s. And yet it is still quite a small community in a global sense, overrepresented in the echo-chamber of the sorts of people likely to be reading this article.

Constructionism and co-creation

I suspect there is something about the open structure of many IoT technologies (and those which have enabled it) which has made this kind of distributed, collaborative community of builders and testers and people with ideas more likely to happen. It may just be the openness, but I think it’s more than that. There are three other elements which might be important:

• Linking the real world to a virtual, abstract, invisible one. Even if an IoT project is about translating one physical phenomenon into another, this action comes about through links to an invisible world. I don’t know for certain why that might be important, but I think it may be that it triggers thinking about how the system works, in a way that is still somewhat outside our everyday experience. This kind of action-at-a-distance retains some magic, in the process calling new mental models or simulations into existence…
• …which are then tested and iterated, because nothing ever works first time. This means people learn through doing things, through coming up with ideas about how things work, and testing those hypotheses by their own hand, often understanding things at quite different levels of abstraction (but that still being just fine). It’s not a field that’s particularly suited to learning from a book (despite some excellent contributions)…
• …and indeed the boundaries of what the IoT is for are so fluid and expansive in a ‘What use is a baby?’ sense that the goal is one of exploration rather than ‘mastery’ of the subject. There is no right or wrong way to do a lot of this stuff, nor limits imposed by any kind of central authority.

I’m no scholar of educational theory, but it seems that these kinds of characteristics are similar to what Seymour Papert, father of LOGO and student of Jean Piaget, termed constructionism–in the words of the One Laptop Per Child project,

“a philosophy of education in which children learn by doing and making in a public, guided, collaborative process including feedback from peers, not just from teachers. They explore and discover instead of being force fed information”.

Constructionist learning (whether with children or adults) is not a ‘leave them to it’ approach: it involves a significant degree of facilitation, including designing the tools (like LOGO, or Scratch) that enable people to create tools for themselves. Returning to the design context, this is a central issue in discussions of participatory design, co-design and co-creation–to what extent, and how, designers are most usefully involved in the process. What are the boundaries of co-creation? How do they differ in different contexts? Is the progression from design for people to design with people to design by people an inevitability? Whither the designer in the end case?

Setting aside this kind of debate for the moment, I am going to say that for the purposes of this article:

• involving people (‘users’, though they are more than that) in a design process…
• to address problems which are meaningful for them, in their life contexts…
• in which they participate through making, testing and modifying systems or parts of systems…
• partly facilitated or supported by designers or ‘experts’…
• in a way which improves people’s understanding of the systems they’re engaging with, and issues surrounding them…

meets a definition of ‘constructionist co-creation’.

Behaviour change through constructionist co-creation

Now, let’s go back to behaviour change. I mentioned earlier my contention that much of what’s wrong with the ‘behaviour change’ phenomenon is about deficiencies in inclusion. People (‘the public’) are so often seen as targets to have behaviour change ‘done to them’, rather than being included in the design process. This means that the design ‘interventions’ developed end up being designed for a stereotyped, fictional model of the public rather than the nuanced reality.

Every discipline which deals with people, however tangentially, has its own models of human behaviour–assumptions about how people will act, what people are ‘like’, and how to get them to do something different (as Susan Weinschenk notes). As Adam Greenfield puts it:

“Every technology and every ensemble of technologies encodes a hypothesis about human behaviour”.

All design is about modelling situations, as Hugh Dubberly and Paul Pangaro and before them, Christopher Alexander remind us. Even design which does not explicitly consider a ‘user’ inevitably models human behaviour in some way, even if by omitting to consider people. Modelling inescapably has limitations–Chris Argyris and Donald Schön suggested that “an interventionist is a man struggling to make his model of man come true”–but of course, although “all models are wrong…, some are useful.”

In design for behaviour change, we need to recognise the limitations of our models, and be much clearer about the assumptions we are making about behaviour. We also need to recognise the diversity and heterogeneity of people, across cultures, across different levels of need and ability, but also across situations. This approach is something like attempting to engage with the complexity of real life rather than simplifying it away–in Steve Portigal’s words:

“rather than create distancing caricatures, tell stories… Look for ways to represent what you’ve learned in a way that maintains the messiness of actual human beings.”

What’s a way to do this? Co-creation, co-production–in a behaviour change context–enables us to include a more diverse set of people, leading to a more nuanced treatment of everyday life. This, in itself, represents an advance in inclusion terms over much work in this field. Flora Bowden and I have tried to take this approach as part of our work on the European SusLab energy project.

But going further, constructionist co-creation for behaviour change would enable people actually to create, test, iterate and refine tools for understanding, and influencing, their own behaviour. Just look at Lifehacker or LifeProTips, GetMotivated or even the venerable 43 Folders. People enjoy exploring ways to change their own behaviour, through experimenting, through discussion with others, and through developing their own tools and adapting others’, to help understand themselves and other people, and the systems of everyday life which affect what we do. Behaviour change could be direct–or it could be, perhaps more interestingly, directed towards exploring and improving our understanding of the systems around us.

Invisible infrastructures and the Internet of Things: avoiding the demon-haunted smart fridge

The thing is, the systems around us are complex and becoming more so, and often invisible–or “distressingly opaque”–in the process, which makes them more difficult to understand and engage with. This includes everything from ‘the Cloud’ (which, as Dan Hon notes, is coming to the fore with news stories such as celebrity photo hacking) to Facebook (as danah boyd puts it, “as the public, we can only guess what the black box is doing”) to CCTV and other urban sensor networks.

(Right: An interesting infrastructure ‘business model’ from the Public Safety Charitable Trust–see http://www.elyplace.com/bluetooth-rates-avoidance-scheme-fails/)

Timo Arnall, in his PhD thesis, introduces this issue using the example of smartphones, “perhaps the most visible aspect of contemporary, digitally-mediated, everyday-life. Yet the complex networks of systems and infrastructures that allow a smartphone to operate remain largely invisible and unknown.”

He goes on to explore, via some beautiful projects, another invisible infrastructure–RFID and near-field communication– and the possibilities of making this visible, tangible and legible.

Most diagrams or infographics aiming to illustrate the Internet of Things show visible lines connecting objects to each other, or to central hubs of some kind. But whatever forms the IoT takes, most of these are going to be ‘invisible by default’, in Mayo Nissen’s words (specifically referring to urban sensors). Invisibility might seem attractive, and magic (and we’ll get onto seamlessness in a bit) but by its very nature it conceals the links between things, between organisations, between people and purpose:

“Some sensing technologies capture our imagination and attract our constant attention. Yet many go unnoticed, their insides packed with unknowable electronic components, ceaselessly counting, measuring, and transmitting. For what purpose, or to whose gain, is often unclear… there is seldom any information to explain what these barnacles of our urban landscape are or what they are doing.”

(Above and below: Black boxes and mental models: an exercise at dConstruct 2011. Some photos by Sadhna Jain.)

Back in 2011 I ran a workshop at dConstruct including an exercise where groups each received a ‘black box’, an unknown electronic device with an unlabelled interface of buttons, ‘volume’ controls and LEDs, housed in a Poundland lunchbox and badly assembled one evening while watching a Bill Hicks documentary and drinking whisky.

Internally —and so secretly—each box also contained a wireless transmitter, receiver, sound chip and speaker (basically, a wireless doorbell), and in one box, an extra klaxon. The aim was to work out what was going on—what did the controls do?—and record your group’s understanding, or mental model, or even an algorithm of how the system worked in some form that could explain it to a new user who hadn’t been able to experiment with the device.

As people realised that the boxes ‘interacted’ with each other, by setting off sounds in response to particular button-presses, the groups’ explanations became more complex.

Each group used slightly different methods to investigate and illustrate the model, with unexpected behaviour or coincidences (one group’s box setting off the doorbell in another, but coinciding with a button being pressed or a volume control being turned) leading to some rapidly escalating complex algorithms.

We are now creating an even more complex world of black boxes, networked black boxes with their own algorithms, real and assumed, and those that depend on algorithms out of our hands, remote, changeable, strategic, life-changing which we may not have any easy way of investigating. And which model us, the public, in particular ways.

(“Algorithm is going from black box code to black box language. Everything is being explained away as “algorithm”. No surprise really.” Scott Smith, 6 July 2014—https://twitter.com/changeist/status/48579323239650918)

As James Bridle puts it, “comprehension is impossible without visibility”:

“the intangibility of contemporary networks conceals the true extent of their operation… This invisibility extends through physical, virtual, and legal spaces.”

Bridle is talking about a policing context, but invisibility, or rather lack of transparency, is of course also a hallmark of crime and corruption, often intentionally complex systems. Dieter Zinnbauer’s concept of ambient accountability is very relevant here: systems can only be accountable if people can understand them, whether that’s windows in building-site hoardings or politicians’ expenses.

Or as Louise Downe has said:

“We can only trust something if we think we know how it works… When we don’t know how a thing works we make it up.”

What new superstitions are going to arise from smart homes, smart meters, smart cities? What will people make up? Are my fridge and Fitbit collaborating with Tesco and BUPA to increase my health insurance premiums? What assumptions are the systems in my daily life going to be making about me? How will I know? What are the urban legends going to be? How will this understanding affect people’s lives? How can we make use of what the IoT enables to help us understand things, rather than making things less understandable?

An opportunity

The opportunity exists, then, for more work which uses a constructionist approach to enable us–the public–to investigate and understand the complex hidden systems in the world around us, in the process potentially changing our mental models, behaviour and practice. Tools based around IoT technology, developed and applied practically through a process of co-creation with the public, could enable this particularly well. In general, co-creation offers lots of opportunities for designing behaviour change support systems that actually respond to the real contexts of everyday life. But the IoT, in particular, can enable technological participation in this.

We would have to start with particular domains where public understanding of a complex, invisible system in everyday life potentially has effects on behaviour or social practices, and where changing that understanding would improve quality of life and/or provide social or environmental benefit.

Introducing ‘knopen’

I want to propose some examples of projects (or rather areas of practical research) that could be done in this vein, but before that–because I can–I am going to coin a new word for this. Knopen, a fairly obvious portmanteau of know and open, can be a verb (to knopen something) or an adjective (e.g. a knopen tool). Let’s say ‘to knopen’ conjugates like ‘to open’. We knopen, we knopened, we are knopening. Maybe it will usually be more useful as a transitive verb: We knopened the office heating system. The app helped us knopen the local council’s consultation process. Help me knopen the sewage system. Maybe it’s useful as a gerund: knopening as a concept in itself. Knopening the intricacies of the railway ticketing system has saved our family lots of money.

Tools for understanding

What does knopen mean, though? I’m envisaging it being the kind of word that’s used as description of what a tool does. We have tools for opening things–prying, prising, unscrewing, jimmying, breaking, and so on. We also have tools that help us know more about things, and potentially understand them–a magnifying glass, a compass, Wikipedia–but just as with any tool, they are better matched to some jobs than to others.

If I just use a screwdriver to unscrew or pry open the casing on my smart energy meter, and look at the circuitboard with a magnifying glass, unless I already have lots of experience, I don’t know much more about how it works, or what data it sends (and receives), and why, or what the consequences are of that. I don’t necessarily have a better understanding of the system, or the assumptions and models inscribed in it. I have opened the smart meter, but I haven’t knopened it. To knopen it would need a different kind of tool. In this case, it might be a tool that interrogates the meter, and translates the data, and the contexts of how it’s used and why, into a form I understand. That doesn’t necessarily just mean a visual display.

This, then, would be knopening: opening a system or part of a system (metaphorically or physically) with tools which enable you to know and understand more about how it works, what it does, or the wider context of its use and existence: why things are as they are. Knopening could include ‘knopening thyself’–understanding and reflecting on why and how you make decisions.

Knopening isn’t as involved as grokking. To grok something is at a much deeper level. Nevertheless, knopening could be transformative. Going back to the earlier discussion, knopening is basically a label for a process by which we can investigate and understand the complex hidden systems in the world around us, which could certainly change our mental models, behaviour and practice. Knopening is about understanding why.

Maybe knopen is a daft conceit, a ‘fetch’ that isn’t going to happen. But it’s worth a try. And I see that it also means ‘to button’ or ‘to knot’ in Dutch, but that’s not too awful. As my wife put it, “that’s quite sweet.” Probably ontknopen, unbuttoning or untying, would be closer in meaning to what I mean. Urban Dictionary tells us that knopen can also mean “the act of knocking on and opening a closed door simultaneously”, which is not inappropriate, I think.

Some areas of research for knopen

These are all about people making and using tools to understand–to knopen–the systems around them, in particular the whys behind how things work. They all have the potential to integrate the quantitative data from networked objects and sensors with qualitative insights from people themselves, in co-created useful and meaningful ways.

DIY for the home of the future

In the UK, “at least 60% of the houses we’ll be living in by 2050 have already been built” (and that quote’s from 2010). That means that whatever IoT technologies come to our homes, they will largely be retrofitted. The ‘smart home’ in practice is going to be piecemeal for most people, the Discman-to-cassette-adaptor-to-car-radio rather than a glossy integrated vision.

(Photo by Toyohara, used under a Creative Commons licence)

That’s something to bear in mind in itself, but even with this piecemeal nature, there’s still going to be plenty of invisibility–quite apart from whatever it is our fridges are going to be making decisions about, what will DIY look like?

What are people going to be able to choose to fit themselves? What systems will people be able to connect together? What’s the equivalent of a buried cable detector for data flows? What will Saturday afternoons be like with the IoT? Is it an electrician we need or a ‘data plumber’? What will happen when parts need to be replaced? When smart grids come along, for example, what is interaction with them going to look like? Can DIY work in that context? What happens if microgeneration becomes popular?

Could we use this DIY context strategically—as a way of engaging people in behaviour change, through active participation in experimenting and changing their own homes and everyday practices, using IoT technologies? How do we domesticate the IoT?

(Tom Coates’ House of Coates, and the Haunted Coates House)

Something in this space could be the core of the knopen concept: tools that enable us to understand and investigate the invisible systems around us, and the links between them, at home (or at work). Really basically, we could think of it as in-context system diagrams on everything – not just static, but explorable explanations in Bret Victor’s terminology, maybe even some kind of data traces. And those explanations don’t have to be physical diagrams—they can be ambient, responsive, exploring both the backstories and possible future states of systems.

Networked devices and sensors, inputs and outputs, everything the IoT provides, could show us explicitly how systems work both in and beyond our immediate home context—including our own actions, past, present and future (hence enabling us to change our behaviour), and those of other people. We would learn what a system assumes/knows about us, and how it makes decisions that affect us and others; how do we fit into these systems that pervade our homes?

Seams, streams and new metaphors

The idea of seamful design  – in contrast to the seamlessness which so often seems to be goal of advances in human-computer interaction–is useful here. We are used to systems being promoted as invisible, seamless, frictionless as if this is necessarily always a good thing, from contactless payment to Facebook Connect. There’s no doubt that seamlessness can be convenient, but there’s a cost.

Matthew Chalmers, who has developed the ideas that Mark Weiser (father of calm technology, ubiquitous computing, etc) had around seamlessness and seamfulness, suggests that: “Seamfully integrated tools would maintain the unique characteristics of each tool, through transformations that retained their individual characteristics.”

Going slightly further than that, perhaps, by enabling people to experience the joins between systems, and the discontinuities, the texture of technologies—even making the seams not just ‘beautiful’ but tangible– we could help them understand better what’s going on, and interact with systems in a different way. As Karin Andersson says:

“The seams that are the most important are the ones that can improve a system’s functionality and when they are understood and figured out how they can become a resource for interaction by the user. If designers know how certain seams affect interactions, they can then incorporate them into an application and direct their effects into useful features of the system. This way, seamful design allows users to use seams, accommodate them and even exploit them to their own advantage”

Knopen is perhaps an attempt to enable people to make tools to make seams visible, or tangible, for themselves, where currently they are not. It is trying to turn seamlessness into seamfulness, then into understanding and empowerment, through enabling, facilitating, investigation of those systems: brass rubbing for the systems of the home, perhaps.

(Detail of Juliana, wife of Thomas de Cruwe, 1411. CC licensed by Amanda Slater)

Seams are important to mental models. In the 1990s, Neville Moray—drawing on a approach taken by cybernetician (and ‘requisite variety’ originator) Ross Ashby—explored how one way of modelling what a mental model really is, is a lattice-like network of nodes that are super- or subordinate to other nodes (not necessarily in the sense of power relations, but rather in terms of parts or categories). By this interpretation, different mental models of the same situation or system come down to things like:

• two people’s models containing different sets of nodes
• or, more specifically, conflating particular nodes or introducing distinctions between nodes where others treat them as the same thing
• two people’s models connecting the same nodes in different ways

Seams are, perhaps, the links or gaps between nodes or groups of nodes. Intentional seamlessness is an attempt to hide these links or gaps by actually conflating particular nodes or groups of nodes from the user’s perspective. Seamlessness is saying, “This is one system, and these nodes are the same”. In doing this, it inherently removes the ability to see or inspect or question or understand these relations.

We are—and will shortly be even more so—surrounded by systems, in our homes and elsewhere, that are collecting, sending, receiving and storing data all the time, about us, our actions and our environments. And yet we are generally not privy to what’s going on, what decisions are being made, where the data come from and where they go.

It might not seem a major issue at present to most people—even in the light of Snowden’s revelations and all that’s come since  – but once, for example, smart meters are dynamically adjusting pricing for electricity and gas on a large scale, a greater number of people are going to want to understand where those prices are coming from, and how these systems work. Compare the—often amusing—reactions when people explore what Google Ads or Facebook thinks it knows about them. Many people seem to enjoy this kind of exploration—all the more reason for a constructionist approach.

We need a narrative context for the streams in our daily lives: what is the story of the sensors? What is the meaning of what’s going on? Even a Dyson-style ‘transparent container’ metaphor for data, showing us what’s being collected, or colour-coded statuses on devices, would give us some more understanding. This is something like ambient accountability in Dieter Zinnbauer’s terminology, but involving us, the public, the ‘end user’, much more explicitly.

Metaphors could play an important role here, or perhaps new metaphors. Representing a new, unfamiliar system in terms of more familiar ones is maybe obvious, and has its limitations (except in Borges, the map is never the territory), but as with our discussion of new superstitions earlier, it’s almost inevitable that new metaphors will arise for parts of these invisible systems in the home and elsewhere, as part of mental models and in people’s explanations to others of how they work. Metaphors are very commonly used in design for behaviour change, from gardens to sarcastic overlords.

(What does energy look like? From the V&A Digital Design Weekend 2014. Photo by V&A Digital.)

We can learn quite a lot from exploring people’s understanding and mental imagery around invisible systems. A project Flora Bowden and I have been doing over the last couple of years involves asking people to draw ‘what energy looks like’; we’ve also tried it with concepts such as ‘clean’ and ‘dirty’, and there are large scale projects such as Can You Draw the Internet? There are insights for the design of new kinds of interfaces, of course, but also something more fundamental about how people perceive and relate to intangible things. Almost by definition, people use metaphors (or metonyms) of one kind or another to visualise abstract or unseen concepts—what would they look like for invisible systems in our homes?

Could we use new metaphors strategically, to help people understand new systems? What should they be? How do they link to behaviour change in this context? Bringing it back to DIY, what metaphors are going to be used to get people interested in fitting these systems to their homes in the first place?

You’re not alone

Moving away from the home, this next group of ideas would use IoT technologies to enable ‘peer support’ for decision making: connecting people to others facing similar situations, and enabling people to understand each other’s thinking and what worked for them (or not). The aim of this knopening of situations would be empathy, but also practical advice and support.

Understanding–and reflecting on–how you think, and how other people approach the same kinds of situation, can help change mental models, support behaviour change in the context of everyday practices (learning from others what worked for them, and why), and tackle attribution errors, as mentioned earlier, by bridging the gaps between our own thinking and our assumptions about others’ behaviour.

The contexts and domains where this could be useful range from physical and mental health, to route planning, to home improvement, to financial decisions, to any situation where a combination of networked objects and/or sensors, combined with qualitative insights from people who are part of the system, could help.

Some specific ways of implementing You’re not alone might include:

(Windows XP Event Viewer—image from https://en.wikipedia.org/wiki/Event_Viewer)

The Shared ‘Why?’

• This would be a tool for annotating situations with ‘what your thinking is’ as you do things (that may be logged automatically anyway)—a kind of ‘Why?’ column in the event logs of everyday life.
• The question might be prompted automatically by certain situations being recognised (through sensor data) or could also be something you choose to record. These ‘Whys’ would then be available to your future self, and others (as you choose) when similar situations arise.
• My thinking here is that (as Tricia Wang points out), the vast quantities of Big Data generated and logged by devices, sensors and homes and infrastructure, are largely devoid of human contexts–the ‘Why?’, the ‘thick’ data–that would give them meaning. There’s a great opportunity for introducing a system which makes this easier to capture. It could be an academic or design practitioner research tool, but my main priority is that it be actually useful to the people using it.

(Annotating household objects to understand thermal comfort. From a study by Sara Renström and Ulrike Rahe at Chalmers University of Technology, Gothenburg.)

• Asking people to annotate real-life situations with simple paper labels or arrows has worked well as a research method for eliciting people’s stories, meanings and thought processes around interaction with particular devices, and the sequences they go through. Similarly, even simple laddering or 5 Whys-type methods can be used to uncover people’s heuristics around everyday activities. But how could these kinds of methods be made more useful for those doing the annotation or answering the questions–and for others too?
• While there exist research methods such as experience sampling and sentiment mapping, with plenty of location- or other trigger-based mobile apps, these largely focus on mood and feelings, rather than the potentially richer question of ‘Why?’. Yet Facebook and Twitter have shown us that short-form status updates, with actual content (mostly!), are something people enjoy producing and sharing with others. When I worked on the CarbonCulture at DECC project, one of the most successful features (in terms of engagement) of the OK Commuter travel logging app was a question prompting users to describe that morning’s commute with a single word, which often turned out to be witty, insightful and revealing of intra-office dynamics around topics such as provision of facilities for cyclists.
• Clearly there are lots of questions here about validity and privacy. Would people only log ‘Whys’ that they wanted others to know? Who would have access to my ‘Whys’? Would they ‘work’ better in terms of empathy or behaviour change if linked to real names or avatars than anonymously? We would have to find ways of addressing and accommodating these issues.

There are some parallels with explicitly social projects such as the RSA’s Social Mirror Community Prescriptions, but also with work in naturalistic decision making. For example, there are projects exploring how Gary Klein’s recognition-primed decision model of how experts make decisions (based on a mixture of situational pattern recognition and rapid mental simulation) can be ‘taught’ to non-experts. A constructionist approach seems very appropriate here.

Helpful ghosts: ambient peer support

• What this would involve is essentially being able to create helpful ‘ghosts’ for other people, which would appear when certain situations or circumstances, or conjunctions of conditions, were detected, through IoT capabilities. You could record advice, explanations, warnings, suggestions, motivational messages, how-to guides, photos, videos, audio, text, sets of rules, anything you like, which would be triggered by the system detecting someone encountering the particular conditions you specified. That could be location-based, but it could also be any other condition. It’s almost like a nice version of leaving a note for your successor, or anyone who faces a similar situation.

(The Stone Tape (BBC, 1972). Image from http://anamericanviewofbritishsciencefiction.com/2013/12/16/the-stone-tape-1972/)

• The ghosts wouldn’t be scary, or at least I hope not. Maybe ghost is the wrong word. The idea obviously has parallels with Marley’s Ghost in Dickens’ A Christmas Carol–and the feedforward / scenario planning / design futures of the Ghost of Christmas Yet-To-Come–but what directly inspired me was Nigel Kneale’s The Stone Tape (probably in turn inspired by archaeologist and parapsychologist Tom Lethbridge’s work), in which ghosts are explained as a form of recording somehow left behind in the fabric of buildings or locations where strong emotions have been felt. Kevin Slavin’s talk at dConstruct 2011, and Tom Armitage’s ghostcar, are also inspirations here. And I have recently also come across Joe Reinsel’s work on Sound Cairns, which has some very clever elements to it.
• Maybe it’s better to think of this like If This Then That (see below), but allowing you to create rules that trigger events for other people instead of just for you.
• How would it be different to Clippy? (thanks to Justin Pickard for making this connection). We should aim to learn from the late Clifford Nass’s work at Stanford on why Clippy was so disliked, and how to make him more loveable. It would also be important that the helpful ghosts did not just become a form of ‘pop-up window for real life’. Advertisers should not be able to get hold of it. It should always be opt-in, and the emphasis should be on participation (creating your own ghosts in response) and understanding. It is meant to be at least a dialogue, a collaborative approach to learning more about, and understanding–knopening–a situation, and then passing on that understanding to others.

A Collective If This Then That

• This is probably already possible to achieve with clever use of If This Then That together with some other linked services, but the basic idea would be a system where multiple people’s inputs–which could be a combination of quantitative sensor data and qualitative comments or expressions of sentiment or opinion–together can trigger particular outputs. These might also be collective, or might apply only in a single location or context.
• There are obvious top-down examples around things like adaptive traffic management, but it would more interesting to see what ‘recipes’ emerge from people’s–and communities’–own needs. There could also be multiple outputs to different systems. They could work within a family or household or on a much bigger scale–connecting families who are often apart, for example.
• The knopen element comes with being able to understand–right from the start–how to make action happen, and collaboratively create recipes which address a community’s needs, for example. The system might be complex but would be not only visible, but fully accessible since the participants would be involved in creating and iterating it.
• It could involve ‘voting’ somehow, but it would also be interesting to see effects emerge from unconscious action or a combination of physical effects read by sensors and social or psychological effects from people themselves.
• I’m inspired here particularly by Brian Boyer and Dan Hill’s Brickstarter–in which the collective desire/need/interest of the crowdfunding model is applied to urban infrastructure–but also by the academic research (and workshop at Interaction 12) I did exploring ‘if…then’-type rules of thumb and heuristics that people use for themselves, often implicitly, around things like heating systems, and how different people’s heuristics differ.
• There’s some really interesting academic research going on at the moment by teams at Brown and Carnegie Mellon–e.g. see this paper by Blase Ur et al from CHI 2014–on using IFTTT-like ‘practical action-trigger programming’ in smart homes as a way to enable a more easily programmable world, and it would be great to explore the potential of this approach for improving understanding and engagement with the systems around us. As Michael Littman puts it:

“We live in a world now that’s populated by machines that are supposed to make our lives easier, but we can’t talk to them. Everybody out there should be able to tell their machines what to do.” (Professor Michael Littman, Brown University)

Storytelling for systems: Five whys for public life

‘Five whys’ is a method for what’s called root cause analysis, used in fields as diverse as quality management and healthcare process reform. It’s similar to the interview technique of laddering, which has seen some application in user experience design. The basic principle is that there is never only one ‘correct’ reason ‘Why?’ something happens: there are always multiple levels of abstraction, multiple levels of explanation, multiple contexts–and each explanation may be completely valid within the particular context of analysis. In ‘solving’ the problem, the repeated asking ‘Why?’ enables reframing the problem at further levels up (or down) this abstraction hierarchy, as well as giving us the ‘backstory’ of the current state (which is often considered to be a problem, hence the analysis).

It’s a practical instantiation, in a way, of Eliel and Eero Saarinen’s tenet of trying to design for the “next largest context–a chair in a room, a room in a house, a house in an environment, environment in a city plan”. In some previous work, I tried exploring (not particularly clearly), the notion that this kind of approach, in reframing the problem at multiple levels, could essentially provide us with multiple suggested ‘solutions’ by inverting problem statements at each level of abstraction.

So what do we do with this? How can IoT technology be useful? Imagine being able to ‘ask’ the physical and societal infrastructure around you–the street lamps, the building site, the park fountain, but also the local council, the voting booth, the tax office, your children’s primary school’s board of governors, the bus timetable, Starbucks, the numberplate recognition camera, the drain cover, the air quality sensors in the park, the National Rail Conditions of Carriage–Why?

Why are they set up the way they are? Who came up with the idea? (not for blame, but for empathy). What’s the story behind the systems? What influenced how they’re operating, how the decisions were made, how they came to be?

What data do they collect, and what do they do with the data? What’s the revision history for this government policy? What were the reasons given for that cycle path being routed that way? What’s the history of planning applications for buildings on this site? What were the debates that led to the current situation?

And for each of those, the answers would be explained at multiple levels–maybe not exactly five ‘whys’, but more than one simplistic reason, devoid of context.

This isn’t just Freedom of Information–although it intersects with that. It’s more about understanding the decision process, the constraints and priorities others have had to contend with along the way. Kind of autobiographies for systems (including public objects, perhaps, but also institutions–maybe even Dan Hill’s ‘Dark Matter’). Or a cross between blue plaques (or rather, Open Plaques), ‘For the want of a nail’, WhatDoTheyKnow, City-Insights, FixMyStreet, Dieter Zinnbauer’s Ambient Accountability, TheyWorkForYou, Historypin, Wikipedia’s revision history, Mayo Nissen’s ‘Unseen Sensors’ and a sort of transparent reverse IFTTT where you can see what led to what.

From a technology point of view, you could do it very simply with smartphones and QR codes or NFC tags stuck on bits of street furniture (for example), but it would be possible to do much more when systems have a networked capability and presence–when data are being collected or received, or transmitted, or when one piece of infrastructure is informing another.

Of course, it could be seen as quite antagonistic to authority: this kind of transparent storytelling could reveal how inept some institutions–and potentially some individuals–are at making decisions, although it could also help generate empathy for people facing tough decisions, in the sense of revealing the trade-offs they have to make, and so increase public engagement with these systems by showing both their complexity (potentially) and their human side. Peerveillance, sousveillance, equiveillance, yes–but preferably framed as storytelling.

The challenge would be finding positive stories to lead with (thanks to Duncan Wilson for this point). Suggestions are very welcome.

Conclusion: what next?

This has been a long, rambling and poorly focused article. It tangles together a lot of ideas that have been on my mind, and others’ minds, for a while, and I’m not sure the tangle itself is very legible. But I welcome your comments.

My basic thesis is that IoT technology can be a tool for behaviour change for social and environmental benefit, through involving people in making systems which address problems that are meaningful for them, and which improve understanding of the wider systems they’re engaging with.

I think we can do this, but, as always, doing something is worth more than talking about it. As an academic, I ought to be in a position to find funding and partners to do something interesting here. So I am going to try: if you’re interested, please do get in touch.

Back in the darkest days of my PhD, I started blogging extracts from the thesis as it was being written, particularly the literature review. It helped keep me motivated when I was at a very low point, and seemed to be of interest to readers who were unlikely to read the whole 300-page PDF or indeed the publications. Possibly because of the amount of useful terms in the text making them very Google-able, these remain extremely popular posts on this blog. So I thought I would continue, not quite where I left off, but with a few extracts that might actually be of practical use to people working on design, new ideas, and understanding people’s behaviour.

The first article (to be split over two parts) is about toolkits (and similar things, starting with an exploration of idea generation methods), prompted by much recent interest in the subject via projects such as Lucy Kimbell, Guy Julier, Jocelyn Bailey and Leah Armstrong’s Mapping Social Design Research & Practice and Nesta’s Development Impact & You toolkit, and some of our discussions at the Helen Hamlyn Centre for the Creative Citizens project about different formats for summarising information effectively. (On this last point, I should mention the Sustainable Cultures Engagement Toolkit developed in 2012-13 by my colleagues Catherine Greene and Lottie Crumbleholme, with Johnson Controls, which is now available online (12.5MB PDF).)

The article below is not intended to be a comprehensive review of the field, but was focused specifically on aspects which I felt were relevant for a ‘design for behaviour change’ toolkit, which became Design with Intent. I should also note that since the below was written, mostly in 2010-11, a number of very useful articles have collected together toolkits, card decks and similar things. I recommend: Venessa Miemis’s 21 Card Decks, Hanna Zoon’s Depository of Design Toolboxes, Joanna Choukeir’s Design Methods Resources, Stephen Anderson’s answer on this Quora thread, Ola Möller’s 40 Decks of Method Cards for Creativity, and Public Policy Lab’s list of Toolkits for Public Service Design. I’m sure there are others.

Problem-solving and problem-framing



“Engineers are not the only professional designers. Everyone designs who devises courses of action aimed at changing existing situations into preferred ones. The intellectual activity that produces material artefacts is no different fundamentally from the one that prescribes remedies for a sick patient or the one that devises a new sales plan for a company or a social welfare policy for a state.”
Herbert A. Simon, The Sciences of the Artificial, 1969 (p.129 of 1981 MIT press 2nd edition)

Designers solve problems, but they are by no means alone in that. As Jack Schulze of BERG comments, ”so do dentists” (Kicker Studio, 2009). Design is not, then, identical to problem-solving, but it certainly involves addressing issues that are seen (by someone) as problems and developing new or changed products, services or environments (seen by someone as solutions) in response. This review is not going to fall into the ‘What is design?’ rabbit-hole, since that has been more than adequately explored by other authors, but it is important to understand how design processes can work, in order to identify the most useful characteristics for the proposed toolkit. [which became Design with Intent]

The view of design as being entirely about ‘problem-solving’–which, at its most mechanistic, is ”basically a form of means-ends analysis that aims at discovering a process description of the path that leads to a desired goal”–as espoused by Simon (1969/1981, p.223, and to some extent in the above quote), has become unfashionable in design research, and not just because of the implied lack of creativity in the process.[1] In particular, the reaction against the ‘problem-solving’ view follows Schön’s (1983) concept of The Reflective Practitioner, whose “inquiry is not limited to a deliberation about means which depends on a prior agreement about ends. He does not keep means and ends separate, but defines them interactively as he frames a problematic situation” (p.68).

Thus, design is seen as being as much about problem-framing as problem-solving, an exploration and co-evolution of both the problem and solution ‘spaces’ (Maher et al, 1996), questioning and refining the problem, changing focus and the boundaries of the problem as part of the process of generating solutions. [2]

  

Dorst and Cross (2001) give the example of a workshop participant asked to redesign in-train litter bins for Dutch Railways (NS) who asks whether simply making a hole in the floor for litter to be dropped through (or combining it with the toilet flush which works in a similar way) is valid within the scope of the brief. They use Cross’s (1997) idea of the formation of ‘bridges’ between problem and solution as the ‘creative leap’ which pairs one representation of the problem with a solution, suggesting that “creative design involves a period of exploration in which problem and solution spaces are evolving and are unstable until (temporarily) fixed by an emergent bridge which identifies a problem-solution pairing. A creative event occurs as the moment of insight at which a problem-solution pair is framed” (Dorst and Cross, 2001).

Pragmatically–and dependent on the semantic preferences of those involved–it is arguable that problem-framing is part of problem-solving. The process of interrogating a brief, stretching and testing the boundaries of what is being asked and what will count as a solution, is an integral part of addressing the problem, rather than being a distinct activity. Paul Rand said that “[i]deas may also grow out of the problem itself, which in turn becomes part of the solution” (Heller et al, 1998), and this is a proposition also found within TRIZ (see below), ‘systems thinking’ in general, and specifically within Edward de Bono’s work.

Christopher Alexander (1964, p.17), using the (re)design of a kettle as an example, notes the fluidity of the boundaries of design problems:


If I say that the kettle is the wrong way to heat domestic drinking water anyway, I can quickly be involved in the redesign of the entire house, and thereby push the context back to those things outside the house which influence the house’s form. Alternatively I may claim that it is not the kettle which needs to be redesigned, but the method of heating kettles. In this case the kettle becomes part of the context, while the stove perhaps is form.

Many more human-related design problems (including those relating to behaviour change) may be characterised as `wicked problems’ (Buchanan, 1992; Rittel and Webber, 1973), perhaps particularly exhibiting the characteristic expressed by Conklin (2009) in his re-statement of some of Rittel and Webber’s principles: “You don’t understand the problem until you have developed a solution. Every solution that is offered exposes new aspects of the problem, requiring further adjustments to the potential solutions. There is no definitive statement of `the problem’: these problems are ill-structured and feature an evolving set of interlocking issues and constraints.”

Generating ideas

Both within and without `design’, a variety of `creative thinking’ techniques are commonly used to generate novel ideas as part of problem-solving processes, often in group workshops, but also individually. While this review cannot hope to do more than scratch the surface, some which potentially offer relevant insights to the subject at hand will be discussed.

The field comprises a mixture of academic and popular literature, and many techniques have become generally familiar, and evolved through use, without their `authorship’ remaining clear. As Gray et al (2010, p.xvi) put it, “[t]he practices live in a mostly oral culture, passed along from person to person by word of mouth. For example, a consultant uses an approach with a client, and the client begins to employ that approach internally. Over time… it evolves into something quite different, and… the source of the original idea or approach may be lost”.

One of the most comprehensive online resources on the subject, Jack Martin Leith’s Compendium of idea generation methods, is no longer available, but a version of the site (Leith, 2005) retained on the Internet Archive, contains over a hundred categorised methods. Most of the methods considered relevant to this thesis are what Leith calls `springboards’ (drawing on the use of the term in Synectics)–those which involve the use of an external stimulus to trigger new thinking.

Lateral thinking

Over more than forty years, Edward de Bono has produced a series of popular books and training courses on creative thinking and innovation methods. The full range of his work cannot be covered here, but some concepts relevant to design and idea generation can be extracted. `Lateral thinking’, which de Bono (1993, p.52) explains via the maxim “You cannot dig a hole in a different place by digging the same hole deeper”, contrasting it with linear `vertical thinking’, comprises four principles (de Bono, 1971, p.68): ”1. Recognition of dominant polarizing ideas; 2. The search for different ways of looking at things; 3. A relaxation of the rigid control of vertical thinking; 4. The use of chance.”

It is noteworthy that a number of the lateral thinking examples de Bono gives across his books are specifically concerned with influencing people’s behaviour and addressing a wide range of societal issues. For example, influencing behaviour for commercial benefit is embodied in the the anecdote (de Bono, 1993, p.6) about an Australian payphone operator which needed to offer fixed-cost local calls to remain competitive with rival operators, but wanted callers to spend less time on those calls so that the telephones were made available for other customers; so the story goes, the operator decided to increase the weight of the telephone handsets so that longer calls became tiring (subconsciously or otherwise), limiting the length of calls made.

Corporate behaviour change for environmental benefit is also included, for example with the idea (e.g. de Bono, 1976, p.146) that a factory taking in river water and discharging (dirty) water back into the river “should be downstream of itself”, i.e. planners should force the water intake pipe to be downstream of the water outlet pipe, thus making it in the factory’s best interests not to discharge polluted water.

Among the methods de Bono suggests for lateral thinking, including particularly those suited for finding “different ways of looking at things” are: simple focus, a deliberate effort to pick out a new focus point for a problem (de Bono, 1993, p.92); the creative challenge, a forced questioning of the current way things are done; and the concept fan, a method of repeatedly `pulling back’, abstracting the problem implied by a search for alternative solutions, such that the need for a ladder is restated as the need to be raised above the ground, in turn restated as the need to reduce the distance between the person and the ceiling, and so on, with each abstraction suggesting a greater range of possible solutions (de Bono, 1993, p.129).

Straker and Rawlinson (2002, p.4) call a similar approach `chunking up’, asking ”What is the real problem here?” at each level; it also recalls aspects of Alexander’s (1964) functional decomposition and the abstraction hierarchies used in cognitive ergonomics and ecological interface design (e.g. Rasmussen, 1985). [see also the kind of ‘abstraction’ method applied in our later work on behavioural heuristics]

Provocation

Many of de Bono’s techniques centre on the idea of provocation, in particular, finding ways of intentionally provoking new ideas through methods ranging from the simple random input (juxtaposing two seemingly unconnected concepts [3] to trigger new ideas as a connection emerges–this is an expression of `the use of chance’ as mentioned above (de Bono, 1993))–to more structured methods such as using reversal, exaggeration and distortion of ideas as part of a stepping-stone process to examine and alter the given problem. The concept of PO (de Bono, 1972) was introduced as a marker to signify that a deliberately provocative (perhaps superficially absurd) suggestion follows, not necessarily to be adopted as a valid solution in itself, but as a trigger to help think of alternative solutions. For example, “PO, cars should have square wheels” leads to thinking about the possibilities of adaptive suspension systems (de Bono, 1993).

This kind of prompt potentially has application in helping designers shift problem frames (see above) implied by a brief: ”[e]ven if an idea is wrong in itself it can serve as a starting point for a new line of thought or as a stepping-stone to get from one idea to a new one” (de Bono, 1976, p.146). In some circumstances, it is easy to imagine that it could suggest behaviour change (rather than solely technology change) as an approach in the first place, by introducing the idea that people should change rather than a product changing (or vice versa).

Six Thinking Hats

One of the most structured creativity techniques applicable to idea generation described by de Bono is Six Thinking Hats (de Bono, 1990 [4]). The idea here is to put members of a group–as part of a meeting or workshop–into a role-playing context, where the coloured hats (put on literally or figuratively) each enable the group’s attention to be directed to different points of view and aspects of the problems and ideas under discussion, and to switch gears between ways of thinking about a problem (`parallel thinking’). The role-playing context also allows participants to say things they might otherwise not feel comfortable expressing—“[w]earing the clown costume gives you full permission to play the clown” (de Bono, 1990, p.29) [5]—including asking others to consider changing their point of view, since “[y]ou can ask someone to `take off the black hat for a moment’ more easily than you can ask that person to stop being so negative” (p.33). The table below summarises very briefly the characteristics of each hat.

The details of the different perspectives triggered by the hats are general enough to apply to a wide range of meetings, workshops, idea generation and decision-making situations. Independently, though, the concept of introducing a deliberate `prop’ to encourage taking different perspectives on a problem could be valuable for idea generation, particularly where there are issues which ought to be debated but which might not otherwise be raised. For example, an `ethical’ hat might be of value when considering behaviour change interventions. It might also be feasible for hats to represent the points of view of different stakeholders—a particular hat being put on to represent the `voice of the user’, a different one to represent the `voice of the shareholders’ and so on. For Baron (1994, p.72), an additional advantage of deliberately taking multiple viewpoints on a problem is that “it is more likely to remind you of the critical information that you need to solve it”, i.e. that multiple views also help ensure that relevant information is not missed.

Perhaps one of the most useful implications of the concept for an idea generation process which seeks to generate a large quantity of ideas (see below) is that switching hats (of whatever form) could re-start the inspiration process when it starts to dry up, explicitly introducing alternative sets of ideas or viewpoints. The Design with Intent `lenses’ follow this approach.

SCAMPER and Rosenman and Gero’s processes

Moving more specifically towards product design, two verb-based idea generation techniques are particularly relevant. While arising from different contexts, they overlap in content.

SCAMPER (Eberle, 1971) was developed as a simplified form of some of Osborn’s (1953) brainstorming recommendations, intended originally for classroom use. It comprises seven verbs (see table below) describing operations which could be carried out on a product or concept (potentially including even people themselves) to generate new variants or improvements. [6]

Rosenman and Gero (1993) and Gero (2000) arrive at a partially similar list of processes (table below), but from the perspective of examining idea generation behaviour by designers and extracting descriptions of the processes (also presented as applicable in an artificial intelligence context), rather than offering them explicitly as inspirational triggers. Gero’s (2000) definition of analogy is somewhat similar to what I have identified with Design with Intent as transposition of design principles between disciplines.

The active provocations offered by Eberle’s approach are more immediately suited to triggering idea generation, but formal descriptions of principles as given by Rosenman and Gero have value in providing a reference of techniques which could be consulted as a reflective part of the idea generation process, in a similar way to Alexander et al’s patterns (see part 2 of this post). Hence, both of these possible approaches are worth considering as relevant directions for Design with Intent. Aside from the form of the processes, the content itself may have direct relevance to the behavioural context. If “people’s behaviours” rather than a product’s features are considered as the focus of each SCAMPER verb, what sorts of ideas might be suggested? Can you design a product which `substitutes’ an undesired behaviour with a desired one? One which combines behaviours to avoid an unwanted harm? One which adapts a behaviour which a person expresses in another context to the context for which you are designing?

[2014 note: Geoff Mulgan of Nesta has recently published a list of ‘Social Design Tools’ similar in form to SCAMPER and Rosenman & Gero’s processes, adapted to fit social enterprises and the public sector.]

Do you know a related problem? Analogies and metaphors

“We can scarcely imagine a problem absolutely new, unlike and unrelated to any formerly solved problem; but, if such a problem could exist, it would be insoluble. In fact, when solving a problem, we always profit from previously solved problems, using their result, or their method, or the experience we acquired solving them. And, of course, the problems from which we profit must be in some way related to our present problem. Hence the question: Do you know a related problem?”

George Pólya, How to Solve It, Princeton University Press, 1945 (p.98 of 2nd edition, 1971)

Pólya’s How to Solve It (1945) is a guidebook for addressing mathematical problems, best known for popularising the term heuristic in the sense of a `rule of thumb’ in problem-solving. The `Short Dictionary of Heuristic’, comprising the main part of the book, offers 67 entries on aspects of, and approaches to, solving problems. The use of questions—“Do you know…? Could you imagine…?” and so on—is reminiscent of some of the provocation techniques mentioned earlier.

A theme which recurs in a number of Pólya’s heuristic approaches relates to the use of analogies, including solving a “simpler analogous problem”, and finding related problems which have been solved in other contexts. As Baron (1994, p.73) puts it, “[h]euristic methods allow us to search our memories for possibilities and evidence that are already there”. [7]

While Pólya’s work deals explicitly with mathematical problem-solving rather than creative design, the use of analogies, similes and metaphors is widely recommended as a method in idea generation for design (as well as a design technique itself). Saffer (2005, p.6) highlights the role of metaphors in cross-domain, interdisciplinary mapping for designers—“[t]he way we understand new things is to conceive of them in terms of things we already know. Metaphors become natural models that allow us to take familiar, concrete objects and experiences and re-cast them onto unknown or abstract concepts or things, giving them structure and meaning.” [8]

Seelig (2009, p.129) recommends the use of similes and metaphors to trigger new perspectives on a problem, using an exercise where teams are asked to come up with multiple versions of a statement in the form, “[concept under discussion] IS LIKE [an unrelated concept, usually a concrete noun] BECAUSE [of some characteristic of the second concept] THEREFORE [implications for the first concept]”. For example, “Ideas are like babies because everyone thinks theirs is cute, therefore be objective when judging your own ideas.”

Saffer (2005, p.10) sees metaphor use in idea generation as being about juxtaposition: “this is probably the easiest and one of the most fruitful way for designers to embrace metaphor use. All metaphors are, in a sense, juxtapositions in that two different things are put together to form a construct that highlights (and hides) different characteristics of each. Finding any inherent metaphors in the problem space is therefore probably a useful activity.” This last point about helping to define and structure the problem space is echoed by Leclercq & Heylighen (2002, p.287), who suggest that drawing analogies “can bring forth valuable knowledge from a known situation… to the ill-defined design situation at hand”.

Learning from biomimetics

“[W]e often find quite different inner environments accomplishing identical or similar goals in identical or similar outer environments—airplanes and birds, dolphins and tunafish, weight-driven clocks and spring-driven clocks, electrical relays and transistors.”

Herbert A. Simon, The Sciences of the Artificial, 1969 (p.7 of 1981 MIT press 2nd edition)

One design approach where analogical transfer is commonly applied in idea generation and problem-solving is biomimetics or biomimicry—making use of biological systems as models and inspiration for technology. Combining biomimetics with TRIZ (see below) to produce BioTRIZ offers a structured way of generating possible biologically inspired solutions for problems (Vincent and Mann, 2002; Craig et al, 2008), but there are also other idea generation methods based on applying biomimetics, such as Volstad and Boks’ (2008) `Biomimicry Card Deck’, intended to help packaging designers generate ideas for novel packaging concepts drawing on biological principles.

It is conceivable, if a somewhat romantic vision, that the biomimetic approach to design—learning from a vast reservoir of solutions to problems, and finding ways to apply them in other contexts—could be seen as a model for how to develop `design for sustainable behaviour’ as a field, treating human history and culture as a reservoir of behavioural insight to adapt and transpose to a design context.

It does, however, seem reasonable to suggest that “idea creation by analogical transfer” (Stacey et al 2009, p.362; Tseng et al 2008) might be most effective where the examples used make it easy for designers to see how the principles can be applied elsewhere—in a similar way to biomimetics—enabling “the ability mentally to stand back from the specifics of the accumulated examples, and form more abstract conceptualizations pertinent to their domain of expertise” (Cross, 2004, p.432).

As part of Design with Intent, an emphasis on example implementations of principles–“previous instances of design elements in a variety of different situations” (Eckert & Stacey, 2000, p.527)–rather than simply descriptions of the principles themselves, should allow designers to explore the ideas and relate them to the problem at hand, even where the terminology is unfamiliar. Thus, if the guide is to help designers make use of metaphor and analogy, these need to be clearly illustrated through examples which are quickly understandable.

Divergent production and brainstorming

A key concept in idea generation is the notion of divergent production, which Guilford (1967, p.213) defines as “generation of information from given information, where the emphasis is upon variety and quantity of output from the same source; likely to involve transfer,” as opposed to convergent production which would involve reaching a single `right’ solution to a problem.

While the `output from the same source’ criterion might be interpreted in a number of ways, the approach of trying to generate as many different ideas as possible is familiar from the process of brainstorming. Osborn (1953)—a co-founder of advertising agency BBDO—introduced the process as “a formal and systematized approach to a fuller utilization of the creative imagination” (p. vii), offering a set of rules and recommendations for how to `ideate’ in group conferences or workshops which have been widely adopted (and mutated) since, to the extent that `brainstorming’ has become a generic term for many different kinds of idea generation, both in groups and individually.

A significant part of the appeal of Osborn’s work must be his optimism and confidence that everyone can be creative: the book (Applied Imagination) makes the “universality of imaginative talent” clear and exhorts everyone to develop his or her creativity via exercises, games and puzzles. The book is somewhat reminiscent of Dale Carnegie’s How to Win Friends and Influence People (see a discussion of its relevance to design for behaviour change) in its mixture of anecdotes, positive encouragement and rules to follow.

Those rules and recommendations will not be covered here in detail, but the “four basics” for “idea-producing conferences” in groups are:

1. “Judicial judgment is ruled out. Criticism of ideas must be withheld until later.
2. `Free-wheeling’ is welcomed. The wilder the idea, the better; it is easier to tame down than to think up.
3. Quantity is wanted. The greater the number of ideas, the more the likelihood of winners.
4. Combination and improvement are sought. In addition to contributing ideas of their own, participants should suggest how ideas of others can be turned into better ideas, or how two or more ideas can be joined into still another idea” (Osborn, 1953, p.300-1).

As Baron (1994, p.120) notes, much of Osborn’s approach centres on the argument that “a major impediment to creation is insufficient search for possibilities. If we are too self-critical during the phase of idea generation, it has been argued, we inhibit ourselves from thinking of our best ideas. We must overcome our inhibitions and ‘brainstorm’ before we criticize and select”.

In the design industry, the most high-profile proponent of the brainstorming approach has been IDEO, which has evolved and tuned Osborn’s recommendations into its own set of `rules for brainstorming’, prominently displayed in company meeting rooms.

It is difficult to assess formally how much use any idea generation method is, since most such methods are, in practice, used in contexts in which there can be no comparable control group. Few organisations are able to bring competing projects to fruition in parallel, and few of the ideas generated by any brainstorming process will ever be directly realised as a product or service, but as Sutton and Hargadon (1996) suggested in a major ethnographic study of IDEO’s brainstorming processes, the process provides the organisation with less quantifiable benefits, including providing skill variety for participants by exposing them to a diversity of ideas and approaches, and supporting the attitude of wisdom by providing a non-judgemental forum “for getting unstuck” through collaborative endeavour.

They suggest that attempts to assess effectiveness of idea generation in terms purely of quantity of ideas generated are too simplistic; nevertheless, IDEO’s rules of brainstorming are at least partly geared towards generating as many ideas as possible (including “Go for quantity (not quality): Set an outrageous goal and surpass it”)–drawing directly from Osborn’s recommendations. This implies that while not a direct proxy for effectiveness, quantity can be an important step on the way. Hence, comparison of the quantity of concepts generated using different methods can still be considered worth studying.

The academic literature on the `productivity’ of brainstorming suggests that Osborn’s focus on groups `outperforming’ individuals may have been erroneous (Furnham, 2000). Interaction effects within differently constituted groups can be responsible for their collectively producing fewer ideas as a result of brainstorming than the individuals would have produced on their own. Phenomena such as production blocking (Diehl & Stroebe, 1987), and social loafing (Robbins, 1995) may lead to less productive sessions. It is also worth noting that recommendations for successful brainstorming (e.g. Wilson, 2006) often include the idea of a ‘warm-up exercise’ using a problem not directly related to the one intended for the main exercise, suggesting that participants may need some time to become `fluent’ in their idea generation.

However, as Sutton and Hargadon imply, there are other benefits from group brainstorming that may be desirable for the situation at hand. Expertise may be transferred between participants with different specialisms (which may be particularly important in a design context where the designers are not necessarily subject matter experts on the domain they are addressing). Group activity may be a chance for other stakeholders’ perspectives to be heard (and feel that they have been heard). For example, in urban planning, a design charrette refers to a session where multiple stakeholders (including members of the public) are brought together to address an issue (e.g. Condon 2008), including brainstorming. The implications of these issues for the development of the idea generation guide are probably that such a guide needs, ideally, to be usable either individually or in a group situation, and, again ideally, needs to be flexible enough to allow different groups of stakeholders to make use of it on an `equal footing’ with each other, rather than being focused entirely on one group as the users.

Although Osborn recommended the use of questions to spur ideation as part of the brainstorming process (some of his example questions were developed into SCAMPER—see above), many brainstorming exercises, at least in the author’s experience, do not use any explicit stimulus or provocation material beyond the problem itself and whatever background information is available. In this sense, an idea generation guide or toolkit is already enabling a slightly different form of brainstorming, although whether it would be more likely to increase the productivity of a session or restrict the ideas generated to only those derived from the guide is something that would need to be investigated.

TRIZ

“We live in an `Era of Technical Revolution’. The main point is that this revolution lies not in the appearance of new machines—that has happened before. The method of developing new machines is changing. organised ways of thinking replace the old chaotic ones. Every step in the thinking process should be as accurate as the movements of a pilot flying an airplane.”

Genrich Altshuller, And Suddenly the Inventor Appeared (trans. Lev Shulyak), Technical Innovation Center, 1994, p.160

One of the most structured systems for idea generation and technological problem solving that is available to designers is TRIZ (teoriya resheniya izobretatelskikh zadatch: theory of inventive problem solving). Developed in the early post-war Soviet Union by Genrich Altshuller and colleagues—and publicised in the West mainly from the early 1990s onwards (e.g. Altshuller, 1994)—TRIZ comprises a family of tools which draw on a database of principles and relationships extracted through analysis of, initially, tens of thousands, and by now, “millions” of patents (Gadd, 2011, p.101). The idea is that “[s]omebody someplace has already solved this problem (or one very similar to it.) Creativity is now finding that solution and adapting it to this particular problem” (Barry et al, n.d.).

Jones (2003, p.140) provides a `Map of TRIZ’, grouping a variety of TRIZ tools according to their function within the innovation process. She distinguishes between problem analysis (or situation analysis) tools (such as working out what kinds of contradictions are occurring) and solution tools (such as the Contradiction Matrix itself—see below).

Following the `Prism of TRIZ’, the problem analysis tools are used to generalise the problem, abstracting it to a form to which TRIZ offers generic solutions—the 40 `Inventive Principles’, such as SEGMENTATION, PERIODIC ACTION, PHASE TRANSITION and THE OTHER WAY ROUND, which are `suggested’ by the contradiction matrix or table of `separation principles’.
In this section, only a few elements of TRIZ will be covered which seem most directly relevant to the behaviour change context. [9]

The Prism of TRIZ

One of the most fundamental ideas in TRIZ is what Gadd (2011) calls the `Prism of TRIZ’ (see diagram), although it goes by a number of other names (e.g. Straker and Rawlinson, 2002, call it `Getting over the invention wall’).

The diagram represents a process of translating a specific problem into a more abstract general problem for which general solutions are known, then re-translating that general solution into the context of your problem, resulting in a specific solution.

The specific problems may be disparate, but on some level they are instances of general, recurring problems which exist in the world, and which someone has solved. Straker and Rawlinson (2002, p.78) suggest that this is in fact “similar to how people normally approach many situations”, but the explicit step of abstracting a specific problem into a more general one is not necessarily a common way to think in everyday life. The first step is not simply Pólya’s “Do you know a related problem?” (see above) but something more like “Can you describe the problem in an abstracted form?”—essentially a process of modelling a situation.

Contradictions

TRIZ has many principles and themes running through the family of tools, but one which dominates is the idea of contradictions. [10]

Altshuller’s approach—which Craig (2008) suggests has much in common with Marxist dialectic—was to see all problems as arising from contradictions between desired states. In TRIZ these are classified as technical contradictions (where “[w]e think of a solution to improve something but something else gets worse”), for example making a structure stronger makes it heavier, and physical contradictions, where “[w]e want opposite solutions—for example, high and low” (Gadd, 2011, p.102-4), such as a blacksmith wanting a horseshoe to be hot enough for the metal to be worked, but cold enough to be able to hold and manipulate it (Straker and Rawlinson, 2002, p.82). Solving physical contradictions involves separating when and where each condition or solution is present—in time, space, scale or on particular conditions—and this is done via consulting a table of `separation principles’ which suggests particular relevant Inventive Principles.

Part of the TRIZ Contradiction Matrix

Each technical contradiction is described in terms of two of 39 abstract `technical parameters’, for example `strength’ (no. 14) and `weight of stationary object’ (no. 2)—as we make something stronger, it is becoming heavier, but we don’t want this—and then the Contradiction Matrix, a 39 × 39 matrix is consulted. This suggests, for each intersecting cell, up to four Inventive Principles that are relevant. For improving strength without worsening the weight of a stationary object, the matrix suggests COMPOSITE MATERIALS, COPYING, CHEAP SHORT-LIVING OBJECTS and SEGMENTATION. Each of these principles can then be considered in more detail (with examples) to see how it might be applied to the specific problem.

The process of abstracting the problem to understand the contradiction(s) present, and hence selecting the parameters, can start in a number of different ways. For example, Jones and Harrison (2000) mapped TRIZ technical parameters to the five axes from Fussler and James’ Eco-Compass (1996), a commonly used tool for mapping changes in environmental impact of new and existing products, to enable this to be used as a starting point for the process (as well as to uncover whether TRIZ could be usefully applied in this context).

Ideality

As Craig (2008, p.40) puts it, in Altshuller’s view “a trade-off was resolved not by optimizing between two conflicting features, but by changing or adapting the system in some way so that both features could improve. For instance, a device may be made stronger and lighter by applying the principle ‘composite materials’”.

In TRIZ, “[t]he Ideal describes the perfect state, a perfect result… Whatever problem we are tackling, if we begin by imagining the Ideal version of the thing we want… then we get quick understanding of the best possible outcomes” (Gadd, 2011, p.177). A word equation is used to explain the concept:

A solution tends towards ideality when the benefits achieved are greater than the `costs’ and `harms’ entailed in the solution; ultimately, the system disappears entirely, the benefits tending to infinity as the costs and harms tend to zero. This implies the functions being delivered without the system existing at all—there are parallels here with the idea of dematerialisation in product-service systems, where a product is replaced augmented by a service which provides the same benefits without needing the same physical form. Mann and Jones (2002) apply TRIZ tools to the example of portable generators in this context. More generally, “[i]nnovation following this law of ideality could contribute to sustainable development, through the delivery of the functions without the environmental impacts associated with current systems of production” (Jones and Harrison, 2000).

What can be usefully applied from TRIZ?

What useful insights from (or features of) TRIZ can be applied to the `design for behaviour change’ guide?

– The notion of a method—systematic but not formulaic, to use a phrase applied by Sato (2009) to `design thinking’ in general—which helps `prescribe’ a range of possible solutions drawing on knowledge and experience with analogous situations, is an appealing one.
– The specific–abstract–abstract–specific arc (the Prism of TRIZ) perhaps provides a more formal description of the kind of analogical transfer discussed in a number of other idea generation and problem solving processes.
– The `lookup table’ form of the contradiction matrix is interesting because it expressly suggests relevant Inventive Principles, building in a creative element, rather than stating unequivocally that there is a single right answer.
– Craig (2008, p.45) notes that the Inventive Principles, being derived from analysis of patents across a number of technology domains, necessarily “resemble elements of the individual strategies used by expert designers in various disciplines.” This parallels the opportunity for an idea generation guide—that of a tool which can help designers learn from practice in other disciplines. Referencing Schön’s concept of problem-framing (see above) and Bryan Lawson’s concept of `gambits’, Craig goes on to suggest that “[d]ialectical ‘contradiction-thinking’ can be seen as an explicit method for problem-framing, just as the Inventive Principles can be understood as a sophisticated set of ‘gambits’”.
– On the other hand, the `certainty’ that may be implied by the philosophy of TRIZ—that there are definitely solutions to all problems, and that those solutions do not need to involve any compromises—does not sit easily with the notion of wicked problems in design, which may make it an uncomfortable perspective to designers working on social problems.

The TRIZ Inventive Principles are all technological, mostly based on physical sciences, although in many cases they can be seen as descriptions of system properties, at different levels (sub-systems, system and super-systems) so some at least could potentially be applied to systems involving human behaviour. Gadd (2011) includes a number of examples of solutions (many via the use of cartoons) illustrating TRIZ principles, which could be seen as `design for social behaviour change’, including:

– a target painted on a urinal to “Give the messy devils something to aim at” (p.163)
– a bakery deliberately piping its `fresh bread’ aroma into the street to attract customers (p.183)
– the use of a deceptive `Beware of the Bull’ sign to scare away trespassers (p.204)
– “Separate on condition with music for older people which repels young people”—playing Frank Sinatra’s songs in a public square at night to discourage younger people from `hanging around’ (p.125)
– using scarcity to make misprinted football shirts appear valuable rather than wasting them (p.161)
– a police officer giving drunken brawlers chocolate bars to stop them fighting rather than hitting them with a truncheon (p.47)
– a group of mothers forming a group to use social pressure to deal with street violence (p.83)

While a number of these are familiar examples, not necessarily created using TRIZ, the implication is that they could have been, i.e. the method potentially provides for the creation of these kinds of solutions.

However, people, and the different ways that people think and act, are not included explicitly in mainstream TRIZ. There is certainly the opportunity for a ‘BehaviourTRIZ’ to be developed, but we are to some extent lacking the body of formally recorded knowledge about behaviour equivalent to the patents that informed the development of TRIZ. We have no `patent database’ of human behaviour and the `solutions’ for influencing it. Human history, literature, politics—indeed, the entire sum of all cultures—is the resource we have, but it is not formalised through the use of claims as patents are, and is thus difficult to interrogate in this way.

Equally, and perhaps most importantly, the heterogeneity and diversity of people’s lives and culture, and responses to social and contextual factors, do not sit easily with attempts to formalise people’s behaviour into a ‘lookup table’.

A vast meta-analysis of meta-analyses, drawing together everything learned from human history that could be extracted as a `principle’ would be a significantly larger project than a PhD. Extracting insights from a limited number of mainly psychological disciplines, that have direct relevance to design (as it is intended that this series of working papers has done), is probably the most that can be hoped for, at least initially, together with limited use of some of the features of the TRIZ method identified above, where they are appropriate.

In part 2 (coming soon): Design patterns, card decks, and other forms of guide

Image credits

All photos and diagrams by author except: Phonebox photo by Halans on Flickr, CC-licensed; Square-wheel trike by Stan Wagon; Social Design Tools table by Nesta; Screenshot from Polya’s How to Solve It; Screenshot from Nina Volstad and Casper Boks’s ‘On the Use of Biomimicry…’; Screenshot from TRIZ 40; Screenshot from BBC News.
The tables are screenshots from Design with intent: A design pattern toolkit for environmental and social behaviour change by Dan Lockton.

Notes

[1]
Developed in detail in the context of artificial intelligence research by Newell and Simon (1972). Hey (2008, p.15) makes an additional criticism, referencing on the frequent use of rule-based games such as chess by researchers such as Simon as contexts for understanding problem solving: ”an ideation session for an NPD [new product development] project can never claim to have exhausted every possible option, in contrast to, for example, determining what next moves are possible in a game of chess (a classic problem solving challenge).”
[2]
‘Exploring problem-framing through behavioural heuristics’ explores some of the implications of this viewpoint for designers involved in behaviour change. Hey (2008) explores designers’ framing in detail in his PhD thesis, in the context of new product development, in particular how design teams negotiate a common frame for their design situation, and how this is matched to the needs of their potential users.
[3]
One is usually related to the problem under consideration, but the other is randomly drawn, e.g. from a dictionary. Straker and Rawlinson (2002) recount that King Gillette used an `Alphabet System’ where he listed every product he could think of beginning with each letter, as a way of triggering new ideas about improving them. Eno and Schmidt’s Oblique Strategies (1975) are considered in Part 2 of this post.
[4]
See also Hewitt-Gleason (2008) for a statement on the origins of the concept, the sole authorship of which is disputed
[5]
There are some parallels with Goffman (1959): see this paper for a discussion of relevance to design for behaviour change.
[6]
Another more general method, Morphological Analysis (Zwicky, 1969; Ritchey, 1998) may be relevant here. It “is a method for identifying and investigating the total set of possible relationships or `configurations’ contained in a given problem complex” (Ritchey, 1998, p.3), dividing a problem into “major parameters, components or problem dimensions and then systematically allow[ing] the user to identify all the combinations possible with those elements… [and] find all the theoretically conceivable solutions to a problem” (Jones 2003, p.130). Elias (2009) used a Morphological Chart to generate concepts for redesigned refrigerators. Straker and Rawlinson (2002) suggest a range of other verbs which could be used to extend the process, similar to the (longer) lists used in methods such as Synectics (e.g. Nolan, 2003).
[7]
An additional aspect is Simon’s (1969/1981) suggestion that “[i]n problem solving, a partial result that represents recognizable progress towards the goal plays the role of stable subassembly” (p.206), and that “[o]ne way to solve a complex problem is to reduce it to a problem previously solved—to show what steps lead from the earlier solution to a solution of the new problem” (p.226). Hence, perhaps, the joke: “A mathematician wants to read a book, but the room he is in is dark, and the light is off. In order to read, he turns on the light. The next day, the mathematician wants to read a book, and the light is on in the room. He first turns off the light, reducing the problem to the one he solved the previous day”.
[8]
Hey and Agogino (2007) studied the use of metaphor across the entire design process, including extracting and coding designers’ use of terms such as “bounc[ing] ideas off each other”. In particular, one of their codings has some parallels with the scamper methodology discussed above—the idea that “Problems Are Objects: They can be assembled, viewed from a different angle, divided, decomposed, be hard, big, well-structured or ill-structured, transformed, patterned, complex, broken down into sub-problems, refined, clarified, broken into parts, and stable” (p.6).
[9]
Of the 40 TRIZ Inventive Principles, a number which could potentially be more easily applied to behaviour have—indirectly—inspired or influenced patterns in the Design with Intent toolkit. In particular, by the stage of DwI v.1.0, SEGMENTATION, ASYMMETRY, PARTIAL OR EXCESSIVE ACTION and FEEDBACK are all represented in some form, though usually not described in quite the same way as in TRIZ.
[10]
Pickering (2010, p.176) links Gregory Bateson’s concept of the double bind (see here for its design for behaviour change context) to the idea of the Zen koan, an apparently self-contradictory, paradoxical or unresolvable question or statement. It is intriguing to consider the possible parallels with contradictions in TRIZ.

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In the previous post, I introduced the exploration Flora Bowden and I have been doing of sonifying energy data, as part of the SusLab project. The ‘Sound of the Office’ represented twelve hours’ electricity use by three items of office infrastructure — the kettle, a laser printer, and a gang socket for a row of desks — turned into a 30-second MIDI file.

Going further with this idea, I’ve been playing with taking it into (near) real-time, producing sound directly in response to the electricity use of multiple appliances. Powerchord seemed too good a name to pass up. Again using CurrentCost IAMs, transmitting data to a CurrentCost EnviR, this system then uses an Arduino to parse the CurrentCost’s XML stream*, and trigger particular audio tracks via a Robertsonics WAV Trigger. I tried a GinSing to start with, which was a lot of fun, but the WAV Trigger offered a more immediate way of producing suitable sounds.

There are lots of questions – what sort of sounds should the system produce? How should they relate to the instantaneous power consumption? Should they be linear or some other relationship? Should it be an ‘alarm’, alerting people to unusual or particularly high energy use, or a continuous soundtrack?** I decided in this case, that I wanted to build on a number of insights and anecdotes that had arisen during discussion of representing energy use in different ways:

• one of the householders with whom we’re working had mentioned in an interview that she could tell, from the sound of the washing machine, what stage it was at in its cycle, even from other rooms of the house.
• a remark from Greg Jackson of Intel’s ICRI Cities that the church bells he could hear from his office, chiming every 15 minutes, helped him establish a much better sense of what time it was, even when he didn’t consciously recall listening out for them



• the amount of birdsong I can hear (mostly sparrows and blackbirds) both lying in bed early in the morning, and from the hedge behind the garden shed where I work when I’m working from home. Reinforced by a visit to the London Wetland Centre in Barnes a couple of weeks ago
• the uncanniness of the occasional silence as the New Bus for London or other hybrid buses pull into traffic, compared with the familiarity of increasing revs for acceleration
• the multi-sensory plug sockets produced by Ted Hunt during our ‘Seeing Things’ student workshop last year
• the idea of linking time and daily routines and patterns to energy use, e.g. Loove Broms & Karin Ehrnberger’s Energy AWARE Clock at the Interactive Institute.
• the notion of soundscapes, e.g. Dr Jamie Mackrill’s work at WMG with understanding and manipulating hospital soundscapes.
• a recording I made out of the window of my hotel room, on a trip to Doha, of the continuous sound of construction work, interspersed with occasional pigeons
• the popularity of things like Mashup: Jazz Rain Fire
• Gordon Pask’s Ear and attempts to recreate it
• the ‘clacking’ sound of split flap displays (e.g. mechanical railway departure boards) as an indicator that the display has updated, as Adrian McEwen and Hakim Cassimally point out in their Designing the Internet of Things.

All of this led to using birdsong as the sounds triggered – in the video here, blackbirds – at different intensities of song (volume, and number of birds) depending on the power measured by the CurrentCost, at 7 levels ranging from 5W to 1800W+. The files were adapted, in Audacity, from those available at the incredible Xeno-Canto – these include Creative Commons-licensed recordings by Jerome Fischer, Jordi Calvert, Roberto Lerco, Michele Peron, David M and Krzysztof Deoniziak. I also made sets of files using house sparrows, and herring gulls, which proved particularly irritating when testing in the office.

The initial intention was to use multiple IAMs, with different birdsong for each appliance, played polyphonically if appliances are being used at the same time. This is the aim for the next version (and I’ll publish the code), but was stymied in this case by 1) my misunderstanding of the CurrentCost XML spec, and 2) a failed IAM, which conspired together to limit this particular version to one IAM (with multiple appliances plugged into it), at least to have it ready to be shown at a couple of events last week. The prototype you see/hear here, in all its Poundland lunchbox-encased glory, was demonstrated by Flora Bowden and me at the V&A Digital Futures event at BL-NK, near Old Street, and at the UK Art Science Prize ‘Energy of the Future’ event at the Derby Silk Mill. It was more a demo to show that it could work at all than anything particularly impressive.

What’s the overall aim with all this? It’s an exploration of what’s possible, or might be useful, in helping people develop a different kind of understanding of energy use, and the patterns of energy use in daily life – not just based on on numerical feedback. If it’s design for behaviour change, it’s aiming to do so through increasing our understanding of, and familiarity with, the systems around us, making energy use something we can develop an instinctual feeling for, much like the sound of our car’s engine – once we’re familiar with it – effectively tells us when to change gear.

The next version will, hopefully, work with multiple appliances at once, playing polyphonic birdsong, and be somewhat better presented – I’ll post the code and schematics too – and, later in the year, might even be tested with some householders.

*Using a modified version of Colin R Williams’ code, in turn based on Francisco Anselmo’s.
**The distinction between model-based sonification and other approaches such as parameter-mapping sonification is useful here – many thanks to Chris Jack for this.

Thank you to Ross Atkin and Jason Mesut for suggestions! Blackbird photo by John Stratford, used under a CC licence.

The three instruments you hear here represent the electricity use of three items of office infrastructure – the kettle, a laser printer, and a gang socket for a row of desks – in the Helen Hamlyn Centre office over 12 hours from midnight on a Sunday to lunchtime on a Monday, in December, monitored using CurrentCost IAMs. The figures were scaled to provide ranges that sounded better, and converted into a MIDI file using John Walker’s csvmidi and then Aria Maestosa.

The ‘ticks’ indicate each hour’s passing. The ‘honk’ (Tenor Sax) is the kettle (up to 1.5kW when in use). The ‘whine’ (Synth Brass 1) is the Kyocera laser printer. The other synth (Polysynth) is the gang socket, which mainly had a couple of laptops (15W-50W) plugged into it when people were in the office, and a charger (1W) plugged into it otherwise . Lower pitch indicates greater electricity use, hence the high-pitched whine is the background power of the printer (about 10W on standby, rising to 300W-500W when in use).

As the audio starts, you can hear, over the background whine of the printer, the kettle come on as the security guard makes himself a middle-of-the-night cup of tea. Then, early in the morning, the kettle is used three times by the cleaners – twice in quick succession (reboiling?) and then once again. Suddenly, from 9.30, as office staff arrive, the kettle goes on again, laptops are plugged in, the printer starts printing and the energetic hubbub of office life becomes apparent.

Data sonification has been in the news a bit recently, from Domenico Vicinanza’s ‘Sound of Space Discovery’ to Opower’s ‘Chicago in the Wintertime’. It’s something that’s long intrigued me, but if I’m honest, has underwhelmed me in terms of either its actual utility or indeed its impact aesthetically. A (visual) graph is useful because I can use it to find something out. A table of numbers, likewise, even if patterns are less immediately evident. But a beautiful orchestral piece that just happens to draw on aggregated data which are a long way from anything I can comprehend, in scale or meaning, doesn’t tell me anything, somehow. Sarah Angliss was pretty much spot-on in this 2011 Mad Art Lab post.

Energy use is the focus of one of the main projects I’m working on, and one of the strongest findings that came out of interviews and co-creation work with householders that Flora Bowden and I did last summer and autumn was the notion that the invisibility of energy was a major component of householders’ lack of understanding, which contributed – by their own admission – to energy waste.

More than one person specifically suggested that being able to ‘listen’ to whether appliances were switched on or not, and, more interestingly, what state they were in (e.g. listening to a washing machine will give you a good idea as to where it is in its cycle), was potentially more useful for understanding how to reduce energy use than a flashy visual display or dashboard. Sound is potentially even more ‘glanceable’ than glanceables. Even hearing what you’d left on as you went out of the door would be useful. There are echoes of Mark Weiser’s Calm Technology including Natalie Jeremijenko’s Live Wire (Dangling String) but also the ‘useful side-effects’ of things like the ‘clacking’ sound of mechanical railway departure boards as an indicator that the display has updated, as Adrian McEwen and Hakim Cassimally point out in their excellent Designing the Internet of Things.

@danlockton @AaronTinjum My father used to make me listen to fluctuating 50Hz hum of fridge (he was a power station commissioning engineer)

— Oliver Payne (@oliverpayne) November 20, 2013

We also explored aspects of this idea further in our Seeing Things project with RCA students back in November, with contributors including Dave Cranmer and Dagny Rewera having an audio/visual sensory translation element to their work. Of the participants, Ted Hunt took an explicitly multi-sensory approach with his project, including audio, while Francesco Tacchini, with Julinka Ebhardt and Will Yates-Johnson, subsequently went on to create the incredible Space Replay where audio is both monitored and played back in public space.

I’m not saying the ‘Sound of the office’ audio above is particularly good. It was more of a let’s-play-around-with-some-data experiment, and I’ve since found that proper sonification platforms exist. But the approach is something I very much want to explore and build on – possibly whole-house energy use audio disaggregated by appliance, or by activity – and it raises so many interesting questions around what is most useful or most effective at actually either influencing energy use, or helping people understand the complex systems around them. Should it be aesthetically pleasing, or horrible enough it triggers you to turn things off? Is that just the kind of over-simplification that makes most energy monitor displays ineffective? Should the audio be real-time or provide a summary? Should it be paired with visuals? (e.g. like Alexander Chen’s beautiful MTA.ME or Listen to Bitcoin / Listen to Wikipedia) How much should it try to be ‘music’ versus, basically an ‘auditory affordance’ or alarm system? Should there be something about the quality of the sound that indicates something, e.g. load on the National Grid? (Thanks to Aideen McConville and Jack Kelly for this suggestion.)

The field is interesting partly because, post-PhD, I’ve come to realise that what I’m interested in is not so much the question of “how do we influence behaviour?” as an end in itself, but something more like “how do people understand complex systems of which their behaviour is a part, and how do we help them understand those systems better?”. There’s a substantial blog post coming on that, which hopefully draws together lots of interests and ideas, from the IoT to heuristics to seamfulness to affordances to mental models, and (I hope) will set out a kind of research programme which I might be able to get some funding for. But in the meantime, this is certainly part of the direction we’re going in with the ‘energy feedback’ part of the RCA’s work on the SusLab project. It’s going to be ambient, and it’s going to involve more than just numbers and graphs.

Direct link for MP3 file

• In March I joined the Helen Hamlyn Centre for Design at the Royal College of Art, as a senior associate working on the SusLabNWE project, and also some executive education work for partner organisations. It’s a wonderful place with some great people, and I’m very pleased to be part of it. There are some exciting events coming up around the SusLab project, which will be announced later in the summer.

• People and energy: A design-led approach to understanding everyday energy use behaviour, a paper based on the first phase of our SusLabNWE work, co-authored with Flora Bowden, Catherine Greene, Clare Brass and Rama Gheerawo, has been accepted for EPIC 2013, the Ethnographic Praxis in Industry Conference taking place in London in September. A more detailed abstract is also available.

• Last year, my post about behavioural heuristics, based on a workshop run at Interaction 12 in Dublin, attracted quite a lot of interest. I have now had an article, Exploring Problem-Framing Through Behavioural Heuristics, accepted and published in the open-access International Journal of Design, which explores the concept in more detail, using some empirical research around interaction with heating systems from the EMPOWER / CarbonCulture project as examples. The article was co-authored with David Harrison, Rebecca Cain, Neville Stanton and Paul Jennings.

• Last September, Rob Phillips and I ran a stall at the Brighton Mini Maker Faire inviting visitors to create instructions for other people, around the tasks of making tea or making fire. The idea was that the way someone explains a system to someone else can provide insights into his or her mental model of the system, and that asking people to create these kinds of ‘peer instructions’ could be a useful research method for design. We have had an article exploring this accepted for the ACM Interactions ‘On Modelling’ forum, edited by Hugh Dubberly, so ‘Making instructions for others: exploring mental models through a simple exercise’, co-authored with Sharon Baurley and Sarah Silve, should be published in Interactions 20(5) in September 2013. I will make sure an open-access version is available.

• Following my previous Guardian Sustainable Business article, I was commissioned by Autodesk to write another, this time on design for repair and the possibilities of wider sustainability (and social) impacts not just through making products that last longer, but through building people’s understanding of everyday systems, and giving us the confidence to change the world for the better. I think there’s something quite powerful here, and it potentially relates to both civic engagement and the debate over ‘seamlessness’ in interaction design. A blog post about this is in gestation.

• I’ll be writing about thermostats for The Atlantic‘s Object Lessons series (thanks to Ian Bogost).

• Finally, my short biography of Tom Lawrence Williams, the founder of the Reliant Motor Company, commissioned by the Oxford Dictionary of National Biography, has now been published, and appears to be free to view online (most articles need a subscription, which most UK public libraries have).

The article was commissioned by Autodesk, whose Sustainability Workshop team offer some excellent resources for designers and students — e.g. these videos on life-cycle perspectives and other concepts relevant to product designers. Last year the team ran a Design with Intent workshop.

In the earlier days of this blog, many of the posts were about code, in the Lawrence Lessig sense: the idea that the structure of software and the internet and the rules designed into these systems don’t just parallel the law (in a legal sense) in influencing and restricting public behaviour, but are qualitatively different, enabling distinct forms of affordance and constraint. Designers (and developers) — or in many cases those overseeing the process — in this sense potentially wield a lot of (political) power.

My aim initially, arising from my Master’s dissertation, was to chronicle and investigate something like this, but expanded to include ‘architectures of control’ in physical architecture and products as well as digital ones. The blog was a wonderful way to continue this research informally; readers’ comments convinced me that this was an interesting, under-explored subject.

While many examples were socially ‘negative’ — e.g. anti-homeless benches — it seemed that similar techniques could be applied in more socially beneficial ways. B.J. Fogg’s Persuasive Technology offered a template for designing systems to help people behave in ways they wanted (exercising more, eating more healthily, and so on), and this more optimistic approach suggested that maybe I could bring together techniques into a form of use to other designers who wanted to help people, society, and the environment. That led to the PhD, and the Design with Intent toolkit, and gradually the focus drifted away from the ‘code’ angle.

A couple of weeks ago, I was privileged to be part of Submit: Code as Control in Online Spaces [PDF], a workshop at the Good School in Hamburg, organised by Sebastian Deterding (a leading voice on intelligent approaches to ‘gamification’), Jan-Hinrik Schmidt, Stephan Dreyer, Nele Heise, and Katharina Johnsen from the Hans Bredow Institute for Media Research. Eighteen participants, deliberately chosen (curated?) to represent disciplines such as interaction design, games, economics, information science, human geography, media studies and law, spent two days “locked in a room” (as Jen Whitson put it), well-oiled with Club-Mate and Fritz-Kola, exploring questions around code through a series of collaborative exercises. Nele has Storified tweets and photos from the two days, while Jen Whitson has a great blog post going into more detail.

In small groups and all together, we looked at questions* including ‘code literacy’ (who needs to know how code works? what should they know? how should it be taught?), the boundaries of what exactly code can be considered to regulate, intentionality (does it matter? – something I’ve sort of looked at before), historically relevant perspectives (Jacquard loom as the thin end of a long wedge), ‘war stories’ of code’s unexpected effects, and the rise of self-regulation via code as a kind of counterpart to Quantified Self approaches and commitment devices. Via a “dinner of ridiculously bold claims”, we considered the extents of privacy, and personal resistance to control, among other issues.

 
Left photo by Nicolas Nova

With Theo Röhle, R. Stuart Geiger and Malte Ziewitz, I helped devise Doorrank, a kind of “role-playing algorithm game”, centred on the idea of a programmable robot nightclub doorman (player 1), an API which could get information from elsewhere (player 2), some kind of designer / developer / censor / nightclub boss / security authority (player 3) making decisions about what rules to code into the doorman to decide who is let in, and who isn’t, and guests trying to get into the club (other players).

It wasn’t exactly fully resolved in the time we spent on it, but the idea was that by “imagining you’re a software object” (as Nicolas Nova put it), something along these lines could be used as an exercise to help highlight the power, and social consequences, of apparently arbitrary (and often hidden) algorithms in everyday life — and how quickly the idea of tricking the doorman (hacking the system) arises. Jen pointed out the game’s parallels with Memento Mori’s Parsely Games; the initial idea I had was something similar to the explicitly behaviour change-focused ‘Rules of interaction’ exercise I’ve used in a couple of workshops.

Photo by Christian Katzenbach

I went away with a list of new perspectives and angles to investigate, potentially in collaboration with some very clever people, bridging disciplines in increasingly diverse ways. Thanks again to all the organisers and participants for a very interesting few days.

*A vague thing which I suggested as something to explore — but with which I could barely even work out where to start — is the idea of representing code (or rules in general) in visual or tactile ways which would allow their impact to be seen or felt ‘directly’ (whatever that means). For example, a low doorway could be seen as a physical representation of a rule that allows shorter people through and restricts taller people, or Spear’s Spellmaster tiles as a physical representation of spelling rules. I am fascinated and inspired by Mark Changizi’s Escher Circuits and David Cox’s FLIPP Explainers, and the idea of physical “perceptual mechanisms” as a form of embodied cognition, along with some of the more visual forms that analogue computing has taken over the years. But I don’t know quite where this idea could lead, and what exactly it would be useful for.

P.S. Sebastian’s recent presentation on Policy Making as Game Design is also very relevant here.

Most people, for most of their day, are trying to get by. Every day is essentially a series of problems, some minor, some major, some requiring more thought than others. Some we care a lot about; some we wish we didn’t have to. Some are welcome; some we even bring on ourselves because we enjoy solving them; others are deeply unwelcome. Some we care about initially, but then find we no longer do; some we don’t care about to start with, but they become important to us over time.

Many are repeating problems we recognise, and we can use stock responses to solve them — we learn from our experiences, and others’, where we can. A few seem new, but after a bit of thought, we realise we recognise them, and can use those stock responses again (perhaps modified slightly). Some are new, and require us to work out what to do — we might ask others, seek information, try to copy others’ actions, or other approaches. Some are new and we can’t work out how to solve them. Some are old problems that we still can’t solve, or don’t want to. With some, we find a solution that works, even if it’s not very good, and stick with it. It might even be the first one that ‘works’ by some criteria: it works, so it’s good enough. Sometimes we build things (‘tools‘) that enable us, or others, to solve similar problems again. Some are other people’s problems, but they become ours too. Others are ours, but someone else tries to solve them for us.

Often, solving one problem just creates more. It’s almost like our lives are a mesh of interwoven problem threads, some ours, some others’, some collective problems, some individual, some long threads, some short, some made of different materials, but all there. We can’t get from one bit of the cloth to another without travelling along or across the threads.

Sometimes we have a number of different ways we can solve a problem. Often, the way of solving it we choose is the way that’s easiest, or that doesn’t (seem to) cause as many other problems (for us).

And lots of problems never get solved. Some disappear by themselves, but others are just kicked into the future for ourselves (or someone else) to deal with.

It’s very easy to pick holes in the above, but it’s a model which summarises, to some extent at least, what I took away from many of the interviews I did as part of the Empower project during 2010-12. It’s taken me a while to reflect on the findings, some necessary distance for a coherent abstraction to form, but it’s coalesced and it’s actually relatively simple (and obvious). It is also intensely relevant to design for behaviour change, and indeed interaction design in general.

The context of our particular research was asking people about aspects of everyday energy use and sustainability at home and at work, interaction with energy-using systems such as heating, air conditioning, lighting, IT equipment, etc, and people’s understanding of those systems. And the point came across, again and again, that however much people cared, in theory, about their behaviour — and most people in our samples would have scored very highly in any kind of survey about attitudes towards the environment — the challenges people face in everyday life are about getting things done, getting through the day. If ‘saving energy’ or ‘doing things more sustainably’ (whatever that means) becomes another problem loaded onto people’s days, they’ll solve easier problems instead.

Is this ‘laziness’ (or, perhaps more diplomatically, Zipf’s least effort)? It depends how you frame it. If we’re thinking about someone else’s behaviour, we have a tendency to frame it somewhat differently to when we explain our own. I think it’s fairer to take the non-judgemental approach Steve Krug did in Don’t Make Me Think: people are busy, and if you can make it easier for them to solve their problems in a way which reflects the constraints and priorities of the context they’re in (and the other problems they’re trying to solve), that’s a behaviour change approach which might meet with more success than trying to persuade people of the importance of behaving differently as a goal in itself, removed from the context of interaction.

That’s not to say, of course, that people can’t learn through using things, and shape and re-shape their understanding of the world: making things easier does not preclude this, and indeed potentially provides more ‘teachable moments’ than something divorced from context. Equally, in some situations, pre-existing attitudes dominate how someone solves the problems faced, but there are many where it is elements of the context which dominate how people get by [PDF]. It’s certainly not either denying the importance of people having strong motivations and vision to solve problems in non-mundane, non-easiest-route ways. That’s what changes the world, and I’m grateful for it. I’m just interested in the extent to which mundane decision-making is recognised and understood, since many of the things people interact with every day are designed systems.

A few years ago on the blog, I contrasted an ‘enabling’ approach to motivating and constraining as ways to influence behaviour through design, drawing on a particular Buckminster Fuller quote. At the time, I didn’t necessarily consider all the implications of the different approaches in practice, but now the power of the enabling approach strikes me very clearly — from choice of default settings to prominence, this is about helping people solve their problems in ways which are easy and yet which also achieve a ‘good’ outcome for at least one party. In a paper from CHI 2010 [PDF], Carl DiSalvo, Phoebe Sengers and Hrönn Brynjarsdóttir contrasted seeing people as the problem (in sustainability) with trying to solve people’s problems. This strikes me as a fundamentally useful distinction to be made for ‘behaviour change’ work in general.

There are a few directions this discussion can go. I hope to explore some of these in due course, and work out, practically, how the approach can be of use to designers investigating people’s behaviour, and in many cases hoping to influence it.

Cubicles image by Michael Lokner, used under Creative Commons licence.

It’s been quiet here, for reasons which will be explained later, but in the meantime I should mention that CarbonCulture (with whom I’ve been working for the past two years as part of the TSB-supported EMPOWER collaboration) has a new blog.

In anticipation of the forthcoming public launch of the CarbonCulture product, we’re introducing some background on behaviour change approaches, energy use and environmental impact. The first few posts (as of today) introduce:

Your comments are very welcome. Over the next few months we’ll build up the story of what we’ve done — the approaches we’ve taken and what we’ve learned. There’s some further background in this article from Public Sector Sustainability by Luke Nicholson, and a paper I presented at BECC 2011.

My jobs as research fellow (for WMG) and research assistant (for Brunel) on the project have now come to an end, but I’m continuing to provide some input to the project, as well as writing up some papers based on what we’ve learned (so far, a journal paper and a conference paper).

I’m proud to have been associated with what is one of the most empathy-driven user-centred behaviour change projects out there: a fascinating, blend of contextual user research, rapid iterations of new features and approaches, adapting to the needs and interests of a whole range of stakeholders, and getting to apply lots of the ideas that fed into Design with Intent in practical settings and seeing how effective they really are.

Background to the project

CarbonCulture is a research-driven software platform designed to increase staff engagement in more sustainable behaviour at work, in areas such as HVAC and thermal comfort, building occupancy, transport modes and food choices. CO2 emissions from non-­domestic buildings, mainly workplaces, make up 18% of the UK’s carbon footprint, and a combination of technology advances and behaviour change has the potential to make significant impact.

Funded by the Technology Strategy Board’s Low Impact Buildings platform, Brunel Design at Brunel University and WMG at the University of Warwick have been working with More Associates to develop and trial CarbonCulture.

With the Department of Energy & Climate Change’s offices in Whitehall as a pilot site, we have been applying methods from user-­centred design practice to understand diverse users’ priorities, mental models of energy and decision-­making heuristics, and incorporating these insights into the development of the platform. The project comprised an ethnographic research phase, participatory design, and iterative trials; we’ve been both providing academic research input to the development of CarbonCulture, and using the platform itself as a research tool.

CarbonCulture also provides publicly accessible energy displays (both near-real-time and summary) for a number of major public buildings in London, including Tate Modern, 10 Downing Street and the Cabinet Office.

EDIT (April 2013): An article based on the ideas in this post has now been published in the International Journal of Design – which is open-access, so it’s free to read/share. The article refines some of the ideas in this post, using elements from CarbonCulture as examples, and linking it all to concepts from human factors, cybernetics and other fields.

There are lots of models of human behaviour, and as the design of systems becomes increasingly focused on people, modelling behaviour has become more important for designers. As Jon Froehlich, Leah Findlater and James Landay note, “even if it is not explicitly recognised, designers [necessarily] approach a problem with some model of human behaviour”, and, of course, “all models are wrong, but some are useful”. One of the points of the DwI toolkit (post-rationalised) was to try to give designers a few different models of human behaviour relevant to different situations, via pattern-like examples.

I’m not going to get into what models are ‘best’ / right / most predictive for designers’ use here. There are people doing that more clearly than I can; also, there’s more to say than I have time to do at present. What I am going to talk about is an approach which has emerged out of some of the ethnographic work I’ve been doing for the Empower project, working on CarbonCulture with More Associates, where asking users questions about how and why they behaved in certain ways with technology (in particular around energy-using systems) led to answers which were resolvable into something like rules: I’m talking about behavioural heuristics.

Behavioural heuristics

The term has some currency in game theory, other economic decision-making and even in games design, but all I really mean here is rules (of thumb) that people might follow when interacting with a system – things like:

▶ If someone I respect read this article, I should read it too

▶ If this email claiming to be from my bank uses language which makes me suspicious, I should ignore it

▶ If I’ve read something that makes me look intelligent, I should tell others

▶ If that Go Compare advert comes on, I should press ‘mute’

▶ If the base of my coffee cup might be wet, I should put it on something rather than directly on the polished wooden table

▶ If, when asked which of two cities has a bigger population, I have only heard of one of them, I should choose that one

▶ If my friend posts that she has a new job, I should congratulate her

▶ If there’s a puddle in front of me, I should walk round it

▶ If there’s a puddle in front of me, I should jump in it

▶ If I’m short of time, I should choose the brand name I recognise

▶ If I have some rubbish, and there’s a recycling bin nearby, I should recycle it

▶ If I have some rubbish, and there isn’t a recycling bin nearby, I should put it in a normal bin

▶ If that bench is wet or dirty, I should sit somewhere else

▶ If lots of my friends are using this app, I should try it too

▶ If there are lots of pairs of seats empty on the train, I should sit in one of them rather than sitting next to someone already occupying one of a pair

▶ If I can’t see the USB logo on the top of this connector, I should turn it over before trying to plug it in

▶ If I can’t get the USB cable to plug in properly, I should force it

▶ If seats are positioned round a table, I should sit at the table

▶ If I’m trying to lose weight, I should try to choose food with less fat in it

▶ If this envelope has HM Revenue & Customs on the back, I should open it

▶ If this envelope is from BT and printed on shiny paper, I should shred it immediately without bothering to open it

▶ If this website asks me to fill in a survey, I should click cancel immediately

▶ That urinal spacing thing. You know what I mean.

These are a mixture of instinctive or automatic reactions (a kind of ifttt for people) and those with more deliberative processes behind them: the elephant and rider or Systems 1 and 2 or whatever you like. Some are more abstract than others; most involve some degree of prior learning, whether purely through conditioning or a conscious decision, but in practice can be applied quickly and without too much in-context deliberation (hence at least some are ‘fast and frugal’, in Dan Goldstein and Gerd Gigerenzer’s terms). Some heuristics could lead to cognitive biases (or vice versa); some involve following plans, some are more like situated actions. And of course not all of them are true for everyone, and they would differ in different situations even for the same people, depending on a whole range of factors.

Truth tables for people

Regardless of the backstory, though, each of these rules or heuristics potentially has effects in practice in terms of the actual behaviour that occurs. They are almost like atomic black boxes of action, transducers* which when connected together in specific configurations result in ‘behaviour’.

We might construct ‘behavioural personas’ which put together compatible (whatever that means) heuristics into persona-like fictional users, described in terms of the rules they follow when interacting with things, and both (admittedly crudely) simulate** their behaviour in a situation, and, maybe more importantly, design systems which take account of the heuristics that users are employing.

If we know that our fictive user is following a “If someone I respect read this article, I should read it too” heuristic, then designing a system to show users that people they respect (however that’s determined) read or recommended an article ought to be a fairly obvious way to influence the fictive user to read the article. If we know that he or she also follows related heuristics in other parts of life, e.g. the “If I’ve read something that makes me look intelligent, I should tell others” rule, then this action could also be incorporated into the process.

There are two main objections to this. One: it’s obvious, and we do it anyway; and two: treating people like electronic components is horrible / grotesquely reductive / etc. I don’t disagree with either, but am nevertheless interested in exploring the possibilities of using this kind of modelling, simple and lacking in nuance as it is, to provide a way of navigating and exploring the many different ways that design can influence behaviour. If we could do contextual user research with this kind of heuristic as a unit of analysis, uncovering how many users in our situation are likely to be following different heuristics, we could design systems which are not just segmented but tailored much more directly to the things which ‘matter’ to people in terms of how they behave.

Trying it out: thank you, Dublin guinea-pigs

At Interaction 12 last week in Dublin, 41 wonderful people from organisations including Adaptive Path, Google and Chalmers University took part in a workshop exploring the idea of these heuristics and how they might be used in design for behaviour change.

What we did first was a kind of rapid functional decomposition (in the Christopher Alexander sense) on a few examples where systems have been designed expressly to try to influence user behaviour in multiple ways.

The example I worked through first though was a simple decomposition of Amazon’s ‘social proof’ recommendation system: the point was to try to think through some of the ‘assumptions’ about behaviour that can be read into the design, and using a kind of laddering / Five Whys process, end up with statements of possible heuristics.

So with the Amazon example here, what are the assumptions? Basically, what assumptions are present, that if true would explain how the system ‘works’ at influencing users’ behaviour? What I have glibly classified as simply social proof contains a number of assumptions, including things like:

▶ People will do what they see other people doing

▶ People want to learn more about a subject

▶ People will buy multiple books at the same time

And many others, probably. But let’s look in more detail at ‘People will do what they see other people doing’: Why? Why will people do what they see other people doing? If we break this down, asking ‘Why?’ a couple of times, we get to tease out some slightly different possible factors.

After a couple of iterations it’s possible to see some actual heuristics emerge:

Of course there are many possible heuristics here, but for the five uncovered, it’s not too difficult to think of design patterns or techniques which are directly relevant:

There’s nothing there that isn’t obvious, but I suppose my point is that each heuristic implies a specific design feature, and the process of unpicking what the actual decision-points might involve gives us a much more targeted set of design possibilities than simply saying ‘put some social proof there’. Depending on the heuristics uncovered, it might be that simple majority preference (the Whiskas ad), irritating pseudo-authority-based messaging (Klout), friend-based recommendation (Facebook apps), peer voting (Reddit) or even celebrity/expert endorsement (John Stalker and Drummer endorsing awnings) could match individual users’ heuristics better.

Sometimes a service will use more than one, to try to satisfy multiple heuristics, or perhaps because the designers are not sure which heuristics are really important to the user (e.g. the This Is My Jam example below). In some ways, this process is approaching the kind of ‘persuasion profiling’ being pioneered by Maurits Kaptein, Dean Eckles and Arjan Haring’s Persuasion API, although from a different direction.

In the workshop, groups did a similar decomposition on three examples: Codecademy, Opower and Foodprints, part of More Associates’ CarbonCulture platform – the introductory material is reproduced below. [PDF of this material]

For each of these, groups extracted a handful of statements of possible heuristics – for example, for Opower, these included:

▶ If my neighbour can do it, I can do it

▶ If life’s a competition, I want to win it

▶ If I set myself goals, I want to meet them

▶ I don’t want to be the ‘weak link’, so I should do it

▶ I want to be ‘normal’, so I should do it

▶ [If I do it] I will be better than other people

▶ If I get apprecation from others, I will continue to do it

▶ If it stops me being the ‘bad guy’, I will do it

▶ If it stops me feeling guilty, I will do it

▶ [If I do it] I will improve myself

▶ If I don’t do it, I won’t fit in

▶ If I save money, I’ll have it for other things

▶ [If I do it] I will be a ‘good’ person

▶ [If I don’t do it] bad things will happen

We went on to swap some of the heuristics among groups, and build them up into relatively plausible (if completely fake) personas, ranging from a “goth who doesn’t want to do what others do”, to Fido, a guide dog intent on helping his partially-sighted owner Bob (as SVA’s Lizzy Showman mentions here).

In turn, the groups then used the DwI cards as inspiration to generate some possible concepts in response to a brief about keeping that person (or dog) engaged and motivated as part of a behaviour change programme at work, around behaviours such as exercise, giving better feedback and so on. Finally, groups acted these out (photo below shows Fido and Bob!).

Where does all this fit into a design process?

What was the point of all this? The aim, really, is ultimately to provide a way of helping designers choose the most appropriate methods for influencing user behaviour in particular contexts, for particular people. This is what much design for behaviour change research is evolving towards, from Stanford’s Behaviour Wizard to Johannes Zachrisson’s development of a framework.

I would envisage that with user research framed and phrased in the right way, observation, interviews and actual behavioural data, it would be possible to extract heuristics in a form which are useful for selecting design patterns to apply. While in the workshop we ‘decomposed’ existing systems without doing any real user research, doing this alongside would enable the heuristics extracted to be compared and discrepancies investigated and resolved. The redesigned system could thus match much better the heuristics being followed by users, or, if necessary, help to shift those heuristics to more appropriate ones.

Ultimately, each design pattern in some future version of the DwI toolkit will be matched to relevant heuristics, so that there’s at least a more reasoned (if not proven) process for doing design for behaviour change, using heuristics as a kind of common currency between user behaviour and design patterns: user research → extracting heuristics → matching heuristics to design patterns → redesigning system by applying patterns → testing → back to the start if needed

In the meantime, my next step with this is to do some more extraction of heuristics from actual behavioural data for some particular parts of CarbonCulture, and (as my job requires) put this process into a more formal write-up for an academic journal. I will try to make some properly theoretical bridges with the heuristics work of Gerd Gigerenzer, Dan Goldstein and (as always) Herbert Simon. But if you have any thoughts, suggestions, objections or otherwise, please do get in touch.

Thanks to everyone who came to the workshop, and thanks too to the Interaction 12 organisers for an impressively organised conference.

* In reality, the rules have to be able to degrade if the conditions are not met: people are maybe following nested IF…THEN…ELSE loops rather than individual IF…THEN rules. Or perhaps more likely (this thought occurred while talking to Sebastian Deterding on a bus from Dun Laoghaire last week) a kind of CASE statement – which would take us into pattern recognition and recognition-primed decision models…
**Matt Jones suggests I should read Manuel deLanda’s Philosophy and Simulation, which fills me with both excitement and fear…

Image sources: ‘If…’ movie poster; Whiskas ad; Nationwide awnings

Continuing the meta-auto-behaviour-change effort started here, I’m publishing a few extracts from my PhD thesis as I write it up (mostly from the literature review, and before any rigorous editing) as blog posts over the next few months. The idea of how architecture can be used to influence behaviour was central to this blog when it started, and so it’s pleasing to revisit it, even if makes me realise how little I still know.

“There is no doubt whatever about the influence of architecture and structure upon human character and action. We make our buildings and afterwards they make us. They regulate the course of our lives.”
Winston Churchill, addressing the English Architectural Association, 1924

In designing and constructing environments in which people live and work, architects and planners are necessarily involved in influencing human behaviour. While Sommer (1969, p.3) asserted that the architect “in his training and practice, learns to look at buildings without people in them,” it is clear that from, for example, Howard’s Garden Cities of To-morrow (1902), through Le Corbusier’s Ville Contemporaine and La Ville radieuse, to the Smithsons’ ‘Streets in the sky’, there has been a long-standing thread of recognition that the way people live their lives is directly linked to the designed environments in which they live. Whether the explicit intention to influence behaviour drives the design process–architectural determinism (Broady, 1966: see future blog post ‘POSIWID and determinism’)–or whether the behaviour consequences of design decisions are only revealed and considered as part of a post-occupancy evaluation (e.g. Zeisel, 2006) or by social scientists or psychologists studying the impact of a development, there are links between the design of the built environment and our behaviour, both individually and socially.

Where there is an explicit intention to influence behaviour, the intended behaviours could relate (for example) to directing people for strategic reasons, or providing a particular ‘experience’, or for health and safety reasons, but they are often focused on influencing social interaction. Hillier et al (1987, p.233) find that “spatial layout in itself generates a field of probabilistic encounter, with structural properties that vary with the syntax of the layout.” Ittelson et al (1974, p.358) suggest that “All buildings imply at least some form of social activity stemming from both their intended function and the random encounters they may generate. The arrangement of partitions, rooms, doors, windows, and hallways serves to encourage or hinder communication and, to this extent, affects social interaction. This can occur at any number of levels and the designer is clearly in control to the degree that he plans the contact points and lanes of access where people come together. He might also, although with perhaps less assurance, decide on the desirability of such contact.”

“Designers often aspire to do more than simply create buildings that are new, functional and attractive–they promise that a new environment will change behaviours and attitudes” (Marmot, 2002, p.252). Where architects expressly announce their intentions and ability to influence behaviour, such as in Danish firm 3XN’s exhibition and book Mind Your Behaviour (3XN, 2010), the behaviours intended and techniques used can range from broad, high-level aspirational strategies such as communal areas “creating the potential for involvement, interaction and knowledge sharing” in a workplace (3XN, 2010) to specific tactics, such as Frank Lloyd Wright’s occasional use of “very confining corridors” for people to walk along “so that when they entered an open space the openness and light would enhance their experience” (Ittelson et al, 1974, p.346). An appreciation of both broad strategies and specific tactics is valuable: from the perspective of a designer whose agency may only extend to redesign of certain elements of a space, product or interface, it is the specific tactical techniques which are likely to be the most immediately applicable, but the broader guiding strategies can help set the vision in the first place. For example, the ‘conditions for city diversity’ outlined by Jacobs (1961)–broad strategies for understanding aspects of urban behaviour–have influenced generations of urbanists.

Following the influence of Christopher Alexander (Alexander et al, 1975, 1977; Alexander, 1979), such strategies and tactics may be expressed architecturally in terms of patterns, which describe “a problem which occurs over and over again in our environment, and then describes the core of the solution to that problem, in such a way that you can use this solution a million times over, without ever doing it the same way twice” (Alexander et al, 1977). The concept of patterns, and Alexander et al’s A Pattern Language (1977) will be examined in detail in a future thesis extract, for their form, philosophy and impact, but, as an example, it is worth drawing out a few of the patterns which actually address directly influencing behaviour architecturally (Table 1). Among others, Frederick (2007) and Day (2002) both also outline a range of architectural patterns, some with similarities to Alexander et al’s, including some specifically relating to influencing behaviour.

Two examples of pattern 53? Chepstow, Monmouthshire (restored 1524) and Philips High Tech Campus, Eindhoven (c.2000)

Table 1. Summaries of a few of Alexander et al’s patterns (1977) which specifically address influencing behaviour, simplified into ‘ends’ and ‘means’.

Layout of physical elements

Practically, most architectural patterns for influencing behaviour involve, in one way or another, the physical arrangement of building elements–inside or outside–or a change in material properties. In each case, there is the possibility of changing people’s perceptions of what behaviour is possible or appropriate, and the possibility of actually forcing some behaviour to occur or not occur (see future article ‘Affordances, constraints and choice architecture’). These are not independent alternatives: the perception that some behaviour is possible or impossible can be a result of learning ‘the hard way’ in the past.

Barrier on the London Underground (Baker Street, from memory), preventing people running down stairs directly onto the track. Most stairs don’t open straight onto the platform like this.

The physical arrangement of elements can be broken down into different aspects of positioning and layout–putting elements in particular places to encourage or discourage people’s interaction with them, putting them in people’s way to prevent access to somewhere, putting them either side of people to channel or direct them in a particular way (e.g. staggered pedestrian crossings which aim to direct pedestrians to face oncoming traffic; Department for Transport, 1995), hiding them to remove the perception that they are there, splitting elements up or combining them so that they can be used by different numbers of people at once, or angling them so that some actions are easier than others (termed slanty design by Beale (2007), both physically and in metaphorical application in interfaces). Urbanists such as Whyte (1980) have catalogued, in colourful, intricate detail the effects that the layouts and features of built environments have on people’s behaviour–why some areas become popular, others not so, with whom, and why, with recommendations for how to improve things, in contrast to work such as Goffman (1963) which focuses on the social contexts of public behaviour in urban environments.

The layouts of shops, hotels, casinos and theme parks, especially larger developments where there is scope to plan more ambitiously, can also make use of multiple aspects of positioning and layout to influence and control shoppers’ paths–Stenebo (2010) discusses IKEA’s carefully planned (and continually refined) “fairyland of adventures” which routes visitors through the store; Shearing and Stenning (1984) examine how Disney World embeds “[c]ontrol strategies in both environmental features and structural relations,” many to do with positioning of physical features; while Underhill (1999, 2004), formerly one of Whyte’s students, describes how his company, Envirosell, uses observation approach to understand and redesign shopping behaviour across a wide range of store types and shopping malls themselves, much of which comes down to intelligently repositioning elements such as mirrors, basket stacks, signage and seating. Poundstone (2010) cites a study by Sorensen Associates which used active RFID tags fitted to shopping trolleys to determine that US shoppers taking an anticlockwise route around supermarkets spend on average $2.00 more per trip; the suggestion is that stores with the entrance on the right will be more likely to prompt this anticlockwise movement.

Changes in material properties can involve drawing attention to particular behaviour (e.g. rumble strips on a road to encourage drivers to slow down: Harvey, 1992), or making it more or less comfortable to do an activity (e.g., as Katyal (2002, p.1043) notes, “fast food restaurants use hard chairs that quickly grow uncomfortable so that customers rapidly turn over”). The application of some of these physical positioning and layout and material property ideas to a particular social issue is described in the blog post ‘Towards a Design with Intent method v.0.1’ from 2008.

Often combining positioning and material properties, the effect of different seating types and layouts on behaviour comprises a significant area of study in itself, with, for example, work by Steinzor (1950), Hearn (1957), Sommer (1969) and Koneya (1976) helping to establish patterns of likely interaction between people occurring with arrangements of chairs around tables, and overall room layouts in classrooms and mental hospitals. Sommer’s design intervention in the dayroom of an elderly ladies’ ward at a state hospital in Canada–by reducing the number of couches around the walls and adding tables and chairs in the centre of the room, with flowers and magazines–led to major increases in the amount of conversation and interaction between residents.

Osmond (1959) introduced the terms sociofugal and sociopetal to describe spaces which drive people apart and together, respectively; Sommer (1969, 1974) notes that airports are often among the most sociofugal spaces, largely because of the fixed, single-direction seating and “sterile” decor: “Many other buildings… such as mental hospitals and jails, also discourage contact between people, but none does this as effectively as the airport… In practice the long corridors and the cold, bare waiting areas of the typical airport are more sociofugal than the isolation wing of the state penitentiary.” (Sommer, 1974: p.72). Hall’s concept of proxemics (e.g. Hall, 1966) provides a treatment of personal space, its effects on behaviour, and its significance in different physical spaces as well as in different cultures. The different ‘distance zones’ identified by Hall–intimate, personal, social and public–have implications for the design process: “If one looks at human beings in the way that the early slave traders did, conceiving of their space requirements simply in terms of the limits of the body, one pays very little attention to the effects of crowding. If, however, one sees man surrounded by a series of invisible bubbles which have measurable dimensions, architecture can be seen in a new light. It is then possible to conceive that people can be cramped by the spaces in which they have to live and work. They may find themselves forced into behavior, relationships or emotional outlets that are overly stressful” (Hall, 1966, p.129).

Emergence, desire lines and predicting behaviour

“All buildings are predictions. All predictions are wrong”.
Stewart Brand, How Buildings Learn, 1994, p. 178.

“I built skyscrapers for people to live in there and now they messed them up–disgusting”.
Ernő Goldfinger, commenting on tabloid reports of violent crime in the Trellick Tower, above (quoted in Open University, 2001)

In How Buildings Learn, Stewart Brand (1994) contrasts ‘Low Road’ architecture designed to permit adaptation by users, with visionary ‘High Road’ architectural plans which seek to define at the design stage the future behaviour and lifestyles of buildings’ users. High Road plans often ‘fail’ in this sense, unable to anticipate future needs or usage patterns (as Ittelson et al (1974, p. 357) put it, “we are all living in the relics of the past”), while Low Road architecture can cope with changing requirements, appropriation (Salovaara, 2008) and emergent behaviour. The stereotype of architect as a ‘High Road’ planner–perhaps living in the penthouse at the top of the tower block he has designed–resonates in both fact (e.g. ErnÅ‘ Goldfinger’s comment quoted above) and fiction (e.g. Anthony Royal in J.G. Ballard’s High Rise (1975).*

The parallels of the the High/Low Road approaches with the design and use of other systems–in particular software, but perhaps also economic and political systems in general–are evident throughout Brand’s book, although never explicitly stated as such; there are also parallels in planning at a level above that of buildings themselves, such as the clash in New York (Flint, 2009) between the bottom-up approach to urbanism favoured by Jacobs (1961) and the top-down approach of Robert Moses. While it will unfortunately not be considered in detail in this thesis, the emerging power of ubiquitous computing, when integrated intelligently into physical space–”city as operating system” (Gittins, 2007)–could permit a kind of Low Road ‘read/write urbanism’ (Greenfield & Shepard, 2007) in which the ‘city users’ themselves are able to augment and alter the meanings, affordances and even fabrics of their surroundings.

A desire path or cowpath is forming across this grass area in the John Crank memorial garden, Brunel University…

One emergent behaviour-related concept arising from architecture and planning which has also found application in human-computer interaction is the idea of desire lines, desire paths or cowpaths. The usual current use of the term (often attributed, although apparently in error, to Bachelard’s The Poetics of Space (1964)) is to describe paths worn by pedestrians across spaces such as parks, between buildings or to avoid obstacles–“the foot-worn paths that sometimes appear in a landscape over time” (Mathes, 2004) and which become self-reinforcing as subsequent generations of pedestrians follow what becomes an obvious path. Throgmorton & Eckstein (2000) also discuss Chicago transportation engineers’ use of ‘desire lines’ to describe maps of straight-line origin-to-destination journeys across the city, in the process revealing assumptions about the public’s ‘desire’ to undertake these journeys. In either sense, desire lines (along with use-marks (Burns, 2007)) could perhaps, using economic terminology, be seen as a form of revealed user preference (Beshears et al, 2008) or at least revealed choice, with a substantial normative quality.

As such, there is potential for observing the formation of desire lines and then ‘codifying’ them in order to provide paths that users actually need, rather than what is assumed they will need. As Myhill (2004) puts it, “[a]n optimal way to design pathways in accordance with natural human behaviour, is to not design them at all. Simply plant grass seed and let the erosion inform you about where the paths need to be. Stories abound of university campuses being constructed without any pathways to them.” Myhill goes on to suggest that companies which apply this idea in the design of goods and services, designing systems to permit desire lines to emerge and then paying attention to them, will succeed in a process of ‘Normanian Natural Selection’ (after Don Norman’s work).

…whereas this one has been ‘paved’ after pedestrians wore a definite path.

In human-computer interaction, this principle has become known as ‘Pave the cowpaths’–“look where the paths are already being formed by behavior and then formalize them, rather than creating some kind of idealized path structure that ignores history and tradition and human nature and geometry and ergonomics and common sense” (Crumlish & Malone, 2009, p.17). Particularly with websites, analytics software can take the place of the worn grass, and in the process reveal extra data such as demographic information about users, and more about their actual desires or intention in engaging in the process (e.g. Google is a “database of intentions”, according to Battelle (2003)). This allows clustering of behaviour paths and even investigation of users’ mental models of site structure. The counter-argument is that blindly paving cowpaths can enshrine inefficient behaviours in the longer-term, locking users and organisations into particular ways of doing things which were never optimal in the first place (Arace, 2006)–form freezing function, to paraphrase Stewart Brand (1994, p.157).

From the point of view of influencing behaviour rather than simply reflecting it, the principle of paving the cowpaths could be applied strategically: identify the desire lines and paths of particular users–perhaps a group which is already performing the desired behaviour–and then, by formalising this, making it easier or more salient or in some way obviously normative, encourage other users to follow suit.

*It is worth differentiating, though, between a visionary approach which considers human behaviour and sets out to change it, and the approach attributed to some other treatments of the ‘visionary architect’ personality, in which human behaviour is simply ignored or relegated as being secondary to the vision of the building itself. In fiction, Ayn Rand’s Howard Roark (in The Fountainhead, 1943) is perhaps an archetype; Sommer’s architect who “learns to look at buildings without people in them” quoted above is perhaps based on real instances of this approach.

The ticket hall of Stratford City railway station, London, with Westfield logo and the Olympic Athletes’ Village under construction in the background, March 2010

The politics of architecture, power and control

“I was aware that I could be watched from above…and that it was possible to go much higher–to become one of the watchers–but I didn’t see how it could be done. The architecture embodied a political message: There are people higher than you, and they can watch you, follow you–and, theoretically, you can join them, become one of them. Unfortunately you don’t know how.”
Geoff Manaugh, The BLDG BLOG Book (2009, p.17)

Architecture can serve as a regulatory force (Shah and Kesan, 2007) and has been used to influence and control public behaviour through embodying power in a number of ways. Direct use of architecture to change the economic or demographic make-up of areas ranges from policies of shopping centres and Business Improvement Districts to shift the social class of visitors to an area* (Minton, 2009), to Depression-era Tennessee Valley Authority’s mandate to revitalise impoverished areas through massive development programmes (Culvahouse, 2007), to government-driven use of settlements to occupy or colonise territories. In this latter context, Segal and Weizman (2003, p. 19), referring to Israel, comment that “[i]n an environment where architecture and planning are systematically instrumentalized… planning decisions do not often follow criteria of economic sustainability, ecology or efficiency of services, but are rather employed to serve strategic and political agendas”.

Vale (2008) discusses Pierre Charles L’Enfant’s 1791 layout of Washington, DC, often seen as physically reifying the ‘separation of powers’ principle contained in the US Constitution, by separating the buildings housing the branches of government, although Vale notes that L’Enfant does not explicitly mention this as his intention. Along perhaps similar lines, Stewart Brand (1994, p.3) mentions Churchill’s 1943 request that “the bomb-damaged Parliament be rebuilt exactly as it was before… It was to the good, he insisted, that the [House of Commons] Chamber was too small to seat all the members (so great occasions were standing-room occasions), and that its shape forced members to sit on either one side or the other, unambiguously of one party or the other.” Indeed, Churchill’s ‘crossing the floor’ in 1904 (and again in the 1920s) perhaps relied on the physical layout of the chamber for its impact. Ittelson et al (1974, p.139) also note that “[t]he eight months of deliberations in 1969, preceding the Paris Peace Talks, were largely centered on the issue of the shape of the table to be used in the negotiations.”

Internal building layouts are analysed for their ‘power’ implications by Dovey (2008), who uses a system of ‘space syntax analysis’ developed by Hillier and Hanson (1984) to examine diverse buildings such as Albert Speer’s Berlin Chancellery, the Forbidden City of Beijing, and the Metro Centre shopping mall in Newcastle-upon-Tyne. One recurring pattern in political buildings is the intentional use of something similar to what Alexander et al (1977, p.610), in a different context, call ‘intimacy of gradient’–a “diplomatic promenade” (Dovey, 2008, p. 65) selectively revealing a sequence of anterooms to visitors, their permitted progress through the structure (the deepest level being the president or monarch’s private study) calculated both to reflect their status and instil the requisite level of awe. Nicoletta (2003) looks at the use of architecture to exert social control in Shaker dwelling houses, e.g. the use of separate entrances and staircases for men and women, and the lack of routes through the house which did not result in observation by other members of the family.

City layouts have been used strategically to try to prevent disorder and make it easier to put down. Baron Georges-Eugène Haussmann’s “militaristically planned Paris” (Hatherley, 2008, p. 11), remodelled for Louis Napoléon (later Napoléon III) after 1848, had “[t]he true goal of…secur[ing] the city against civil war. He wanted to make the erection of barricades in Paris impossible for all time… Widening the streets is designed to make the erection of barricades impossible, and new streets are to furnish the shortest route between the barracks and the workers’ districts.” (Benjamin, 1935/1999, p. 12). The Haussmann project also involved “the planning of straight avenues as a method of crowd control (artillery could fire down them at barricaded masses)” (Rykwert, 2000, p.91). Scott (1998, p.59) likens the “logic behind the reconstruction of Paris” to the process of transforming old-growth forests into “scientific forests designed for unitary fiscal management”–part of which involves, as Scott emphasies throughout his book Seeing Like a State, the idea of making a space (and the people in it) legible to whoever is in power by removing or simplifying inconsistencies, anomalies and local practices to ‘tame’ potentially dangerous ceintures sauvages. Legibility affords measurement and standardisation, and these (from Domesday Book to the standardisation of surnames, to biometric IDs) afford modelling, regulation and control. Drawing on Hacking (1990), Scott (1998, p.92) suggests that it is “but a small step from a simplified description of society to a design and manipulation of society, with improvement in mind. If one could reshape nature to design a more suitable forest, why not reshape society to create a more suitable population?”

Returning to the specifics of architectural schemes, New York ‘master builder’ Robert Moses’ low parkway bridges on Long Island are often mentioned in a similar vein to Haussmann’s Paris (Caro, 1975; Winner, 1986). These had the effect of preventing buses (and by implication poorer people, often minorities) using the parkways to visit the Jones Beach State Park–another of Moses’ projects. However, Joerges (1999) questions details of the intentionality involved, suggesting that the story as presented by Winner is more of a parable (Gillespie, 2007, p. 72) about the embodiment of politics in artefacts–an exhortation to recognise that “specific features in the design or arrangement of a device or system could provide a convenient means of establishing patterns of power and authority in a given setting,” (Winner, 1986)–than a real example of architecture being used intentionally to discriminate against certain groups (see also the forthcoming blog post ‘POSIWID and determinism’). Nevertheless, Flint (2009, p.44) suggests in his book on Jane Jacobs’ battles with Moses over New York planning, that, at least in his earlier years, “Moses strove to model himself after Baron Haussmann”.

*Minton (2009, p.45) interviews a Business Improvement District manager in the UK who tells her explicitly that “High margins come with ABC1s, low margins with C2DEs. My job is to create an environment which will bring in more ABC1s.”

‘Pig ear’ skate stoppers near City Hall, London

Disciplinary architecture and design against crime

“Where the homeless are ejected from business and retail areas by such measures as curved bus benches, window-ledge spikes and doorway sprinkler systems, so skaters encounter rough-textured surfaces, spikes and bumps added to handrails, blocks of concrete placed at the foot of banks, chains across ditches and steps, and new, unridable surfaces such as gravel and sand.”
Iain Borden, Skateboarding, Space and the City (2001, p.254)

Perhaps difficult to extract from the political dimension of architecture is the notion of disciplinary architecture, covering everything from designed measures such as anti-homeless park benches to prison design, via Jeremy Bentham’s Panopticon (1787) and Foucault’s ‘technologies of punishment’ (1977). Howell (2001) notes that this is often framed as ‘defending’ the general public against ‘undesirable’ behaviour by other members of the public–in this particular case again, measures to make skateboarding more difficult. Similar measures may be installed by members of the public to defend their own properties: Flusty (1997, p. 48) classifies “five species” of “interdictory spaces–spaces designed to intercept and repel or filter would-be users”, many of which occur frequently in residential contexts as well as public spaces: stealthy space–areas which have been deliberately concealed from general view; slippery space–spaces with no apparent means of approach; crusty space–space that cannot be accessed because of obstructions; prickly space–space which cannot be occupied comfortably due to measures inhibiting walking, sitting or standing; and jittery space–space which is constantly under surveillance (or threatened surveillance). Some of the ways of achieving these species of space will be familiar from other examples discussed in this thesis, particularly prickly space.

Prikka strips, a popular brand of add-on DIY plastic spikes for your wall.

‘Design against crime’ has recently received significant attention in the UK via initiatives such as the Design Against Crime Research Centre at Central Saint Martins (e.g. Ekblom, 1997; Gamman & Pascoe, 2004; Gamman & Thorpe, 2007) whose work has addressed some high-profile areas such as bicycle theft and bag theft in restaurants and bars (AHRC, 2008) through innovative product design interventions taking account of the environmental contexts in which crimes occur. While the focus may be on ‘better’ products (as was a much earlier programme by the Design Council focusing on design against vandalism (Sykes, 1979)), the parallel field of crime prevention through environmental design (CPTED) has developed from the early 1970s to date, focusing on redesigning architectural elements to discourage particular behaviours. In the UK, compliance with an Association of Chief Police Officers’ CPTED initiative, ‘Secured by Design’–run by ACPO Crime Prevention Initiatives Ltd–has, according to Minton (2009, p.71), become a condition of planning permission for some large residential developments, leading to the situation where new estates are required to be “surrounded by walls with sharp steel pins or broken glass on top of them, CCTV and only one gate into the estate.”

Crowe (2000) provides a practical guide to implementing CPTED with diagrams and ‘design directives’ for a wide variety of spaces, including schools and student residences. Poyner (1983), in a guide which is effectively A Pattern Language for CPTED, outlines 31 patterns addressing different types of crime in different settings–for example, “4.7 Access to rear of house: There should be no open access from the front to the rear of a house. Access might be restricted to full-height locked gates,” addresses burglary and break-ins. Many of Poyner’s patterns make use of the principle of natural surveillance, described in Oscar Newman’s influential book Defensible Space: People and Design in the Violent City* (1972). Natural surveillance implies designing spaces to afford “surveillance opportunities for residents and their agents” (Newman, 1972, p. 78)–effectively, designing environments so that building users are able to observe others’ activities when outside the home, and feel observed themselves (a concept which, applied in the wider context of digital communications and social media, might be termed peerveillance**). There should be parallels with Jacobs’ (1961) concept of ‘eyes on the street’–although as Minton (2009) points out, implementing natural surveillance via enclosed, gated communities where strangers will necessarily stand out means that the residents can become isolated, targets even for burglars who know that it is unlikely there will be any passers-by (or even passing police) to see their activities.

Katyal (2002) provides a comprehensive academic review of ‘Architecture as Crime Control’, addressed to a legal and social policy-maker audience, but also interesting because of a follow-up article taking the same approach to examine digital architecture (see future article). One point to which Katyal repeatedly returns is the concept of architectural solutions as entities which subtly reinforce or embody social norms (desirable ones, from the point of view of law enforcement) rather than necessarily enforce them: “Even the best social codes are quite useless if it is impossible to observe whether people comply with them. Architecture, by facilitating interaction and monitoring by members of a community, permits social norms to have greater impact. In this way, the power of architecture to influence social norms can even eclipse that of law, for law faces obvious difficulties when it attempts to regulate social interaction directly” (Katyal, 2002, p. 1075).

*‘Defensible space’ covers “restructur[ing] the physical layout of communities to allow residents to control the areas around their homes.” (Newman, 1996)
**The author used ‘Peerveillance’ for a pattern based on this concept in DwI v.1.0, at the time (March 2010) finding only one previous use of the term, on Twitter, by Alex Halavais. As of May 2011, the tweet is no longer findable via either Twitter or Google searches.

Implications for designers

▶ Designed environments influence people’s behaviour in a variety of ways, and some have been designed expressly with this intention, often for political or crime prevention reasons

▶ This can range from high-level visions of influencing wider social or community behaviours, to very specific techniques applied to influence particular behaviours in a particular context; the use of patterns facilitates re-use of techniques wherever a similar problem recurs

▶ Most patterns involve either the physical arrangement of building elements–positioning, angling, splitting up, hiding, etc–or a change in material properties, either to change people’s perceptions of what behaviour is possible or appropriate, perhaps by reinforcing or embodying social norms, or to force certain behaviour to occur or not occur

▶ There are also patterns around aspects of surveillance–designing layouts which facilitate or prevent visibility of activity between groups of people

▶ In practice, patterns may be applied in combination to create different kinds of space with different effects on behaviour

▶ There is potential for ‘paving the cowpaths’ strategically through design, identifying the paths of particular users–perhaps a group which is already performing the desired behaviour–and then, by formalising this, making it easier or more salient or in some way obviously normative, encourage other users to follow suit

▶ By affecting so completely the way in which people spend their lives, political or police attempts to control behaviour through the design of environments can be controversial

▶ Some concepts related to influencing behaviour in the built environment may be transposed to other designed systems and contexts

References

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Reminiscent of a scene from Ballard’s Super-Cannes, the Philips High Tech Campus also includes this lake and boardwalk, perhaps affording breakout meetings and secret discussions away from the earshot of office colleagues, although in full view of the surrounding buildings.

A couple of weeks ago, at dConstruct 2011 in Brighton, 15 brave participants took part in my full-day workshop ‘Influencing behaviour: people, products, services and systems’, with which I was very kindly assisted by Sadhna Jain from Central Saint Martins. As a reference for the people who took part, for me, and for anyone else who might be intrigued, I thought I would write up what we did. The conference itself was extremely interesting, as usual, with a few talks which provoked more discussion than others, as much about presentation style as content, I think (others have covered the conference better than I can). And, of course, I met (and re-connected with) some brilliant people.

I’ve run quite a few workshops in both corporate and educational settings using the Design with Intent cards or worksheets (now also available as a free iPad app from James Christie) but this workshop aimed to look more broadly at how designers can understand and influence people’s behaviour. This is also the first ‘public’ workshop that I’ve done under the Requisite Variety name, which doesn’t mean much different in practice, but is something of a milestone for me as a freelancer.

In the previous post I outlined what I had planned, and while in the event the programme deviated somewhat from this, I think overall it was reasonably successful. Rather than using a case study (I feel uneasy, when people are paying to come to a workshop, to ask them effectively to do work for someone else) we ran through a series of exercises intended to explore different aspects of how design and people’s behaviour relate to each other, and perhaps uncover some insights which would make it easier to incorporate a consideration of this into a design process.

Heuristics and decision-making exercise

After a brief introduction to how design has been and is being used to influence people’s behaviour, we ran through a few questions together intended to explore the idea of heuristics and biases in decision-making. Some questions addressed ‘classic’ behavioural economics issues such as sunk costs, loss aversion and recency/primacy effects–which can all affect users’ interaction with a system. Drawing on the project around energy use in which I’m currently involved with More Associates, we also looked at some heuristics issues relating to users’ interaction with systems across physical/digital interfaces, such as whether the salience of ‘visible’ things such as lighting leads people to overestimate how much energy they use compared with ‘invisible’ systems such as heating and air-conditioning. We briefly looked at anchoring effects and how menu designers use them, and discussed the potential upside of certain heuristics in certain circumstances, such as Gerd Gigerenzer’s ‘fast and frugal’ heuristic [PDF], and how thinking along these lines might result in more intuitive interfaces.

The main insights from this first session were:

• people use heuristics–sets of simple decision-making rules–to work out what to do in different situations, including using products and services

• they’re often relatively sensible and efficient, based on experience and pattern recognition, but can sometimes lead to biases and poor decisions

• so, understanding the heuristics your users use in making decisions about how to interact with your system is important, especially if you’re seeking to influence their behaviour in some way

Black boxes and mental models

Each group received a ‘black box’, an unknown electronic device with an unlabelled interface of buttons, ‘volume’ controls and LEDs. The boxes were children’s lunchboxes from Poundland. Internally–and thus secretly–each box also contained a wireless transmitter, receiver, sound chip and speaker (basically, a wireless doorbell), and in one box, an additional combined buzzer and klaxon. The aim was to work out what was going on–what did the controls do?–and record your group’s model of how the system worked in some form that could explain it to a new user who hadn’t been able to experiment with the device.

Because of the hidden functionality, the boxes’ operation was more complex than might initially have been apparent, and as it was realised that the boxes ‘interacted’ with each other, by setting off sounds in response to particular button-presses, the models generated by groups became more complex. Each group used slightly different methods to investigate and illustrate the system model–an exhaustive kind of state transition table/truth table, a user manual-style annotated diagram of the device, and a diagram focusing on each button or control in turn and elaborating its function. The investigation methods themselves differed slightly, with unexpected behaviour or coincidences (one group’s box setting off the doorbell in another, but coinciding with a button being pressed or a volume control being turned) leading to some rapidly escalating complex models.

The intended outcomes from this session were:

• trying to understand a new or unknown device essentially involves a user applying a number of heuristics to arrive at a mental model which seems OK, or satisfices

• representing and understanding models of system behaviour is difficult if you haven’t done it before, and there’s no universally agreed way of how best to do it to make sense to users

• models of complex systems may need to take into account the behaviour (or effects on) other actors, systems or contexts: very little in the world works entirely in isolation, and a systems approach to understanding technology needs to recognise the effects it has on society, and society on it

These three photos above by Sadhna Jain

Photo by Sadhna Jain

Rules of interaction

Inspired by ‘Wizard of Oz’ testing and Eric Berne’s Games People Play, this exercise involved, in pairs, each person playing the role of either ‘device’ or ‘user’. Facing each other via a ‘screen’ made out of card, and each having a bowl of mixed sweets and toffees, each person picked up a (randomly drawn) set of rules for how to interact with the other–both an objective and a strategy for how to achieve it. The device’s objectives all involved ‘behaviour change’ in some way. The full list of objectives and strategies was as follows:

Device: Objectives
• Try to get all of a particular kind of sweet from the user–for example, all of the shiny-wrappered toffees.
• Try to get the user to eat as many sweets as possible–they can be yours or his/hers.
• Try to get the user not to eat any sweets at all.
• Try to get the user to get up and give his or her sweets to another user somewhere else in the room.

Device: Strategies
• Ignore the user’s understanding or attempts to engage with the situation. Don’t answer any questions, ignore everything the user says, and just keep demanding what you want to try to achieve your objective
• Ask questions to try to understand the user’s perspective, and try to come to an agreement which brings you both closer to your objectives.
• Try to trick the user somehow, e.g. by lying about what you’re trying to achieve
• Try to persuade the user to comply with your objective, by using reasoned, polite arguments to show that you are right.
• Assume the user just wants everything done as quickly and easily as possible, and emphasise that it’s easy to achieve that by doing what you say.
• Assume the user is very greedy, and will readily give up some sweets in return for ones he/she perceives as better. Make them seem desirable.

User: Objectives
• You want to keep as many as possible of your sweets, while acquiring the ones the device has got.
• You don’t want any of your sweets, but you do want the ones the device has got.
• You only want certain types of sweet (e.g. you want only ones with shiny wrappers).
• You want to find out more about the pros and cons of eating sweets, and you expect the device to tell you.

User: Strategies
• You just want things to be as easy as possible. Accept suggestions from the device as long as they’re reasonable.
• Ask lots of questions of the device. You want to understand and find out more about the options available to you, whatever they might be.
• Be open to trading / swapping sweets with the device, but don’t let it get the better of you.
• The device is your servant. Treat it accordingly.

The combination of objectives and strategies was intended to embody ‘assumptions’ about how the other (user or device) would act–in each case, to some extent a mental model of the system and the behaviour of its components. A device which, for example, assumes that “the user just wants everything done as quickly and easily as possible” is embodying a certain ‘designer’s model’ of how the user thinks and will behave.

When the interaction was ‘run’, some pairs quickly arrived at a negotiated result where both were happy, in the sense of their objectives and strategies being mutually compatible, while others reached a kind of stalemate. In at least one case, the device ‘won’ in persuading a user to give up her sweets against her own objectives. In practice, some pairs told each other what their objectives and strategies were, while others kept this secret; some possible lied about their objectives, consistent with the strategies given. Sometimes one person told the other his or her objectives, but the other ignored this (as per the strategy given). Some of the combinations were expected to lead to a degree of recursive second-guessing (the user assuming that the device is assuming that the user is assuming…) or knots, using R.D. Laing’s terminology, although it seems that the workshop participants were too sensible to let this happen!

The intended insights from this exercise were:

• when designers are trying to influence users’ behaviour, they do so with some model embodying assumptions about how users will behave and react to the way the product or service behaves (this is something we explored briefly in a workshop at UX London in 2010, which led to this paper and a forthcoming article in the Journal of Design Research)

• a product or service influencing a user’s behaviour can work best when the objectives of each side and the designer’s and user’s model of the system are compatible

• so, it is important to:
    • try to understand the models that users have of your system
    • design using strategies that match them

Exploring the environment

In the afternoon, we first went on a quick exploratory tour of streets around the workshop venue in the centre of Brighton, looking at some examples of designed situations or ‘interventions’ which aim to influence public behaviour in some way. (My direct inspiration here was Adam Greenfield and Nurri Kim’s excellent Systems/Layers Walkshop concept.) The main examples we examined and discussed were the (remains of the) Tidy Street energy graph, a CCTV camera on a tall pole with anti-climb spikes in the heart of one of the most ‘liberal’ towns in the UK, a ‘Scores on the Doors’ food hygiene rating scheme using stickers on the doors of restaurants and cafes, the conflicts between pedestrians, cyclists and drivers in shopping streets which may appear pedestrianised but aren’t (neatly illustrated by an irate driver shouting at us), and a touchscreen cider advertisement at a bus stop, which invites the public to rearrange ‘fridge magnet’ words to create a limited set of mostly positive messages about the cider which are then apparently submitted to the brand’s Facebook page.

In each case, the aim was to look at the situation from both the designers’ and the users’ points of view: what assumptions do the designers appear to have made about how the public will understand or interact with the product/service/thing? What behaviours are they trying to influence? What is the result? Who are the stakeholders in each situation? Are the designers aiming to target everyone, or only particular groups? (e.g., by asking an older lady waiting at the bus stop about the interactive touchscreen advert, we found that she had no idea that it was anything more than a static ad.) From a design perspective, what kind of research would need to be done to make the interventions more effective? We also considered briefly whether some of the techniques used might translate into other contexts–e.g., could the Tidy Street idea be applied to other statistics or figures in public space? (Marking crime hotspots was suggested.) Which sorts of physical interventions might translate easily into a digital context, and vice-versa?

Tools and processes exercise

Returning to the workshop venue, we spent the rest of the afternoon exploring the processes that each participant uses to research, design and evaluate whatever it is that he or she does, and through discussion together, identify how explicit consideration of user behaviour, mental models and heuristics might be incorporated if influencing behaviour is to be part of the designer’s brief. What tools do people use to incorporate insights from user research into the design process? What assumptions are made about how users think, and how are these assumptions tested? The thinking here was that not only did we have a room full of very experienced people working in a range of digital and other design disciplines, but that they all used slightly different processes, and some cross-pollination between that expertise might be valuable for everyone involved.

In particular, the issue of how the use of personas relates to understanding (and influencing) user behaviour arose from the discussion, since a number of participants’ processes make use of them: some of the main points raised were:

• How much determinism is inherent in rigid use of personas, designing with particular assumptions in mind about how people behave? Is there retrofitting of finished product behaviour to particular persona assumptions?

• The depth or superficiality of personas: do they include any real consideration of behaviour? Has any attempt been made to include a representation of users’ mental models as part of the persona? How might this be done?

• How fixed are personas? How often are they revised? Is there a feedback loop as part of your design process? Could you plan it to incorporate them? Can gathering behavioural data be designed into the product?

• How are edge cases / troublemakers / extreme users included in your personas?

• What about emergent or unexpected behaviours? Can the personas cope with these? How do you even find out what behaviours are emerging?

• Do your personas incorporate a treatment of the history and future relationship of the individual with the product / service / brand? What might this involve if you took changes in behaviour into account?

There were some great anecdotes about personas which I’d probably better not share as they’ll incriminate the participants, but the point to which much of this discussion seemed to be converging was essentially, what might a behavioural persona look like? Could personas even be defined in terms of mental models (“this is how a user with this mental model might behave”)?

Some other points raised in the discussion included:

• How might cultural probes and story construction be used to explore behavioural factors?

• Are different approaches to behaviour used at different levels of the design process? Are assumptions made at once stage which have to be ignored at another?

• Could there be a kind of cross-disciplinary checklist of heuristics or behavioural considerations to address at different stages?

• How much can the designers question the assumptions about users made by a client?

• Is bringing in external specialists such as ethnographers the best way to investigate user behaviour or could the ability be developed by the design team?

• In some cases, designers know exactly who their users are (e.g. for developing products used internally within a company). Could this be extended to consumer products?

• Is it possible for designers to experience products from a user’s point of view? How could you facilitate this?

In summary, then, the last session tried to look at how a treatment of behaviour, the factors affecting it, and how to influence it, might be built into the design processes that organisations currently use. While the Design with Intent toolkit and other great resources such as the Behavior Wizard, Mental Notes or Brains, Behavior and Design seem to have proved useful to many designers facing ‘behavioural’ briefs, I’m under no illusions that they offer a complete process. They don’t: they need proper research with users, to understand the contexts of behaviour and the ways that decisions are made, before trying to influence that behaviour through design. As the ‘Rules of interaction’ exercise demonstrated very simply, when the designer’s and user’s strategies and objectives aren’t aligned, behaviour is unlikely to change in the way the designer intends.

More photos on Flickr.

Thanks to Andy Budd and Kate Bulpitt at Clearleft for inviting me and organising things so well respectively, and to Sadhna Jain for helping out. Do have a look at some of her recent student projects. And thanks too to the participants for being so enthusiastic about what , on the face of it, might have seemed a rag-bag collection of exercises!

Photo by Sadhna Jain

I’m running a workshop on Wednesday 31st August at dConstruct 2011 in Brighton, and I thought it would be worthwhile explaining in a bit more detail what it’s about, and what we’ll be doing.

Here’s the summary from the dConstruct website:

 

Whether we choose to do it or not, what we design is going to affect how users behave, so we might as well think about it, and–if we can–actually get good at it. Bridging the gap between physical and digital product design, a systems approach can help us understand how people interact with the different touchpoints they experience, how mental models and cognitive biases and heuristics influence the way people make decisions about what to do, and hence how we might apply that knowledge (for good).

In this full-day practical workshop, we’ll try a novel approach to design and behaviour, using ourselves as both designers and cybernetic guinea pigs in exploring and developing a combination of physical and digital experiences. You’ll learn how to improve your own decision-making and understanding of how your behaviour is influenced by the systems around you, as well as ways to influence others’ behaviour, through a new approach to designing at the intersection of people, products, services and systems.
 

So what will the day actually involve? (You’re entitled to ask: the above is admittedly vague.) I’ve run quite a lot of workshops in the last couple of years, mainly using the Design with Intent toolkit in one form or another to help groups generate concepts for specific behaviour change contexts, but this one is slightly different, taking advantage of a full day to explore more areas of how design and behaviour interact, in a way which I hope complements dConstruct’s overall theme this year of “bridging the gap between physical and digital product design” usefully and interestingly. Also, the concept of ‘design for behaviour change’ is probably no longer new and exciting (at least to the dConstruct audience) in quite the way it might have been a few years ago: a more nuanced, developed, thoughtful exploration is needed. We’ll be using some of the Design with Intent cards throughout the workshop, but they’re not the main focus.

My plan is for the workshop to have four stages (3 shorter ones in the morning, 1 longer one for the afternoon):

1) Exploring cognitive biases, heuristics and bounded rationality in a design context

Through a short group exercise, we’ll investigate our own decision-making and thought processes—biases and heuristics which might mislead us, but which can also help us, in the context of using products and services (and how we assume users may use them). This section attempts to translate ideas which may be familiar from behavioural economics—Kahneman, Tversky, Thaler, Sunstein, Ariely and others—into technology applications, but also includes the work of people such as Gigerenzer and Goldstein, taking a different perspective on the idea of ‘bounded rationality’ and what it might mean when understanding how people really interact with products and services.

2) Black boxes, cybernetics and users’ mental models of systems

I’m not going to give too many details of this stage, since it’ll spoil the surprise. But (in groups) we’ll be trying to work out what’s going on with a set of unknown products—how they work, and how our behaviour (as users) affects what happens as part of a wider system. There will be breadboards, and LEDs, and cardboard boxes (probably not black), and maybe unexpected things. And Post-It notes, I expect.

3) Designers’ mental models of people’s behaviour

Again, I don’t want to give away too much here, but imagine a cross between a Wizard of Oz experiment, metagames, and some of the ideas discussed here. Basically, in pairs we’ll be playing users and products/services intended to influence behaviour, following our own strategies and seeing what happens. The outcomes of this will be compared (in structure if not in content) to some of R D Laing’s Knots, not to complicate them further(!) but to link them back to the systems/cybernetics perspective which emerged from 2).

4) Prototyping tools for understanding users and influencing behaviour

In the afternoon, the aim is—building on the insights from the morning—to create and develop tools for uncovering and understanding how users think and behave (and match these to design strategies), in a system context. We will have a ‘behaviour’ scenario to investigate, and the scope to examine it from different perspectives. Hopefully this will take in the existing knowledge and expertise some participants will have on user research methods, and build on this with some more explicitly behaviour-related insights. The result will be a set of methods and approaches which ought to be useful and applicable outside the workshop wherever understanding and influencing user behaviour, as part of a system, is needed, and which participants have played a part in creating. These will be documented so you’ll have something after the event as a reference.

If all that sounds like the sort of thing you’d find useful and interesting, there are still (at time of writing) a few workshop tickets available, which also get you into the conference. The workshop takes place at Clearleft’s offices at 28 Kensington Street, Brighton. Any questions / suggestions / ideas please do comment below.

Thanks to Clearleft for organising the conference—it’s been great the last couple of years, and I feel privileged to be part of it this year.

PS: Brighton Dome are right to ask you not to sit on the radiators, really. They’re old, and beautiful.

In a meta-auto-behaviour-change effort both to keep me motivated during a very protracted PhD write-up and demonstrate that the end is in sight, I’m going to be publishing a few extracts from my thesis (mostly from the literature review, and before any rigorous editing) as blog posts over the next few weeks. It would be nice to think they might also be interesting brief articles in their own right, but the style is not necessarily blog-like, and some of the graphics and tables are ugly.

“It is now clear that we must take into account what the environment does to an organism not only before but after it responds. Behaviour is shaped and maintained by its consequences… It is true that man’s genetic endowment can be changed only very slowly, but changes in the environment of the individual have quick and dramatic effects.”
B.F. Skinner, Beyond Freedom and Dignity, 1971, p.24

Behaviourism as a psychological approach is based on empirical observation of human (and animal) behaviour–stimuli in the environment, and the behavioural responses which follow–and attempts in turn to apply stimuli to provoke desired responses. John B. Watson (1913, p.158), in laying out the behaviourist viewpoint, reacted against the then-current focus by Freud and others on unobservable concepts such as the processes of the mind: “Psychology as the behaviorist views it… [has as its] theoretical goal…the prediction and control of behavior. Introspection forms no essential part of its methods, nor is the scientific value of its data dependent upon the readiness with which they lend themselves to interpretation in terms of consciousness”.

Classical and operant conditioning

In an engineering sense, Watson’s behaviourism perhaps treats animals and humans as black boxes* (Sparks, 1982), whose truth tables can be elicited by comparing inputs (stimuli) and outputs (responses), without any attempt to model the internal logic of the system–an approach which Chomsky (1971) criticises. As Koestler (1967, p.19) put it–also heavily criticising the behaviourist view–“[s]ince all mental events are private events which cannot be observed by others, and which can only be made public through statements based on introspection, they had to be excluded from the domain of science.” However, learning (via conditioning) is inherent to behaviourism–both Watson’s and the later perspective of Skinner–which means that the black box is somewhat more complex than a component with fixed behaviour. Classical or respondent conditioning, of the kind explored with dogs by Pavlov (1927)–and often applied in behaviour change methods such as aversion therapy (as for example, the ‘Ludovico technique’ in Burgess’s novel A Clockwork Orange (1962))–repeatedly pairs two stimuli so that the reflex behaviour provoked by one also becomes provoked by the other.

Operant conditioning, as developed by B.F. Skinner (1953) via famous experiments with pigeons, rats and other animals, is essentially about consequences: it involves reinforcing (or punishing) certain behaviours (the operant) so that the animal (or person) becomes conditioned to behave in a particular way:

“When a bit of behaviour is followed by a certain kind of consequence, it is more likely to occur again, and a consequence having this effect is called a reinforcer. Food, for example, is a reinforcer to a hungry organism; anything the organism does that is followed by the receipt of food is more likely to be done again whenever the organism is hungry. Some stimuli are called negative reinforcers: any response which reduces the intensity of such a stimulus–or ends it–is more likely to be emitted when the stimulus recurs. Thus, if a person escapes from a hot sun when he moves under cover, he is more likely to move under cover when the sun is again hot.” (Skinner, 1971, p.31-32)

It is important to note here that in Skinner’s terms, positive and negative reinforcement do not imply ‘good’ and ‘bad’, and negative reinforcement is a different concept to punishment. Positive reinforcement is giving a reward in return for particular behaviour; negative reinforcement is removing something unpleasant in return for particular behaviour. These are subtly different. Pryor (2002) gives the example of a car seatbelt warning buzzer as negative reinforcement–a device designed to be irritating or unpleasant enough to cause the user to take action to avoid it. We might consider that a recorded voice saying “Thank you” after the seatbelt is fastened could be a positive reinforcement alternative. Positive and negative punishment are essentially the inverse of each of these–a fine for not wearing a seatbelt while driving is a form of positive punishment, and taking away someone’s driving licence would be a form of negative punishment. Clicker training with animals such as dolphins and dogs (e.g. Pryor, 2002) arguably combines features of classical and operant conditioning, using an audible clicking device to help ‘mark’ particular behaviours immediately they occur, which can then be positively reinforced with treats–or the click itself can act as a reinforcer.

A major factor in operant conditioning is the schedule of reinforcement that occurs: variable schedules of reinforcement, where a reward occurs on an unpredictable schedule–either ratio (amount of behaviour required) or interval (time required)–can be particularly effective; as Skinner (1971, p. 39) notes, variable ratio scheduling is “at the heart of all gambling systems”. Pryor (2002, p. 22) comments that “[p]eople like to play slot machines precisely because there’s no predicting whether nothing will come out, or a little money, or a lot of money, or which time the reinforcer will come (it might be the very first time).” This principle is inherent in all games of chance–Schell (2008, p.153) recognises it as something a designer can work with explicitly: “a good game designer must become the master of chance and probability, sculpting it to his will, to create an experience that is always full of challenging decisions and interesting surprises.”

*A ‘black box’ approach to modelling human, animal and other system behaviour has also been discussed extensively within cybernetics, e.g. by Ashby (1956) and Bateson (1969).

Social traps

“Like their physical analogs, social traps are baited. The baits are the positive rewards which, through the mechanisms of learning, direct behavior along lines that seem right every step of the way but nevertheless end up at the wrong place. Complex patterns of reinforcement, motivation, and the structure of social situations can draw people into unpreferred modes of behavior, subjecting them to consequences that are not comprehended until it is too late to avoid them.”
Cross and Guyer, Social Traps, 1980, p.16-17

Platt (1973) and Cross and Guyer (1980) discuss ‘social traps’, situations in which there is both reinforcement which encourages a behaviour, but also a punishment or unpleasant consequences of some kind, affecting either the person involved or someone else, at some later point or in some other way. “The behavior that receives the green light becomes supplanted by or is accompanied by an unavoidable punishment…[C]igarette smoking provides a simple example: the gratification associated with smoking encourages future behavior of the same kind, while the painful illness associated with that same behavior does not occur until a point very distant in the future; and when, finally, the illness does occur, no behavioral adjustments exist that are sufficient to avoid it” (p.11-12). There are perhaps parallels with Bateson’s concept of the double bind (Bateson et al, 1956), in which a person is subject to conflicting ‘injunctions’ (reinforcers or punishments) about what ‘right’ behaviour is, with the result that whatever he or she does, will be wrong (and perhaps punished) according to one of the injunctions.

Countertraps–what Platt (1973) suggests might be called ‘social fences’–also exist, where people avoid a behaviour because of (fear of) punishment or undesirable consequences, even though the behaviour would have been desirable. Often the reinforcer is a short-term, local gain, whereas the punishment is a longer-term effect, perhaps affecting a wider group or area: Platt cites Hardin’s tragedy of the commons (1968) as a well-known example of social trap with worldwide social and environmental consequences. Costanza (1987) examines how different kinds of social traps are responsible for a range of environmental problems.

Cross and Guyer’s (1980) taxonomy of social traps is potentially interesting for two reasons from a design perspective, since (in common with some of the cognitive biases and heuristics to be discussed in a later post), design could seek to help users avoid such traps, by redesigning situations to avoid them (hence influencing behaviour), or in some way exploit the effects to influence behaviour, if they are useful in some other way. In Cross and Guyer’s taxonomy, there are five classes of trap (including countertraps), together with a ‘hybrid’ category for traps comprising more than one of the others: time-delay traps, where the time lag between a behaviour and a reinforcer is too high for it to be effective, e.g. “the high school dropout who, avoiding the present pain and unpleasantness of school, finds himself later lacking the education which could have prepared him for a more rewarding job” (p.21); ignorance traps, in which people fail to make use of generally available knowledge when making a decision, but simply rely on immediate reinforcers or superstitions; sliding reinforcer traps, “patterns of behavior [which] continue long after the circumstances under which that behavior was appropriate have ceased to be relevant, producing negative consequences that would have been avoided easily had the behavior stopped earlier… The trap occurs because the rewards establish a habit which persists in the succeeding period” (p.25); externality traps, where “the reinforcements that are relevant to the first individual may not coincide with the returns received by the second… If Peter spends five minutes in a cafeteria line choosing his dessert, he does not suffer for it, but all the people waiting behind him certainly do” (p. 28); and collective traps, which involve tragedy-of-the-commons-type externality traps, involving reinforcers or consequences for multiple participants based on behaviour by one or more.

Cross and Guyer (1980, p.35) suggest ‘ways out’ of the traps, including their ‘conversion’ into trade-offs, “presenting the individual with a set of reinforcers that occur in close proximity to the behavior in question and which closely match the actual reward and punishment patterns that underly [sic.] the situation. The trap then becomes a simple choice situation in which rational and learned behavior are coincident. In some cases–particularly those of time-delay traps–this might be accomplished simply by altering the timing of reinforcers somehow bringing the punishment or proxy for the punishment into closer proximity with its causative behavior.” This could well be the principle behind a design approach to removing social traps, although it relies on being able to determine the structure of reinforcers and punishments which are affecting current behaviour, and somehow redesigning them accordingly.

Means and ends

Studer (1970, p.114-6) discussed applying operant conditioning principles to the design of environments (such as buildings), by treating them as “learning systems arranged to bring about and maintain specified behavioral topographies…What operant findings suggest, among other things, is that events which have traditionally been regarded as the ends in the design process, e.g., pleasant, exciting, comfortable, the participant’s likes and dislikes, should be reclassified. They are not ends at all, but valuable means, which should be skillfully ordered to direct a more appropriate over-all behavioral texture.”

Reconsidering means and ends in this way may provide a useful alternative perspective on design for behaviour change. What may be an end from the user’s perspective (some kind of reward for turning off unnecessary equipment, perhaps) effectively becomes the means by which the designer’s end (the user turns off unnecessary equipment) might be influenced. The designer’s intended end is the user’s means for achieving the user’s intended end (Figure 1). If the end the user desires can be aligned with the means available to the designer, then the behaviour is reinforced. The mapping between ends and means (in both directions) may not seem to be one-to-one on first inspection. For example, the user’s end probably reflects an underlying need–not examined further in a behaviourist context–and likewise with the designer’s end. ‘Receiving feedback on my energy use in the office’–a favourite designer’s means for influencing reduced energy use–is probably rarely expressed as a desired end from a user’s point of view, but if successful at reinforcing conservation behaviour, it presumably fulfils some underlying psychological needs.

Figure 1. The designer’s end and user’s means may be seen as reflections of each other, and likewise with the designer’s means and user’s end. Based on ideas from Studer (1970).

As an informal warm-up exercise in a workshop run at the Persuasive 2010 conference in Copenhagen, the author asked participants (designers and others involved with planning persuasive technology interventions) to map some intended ends relating to socially beneficial behaviour change, and some of the means they could think of to achieve them (Figure 2), using the labels ‘People will do this…’ and ‘…if our design does this’ for ends and means respectively.

Viewing the designer’s means from the user’s point of view, as an end, sometimes involves the end being avoiding something rather than receiving something–i.e. negative reinforcement. It is debatable whether this has much value beyond being simply a warm-up exercise, but it does encourage designers to think about trying to align the ends desired by the user with the means available to the designer. Weinschenk (2011, p.120), in appealing to (mainly web) designers to consider operant conditioning as a strategy for influencing behaviour, asks, “Hungry rats want food pellets. What does your particular audience really want?”

Figure 2. Some means-end pairings suggested by workshop participants in Copenhagen.

Impact of behaviourism

Despite many of behaviourism’s principles having been adopted in other fields–not just animal training but therapeutic applications (e.g. with autism), athletic training, programmed learning via ‘teaching machines’ (e.g. Kay et al, 1968), to the emerging self-help industry (Rutherford, 2009)–it was largely supplanted in the mainstream of academic psychology by the ‘cognitive revolution’ (e.g. Crowther-Heyck, 2005), re-emphasising cognition as something to be understood as a determinant of behaviour. Pask (1969, p.21) refers to “the arid conflict between behaviourism and mentalism,” while Ericsson and Simon (1985, p.1) suggest that “[a]fter a long period of time during which stimulus-response relations were at the focus of attention, research in psychology is now seeking to understand in detail the mechanisms and internal structure of cognitive processes that produce these relations.” Images of Skinner-like scientist figures peering at rats pressing levers to obtain food, with the implication that this was what was proposed for humanity, to some extent cast a shadow of ‘the psychologist as manipulator’ over subsequent work on behaviour change–as Pryor (2002, p. xiii) notes, “to people schooled in the humanistic tradition, the manipulation of human behavior by some sort of conscious technique seems incorrigibly wicked.” Winter and Koger (2004, p.116) suggest that “[s]inister motives are attributed to those who would implement behavioral technology, and Skinner himself has been badly misrepresented and misunderstood as a cold, cruel scientist”.

Skinner’s Beyond Freedom and Dignity (1971), which proposed a new society–“the design of a culture” based on a scientifically refined “technology of behaviour” reinforcing only behaviours which were beneficial to humanity, many of which were essentially about ensuring environmental sustainability–was widely read as promoting a totalitarian future. Chomsky (1971) suggested that “there is nothing in Skinner’s approach that is incompatible with a police state in which rigid laws are enforced by people who are themselves subject to them and the threat of dire punishment hangs over all,” and this view persists, although Skinner eschews the use of punishment in favour of reinforcement. Slater (2004, p. 28) argues that “Skinner is asking society to fashion cues that are likely to draw on our best selves, as opposed to cues that clearly confound us, cues such as those that exist in prisons, in places of poverty. In other words, stop punishing. Stop humiliating. Who could argue with that?”

In a later work, Skinner (1986) offers an explicit ‘design for sustainable behaviour’ view of the possibilities of intelligent use of operant conditioning:

“[W]e have the science needed to design a world…in which people treated each other well, not because of sanctions imposed by governments or religions but because of immediate, face-to-face consequences. It would be a world in which people produced the goods they needed, not because of contingencies arranged by a business or industry but simply because they were “goods” and hence directly reinforcing. It would be a beautiful and interesting world because making it so would be reinforced by beautiful and interesting things… It would be a world in which the social and commercial practices that promote unnecessary consumption and pollution had been abolished… A designed way of life would be liked by those who lived it (or the design would be faulty).” (Skinner, 1986, p. 11-12)

Rutherford (2009, p.102) notes that Skinner himself designed and “constructed a variety of gadgets and devices that allowed him to control his environment, and thus his behavior. For example for many years Skinner rose early to write, often going directly from his bed to his desk. He would then switch on his desk lamp, which was connected to a timer. When his writing time was up, the timer would switch off his desk lamp, signaling the end of the writing period… For Skinner, setting up environmental contingencies for personal self-management was a natural outcome of behavior analysis.”

Regardless of the position of behaviourism in current academic psychological discourse, there are certainly elements which are relevant to design for behaviour change; indeed, the principles of reinforcement can be seen at work underneath many designed interventions even if they are not explicitly recognised as such. As Skinner (1971) argued (see quote opening this section), the environment shapes our behaviour both before and after we take actions, antecedent and consequence (even the absence of a perceived consequence is a consequence, in this sense). This is an important point, since much work in behaviour change focuses on one or the other. A system designed to suggest or cue particular behaviours, and then reward or acknowledge them, covers both intervention points, particularly given the fact that much interaction with products and systems is part of a regular schedule, and users do learn how to operate things through an ongoing cycle of reinforcement: behaviour change does not necessarily happen in a single step. The concept of variable or unpredictable reinforcement has potential design application in situations where a reward cannot be given every time, and also (as noted by Schell (2008)) in the design of games and game-like features in other interactions. The idea of shaping behaviour towards an intended state through progressive rewards for improvements in behaviour rather than every time has relevance in changing habits, which can be important in (for example) establishing exercise and healthier eating routines.

Winter and Koger (2004, p.118) propose what a behaviourist approach to a sustainable society might involve in relation to influencing more environmentally friendly transport choices, which suggests a mixture of different kinds of reinforcement designed into the system: “All the cues encouraging driving alone would be gone. Nobody would be climbing into a car alone, cars would be expensive to operate and roads would be less convenient. People would live within walking or biking distance to their workplace, commute in groups, or use public transportation… Schools and shops would be arranged close by, allowing people to complete errands without the use of a car… We wouldn’t try to change out of moral responsibility or pro-environment attitudes. We would emit environmentally appropriate behaviors because the environment had been designed to support them.”

Implications for designers

▶ Behaviourism is no longer mainstream psychology, but some of the principles could have potential application in design for behaviour change

▶ There is a recognition that the environment shapes our behaviour both before and after we take actions–a useful insight for designing interventions

▶ There is also a recognition that behaviour change does not necessarily happen in a single step, but as part of an ongoing cycle of shaping

▶ Where cognition cannot be understood or examined, modelling users in terms of stimuli and responses may still offer valuable insights

▶ Positive and negative reinforcement, and positive and negative punishment can all be implemented via designed features, and often underlie designed interventions without being explicitly named as such

▶ Schedules of reinforcement can be varied (e.g. made unpredictable) to drive continued behaviour

▶ Design could either exploit or help people avoid ‘social traps’ where both reinforcement and punishment exist, or reinforcement is currently misaligned with the behaviour, converting them into ‘trade-offs’ which more closely match the intended behavioural choices

▶ Considering means and ends may provide a useful perspective on design for behaviour change. The end from the user’s perspective effectively becomes the means by which the designer’s end might be influenced

References

Ashby, W.R. (1956) An Introduction to Cybernetics. Chapman & Hall, London
Bateson, G., Jackson, D.D., Haley, J. and Weakland, J.H. (1956) Toward a Theory of Schizophrenia. Behavioral Science I(4)
Bateson, G. (1969) Metalogue: What Is an Instinct? In Bateson, G. (1969) Steps to an Ecology of Mind. University of Chicago Press, Chicago
Burgess, A. (1962) A Clockwork Orange. Heinemann, London
Chomsky, N. (1971) The Case Against B.F. Skinner. The New York Review of Books, 30 Dec 1971
Costanza, R. (1987) Social traps and environmental policy. Bioscience 37(6)
Cross, J.G. and Guyer, M.J. (1980) Social Traps. University of Michigan Press, Ann Arbor
Crowther-Heyck, H. (2005) Herbert A. Simon: The Bounds of Reason in Modern America. Johns Hopkins University Press
Ericsson, K.A. and Simon, H.A. (1985) Protocol Analysis: Verbal Reports as Data. MIT Press
Hardin, G. (1968) The Tragedy of the Commons. Science 162.
Kay, H., Dodd, B. and Sime, M.E. (1968) Teaching Machines and Programmed Instruction. Penguin
Koestler, A. (1967) The Ghost in the Machine.
Pask (1969) The meaning of cybernetics in the behavioural sciences (The cybernetics of behaviour and cognition; extending the meaning of “goal”). In Rose, J. (ed.) (1969) Progress of Cybernetics, Volume 1. Gordon and Breach
Pavlov, I. (1927) Conditioned Reflexes: An Investigation of the Physiological Activity of the Cerebral Cortex. Translated by Anrep, G.V. Oxford University Press
Platt, J. (1973) Social Traps. American Psychologist, 28
Pryor, K. (2002) Don’t Shoot the Dog: The New Art of Teaching and Training. Interpet
Rutherford, A. (2009) Beyond the Box: B.F. Skinner’s Technology of Behavior from Laboratory to Life, 1950s-1970s. University of Toronto Press
Schell, J. (2008) The Art of Game Design. Morgan Kaufmann
Skinner, B.F. (1953) Science and Human Behavior. The Free Press, New York.
Skinner, B.F. (1971) Beyond Freedom and Dignity.
Skinner, B.F. (1986) Why we are not acting to save the world. In Skinner, B.F. Upon further reflection. Prentice-Hall
Slater, L. (2004) Opening Skinner’s Box: Great Psychology Experiments of the Twentieth Century. Bloomsbury
Sparks, J. (1982) The Discovery of Animal Behaviour. Collins.
Studer, R.G. (1970) The Organization of Spatial Stimuli. In Pastalan, L.A. and Carson, D.H. (eds.), Spatial Behavior of Older People. University of Michigan Press, Ann Arbor
Watson, J.B. (1913) Psychology as the behaviorist views it. Psychological Review, 20
Weinschenk, S (2011) 100 Things Every Designer Needs to Know About People. New Riders
Winter D. du N. and Koger, S.M. (2004) The Psychology of Environmental Problems. Lawrence Erlbaum Associates

B.F. Skinner photo from http://www.pbs.org/wgbh/aso/databank/entries/bhskin.html
Banksy Rat photo from DG Jones on Flickr, licensed under CC-BY-NC