Mulgan suggests that people in the late 1940s, 1960s, and much of the 19th century had a strong sense of how their societies could get better, influenced by utopian literature and social movements (in Western nations at least). There were, too, dystopian narratives – Dickens’ novels, Orwell’s Nineteen eighty-four, Huxley’s Brave new world, and Carson’s Silent spring.

Brad DeLong’s book “Slouching towards utopia” writes about how the world was transformed from the 1870s onwards through technological progress and capitalism, which fueled visions and expectations of universal improvement. However, imagining an economic paradise didn’t create it, wealth accumulated but wasn’t evenly distributed.

And DeLong, as well as others, points out that productivity has been slowing now for several decades. This, combined with concerns about inequality, climate and environmental degradations, probably drives our current leaning towards dystopias.

Fearful narratives rather than stimulating action can become self-fulfilling prophecies, since they can overwhelm and lead to paralysis. But some, like Silent spring, stimulated action because there were relatively straightforward solutions, and shared public and political appetites to do something.

Hopeful narratives about the future are also intended to inspire and stimulate action.

Interestingly, some research suggests that when considering the present we can be quite good at imagining how specific things or experiences can be improved. But for many this doesn’t seem to translate into thinking about broader more generally positive futures thinking.

There are hopeful or inspiring stories if you go looking for them. Future Crunch, for example, sends out regular newsletters highlighting good news stories. And better futures are regularly generated by futures exercises too, they just get outcompeted in the media by the doomy, gloomy ones.

Mulgan suggests that we have a paucity of optimistic thinking (especially within governments) because of too little imagination. Others, such as Vaclav Smil in his book How the world really works, suggest that utopian visions of sustainable societies can suffer from too much imagination - wishful thinking that ignores, or doesn’t critically explore, current realities and barriers. [Smil in turn has been criticised for being too limited in the evidence he uses.]

Navigating the Scylla and Charybdis of futures thinking

Mulgan and Smil are both right. Futures thinking is about expanding imagination, as well as having a critical mind to understand current realities and influences. Too much of the former and not enough of the latter leads to the Charybdian whirlpool of wishful thinking and unrealistic vision statements. Too much of the latter and not enough of the former leads us onto Scylla’s destructive shoals of just tinkering at the edges.

Futures methods help with improving imagination, and in understanding current realities. But I’m often uninspired by futures reports and articles that I read.

So what’s going wrong? Many scenarios or narratives lack both imagination and depth. “Transformative” scenarios skew towards the simplistic, and often are achieved through largely technological steps or sudden changes in collective mindsets.

There is a predominance too of short descriptive futures, focused on telling how a problem from today was solved, or not. See, for example, Reinventing energy futures.

Weakly descriptive idealised futures are often no match for the emotive force of easily imagined disasters. So we need to devote more time to developing alternative futures that resonate.

Short problem-focussed futures exercises are understandable. We (individuals, firms, institutions) aren’t usually comfortable thinking longer term, so futures exercises often need to demonstrate relevance and salience, with an action plan attached, to a current problem. Consequently, they are prone to jump to solutions. “What’s the future of ...?”, “How do we fix ...?”

That’s not a fault of the methods, but rather of mindsets and how we use the the tools we have. Futures exercises can be compressed affairs, based around a couple of workshops. They can also tend to favour the “brain storm” approach, which restricts imaginative and reflective thinking. This means that we can too quickly jump to one preferred future, slogans, and “Magic word solutionism” (see my previous post).

For example, at the moment “circular economies”, “degrowth”, “nature-based solutions”, and “green new deal” proposals are common themes for creating better futures. These can be appealing but are often vague, and so are easy to criticise. Corvellec et al highlight the lack of clarity and substance to some of these terms, and caution against uncritical acceptance of the circle as a metaphor for sustainability issues.

What is being circularised, and what isn’t?; what does degrowth mean in practice, and how will it overcome current power structures and incentives that maintain the status quo?; what qualifies as a nature-based solution?

Imagination can also be restricted by focussing on a problem, and how to solve it. Reviewing climate change trends and developments Elizabeth Kolbert concluded that:

More focus on potentials not just problem solving

Optimistic futures aren’t utopian ones, but they are anti-dystopian ones.

Futures projects that explore and seek to solve critical challenges are necessary, and there are already plenty of those. But they can reinforce a form of “deficit thinking” – if we just fix this then all can be well. We often hope in vain that the problem is completely fixable, and then magic will happen.

To generate more realistically optimistic (or hopeful) futures that gain wider credence we need more projects that credibly explore potential when limits or constraints still exist. I find I’m most creative when there are bounds to work within, or around.

That doesn’t mean accepting the status quo, but it does mean exploring less than perfect futures. Futures where many can feel themselves in them and have some sense of optimism and agency.

Novels (and movies and theatre) of course can do this. But they tend to emerge out of the social climate. More futures ideas and projects, from a greater diversity of perspectives and experiences, helps seed that climate.

The futures tools are available, we just need to be more creative and critical in how we use them. And to treat futures thinking not as a brief and rare activity, but as a capability to be practiced and improved upon over time.

Featured image created with DALL·E 2 using the text: “scylla, charybdis and a unicorn in stained glass”

Unfortunately, many discussions of Aotearoa New Zealand futures don’t seem to explore much of the imaginative space. The desired future state that tends to emerge in workshops, and opinion pieces, is a green and pleasant land (and healthy oceans), with regenerative agriculture, environmental restoration, greater social justice & equity, and vague circular economies.

There is nothing wrong with those ideals. They are common in many scenarios from elsewhere too. But the desirable kiwi future often feels like a slightly higher tech version of the Shire from Lord of the rings. Doing what we have done for the last 150 years, but better. That has not moved us beyond the “farm and theme park” mindset that Paul Callaghan pushed back against over a decade ago.

This, I think, reflects a dominant narrative about Aotearoa New Zealand - “Our economic development has been built on food production. Growing stuff is what we do well, and will continue to do.”

We see our “competitive advantage” as efficient pastoral agriculture and horticulture, so that’s where most of our effort goes. To an extent that is a reasonable position. However, it has also led to complacency, as can be seen from the continued dominance of commodity products.

Avoiding complacency

It can also prevent us thinking about what if that advantage disappears.

Yes, the economy has been diversifying. There is a growing emphasis on enhancing the “bioeconomy”, where higher value products (such as chemicals and specialised materials) are created. This has proven easier said than done so far, as the diagram above illustrates.

But, the economic contributions of services and information technology have also been growing. And there has been a push to improve the manufacturing sector. Aotearoa now has a modest space industry. We also have WētāFX, marine design and technology companies, a growing health technology sector, successful digital game developers, and other innovative firms.

But most people don’t, yet, appear to imagine a plausible future Aotearoa as an industrial or technology “power house.” This is, in part, because there’s no strong narrative to compete against the “Growing stuff” one.

An economy where farming is still an important part of the future may be the most likely future. But it isn’t something that we should assume, or sleepwalk into. By not carefully imagining and exploring other possibilities means other opportunities can be overlooked or poorly prepared for.

One of the reasons for our generally limited imagination may be that the future of farming is frequently discussed, with scenarios of more sustainable or regenerative futures highlighted, usually by industry groups. Examples include FMG, Beef + Lamb, BNZ, and Pure Advantage. There isn’t the same championing of other futures.

Creating other narratives and worldviews

Another reason is that creating effective new narratives can be hard. It isn’t done by throwing out new terms, which seems to be normal practice currently. We hear a lot about “Industry 4.0”, “deep tech”, the “metaverse”, and “radical transformation.” These, along with many other similar terms are common in futures, and policy, thinking, business PR, and research proposals. But they can quickly become “magic word solutionism.” Vague terms that, repeated often enough, become trends in themselves:

Narratives represent a central idea or deeper meaning that is more than just a phrase or a story. As the Narrative Initiative explains, narratives emerge from worldviews and values. For example, “New Zealand helps feed the world” is a common worldview (or frame) of how we see ourselves. The narrative of “we are good at growing stuff” comes from that.

Stories make narratives relatable. They describe something happening (to someone or something). So, a story of a farming family from Inglewood who adopted a lower input approach to their beef and dairy farm and improved production and biodiversity can be an illustration of a narrative about being good farmers and environmental stewards.

Paul Callaghan brought a different narrative to public attention, through his “Wool to Weta” book and his other writings and talks. He emphasised that there are other avenues for kiwi ingenuity that could create better economic opportunities and living standards.

The stories of WētāFX, Rocket Lab, Animation Research Ltd, Xero, Fisher & Paykel Healthcare, etc support that narrative. But they still seem to be seen by many as exceptions or add-ons to an agricultural-based future of Aotearoa. The generational heft of farming narratives persists.

That suggests that alternative worldviews are needed so new narratives and futures are seen as viable, not just anecdotes.

Futures thinking is most effective when it explores different worldviews

That’s where futures thinking can help create stronger connections between stories, narratives, and values. Futures methods help breakthrough biases, stretch the imagination, create new worldviews, and support new narratives. Simplistic approaches, such as two-by-two matrices favoured by typical business consultants, aren’t the answer. These only produce superficial futures, with no story telling power. “Conceptual flatlands” according to Curry & Schultz.

More intensive and participatory methods are required to move beyond the familiar and obvious. One example of a more engaging way of imagining desirable futures is through using the “seeds approach.”

In one of my recent projects a “seed” I planted was the possibility of Aotearoa developing a new chemical industry, through studying and replicating chemical reactions occurring around marine black smokers. Just like the undersea world, there are unexplored futures for us to still consider.

A 2021 report from the International Transport Forum - Travel Transitions. How Transport Planners and Policy Makers Can Respond to Shifting Mobility Trends - considers this. It looks at why transport planners didn’t foresee changes in mobility patterns over recent decades, their generally poor performance in predicting transport demands, and how planning can be improved.

The report shows that common analytical and decision-making methods for transport planning are no longer fit-for-purpose. The way planners think about the future also needs to change.

Its messages are relevant to other fields of planning, and to futures thinking more generally.

The main point is that traditional forecasting models provide a false sense of certainty in changing times. Uncertainty is usually hidden (unintentionally or not), rather than being explored.

The foresight field too is strewn with over-confident predictions of what are the important factors shaping the future.

The report doesn’t reject the use of models, but argues that better models (and mindsets) are needed, and that they shouldn’t be the sole basis for planning decisions.

As any good foresight practitioner will tell you, taking the time to formulate the futures questions is critical to success. You shouldn’t just grab a model to generate an output value. Asking “how may demands for transport be influenced over the next two decades?” leads to a very different approach to planning than asking “what will demand be in two decades?”

Six important foresight messages from the report are described below.

Novelty is often the Achilles heel of models

Models usually don’t cope well with significant unanticipated changes, such as new travel options and behaviours.

It can also be difficult to determine whether newly emergent behaviours and activities are short-lived fads or will become an important influence. If they are viewed as fads, they are ignored or discounted (as the first automobiles were).

On the other hand, extrapolating out from a fad can distort expectations too. The augmented reality game Pokémon Go was very big in 2016, but this type of mobile game hasn’t yet become the norm.

If they do become an important trend, there remains considerable uncertainty over what time period, and how, the impacts could be felt. This is the case for autonomous vehicles, when for the last decade fully autonomous driving was expected by many to be just around the technological corner. Assumptions about use of autonomous vehicles also haven’t been well tested.

This requires resisting the temptation to identify the next big thing, or prematurely calling the demise of the last big thing. A range of potential trajectories needs to be actively considered, and monitored over time, to improve understanding.

The need to take a broader system view

Planning and other models may not take account of broader system factors that influence future demand (or supply), or they assume that the influences won’t change. For example, the ITF report notes that long term travel trends are influenced more by wider societal changes (such as the nature of work) than by changes in transport systems.

Similarly, whether working away from the office will become common or not depends on a range of factors, which may not be accounted for in models, or in “hot takes.”

So, when times are changing you shouldn’t just rely on the usual sources and suspects for information.

Focus on hypotheses not simplistic explanations

A discussion paper that supported the report noted that studies of earlier transport transitions usually developed ad hoc qualitative explanations rather than hypotheses of change. There has often been a belief in the importance of a particular factor that influences future transport demand, which subsequent research shows played only a modest (if that) role.

And even if one or a few factors accounted for much of a previous transition, it doesn’t mean they will for future ones.

Hypotheses encourage exploration. For transport planning, the report notes that development of good hypotheses requires interdisciplinary collaboration. Testing them requires good data sources, long-term perspectives, and a focus on processes not just outcomes.

Being data informed not data driven

Quantitative approaches are common in most areas of planning, and becoming so in other foresight projects. As more and larger data sets, and methods to analyse them, become increasingly available it is tempting to add them into models. These can provide benefits, but the type and quality of data, and the algorithms used, need to be carefully considered.

Theory-free approaches, where patterns in the data are identified without hypotheses for how they come about, can be useful initial steps. But patterns don’t always illuminate processes, so hypotheses will still need to be developed to help plan better.

As Nobel Laureate Paul Nurse commented, “data should be a means to knowledge, not an end in themselves.”

It is often assumed that the critical indicators to measure activities have been identified, and the appropriate data is available. That’s not always the case, especially in periods of change. Available data, rather than the best data may be used. If they can’t be easily quantified critical factors may be omitted from models. Clarity on why particular data are used and how, and why other data sets are not, is becoming more important to understand the strengths and limitations of models and their outputs.

Models may not take account of considerable variability between regions and between different population groups. For example, transport patterns can vary in different parts of the country and between different age groups.

The report also recommends combining rather than replacing traditional data sources (like surveys) with new sources (such as mobile phone records), since this can help identify and understand longer-term trends as well as more rapid changes.

Focus on plausibility and adaptability, not precision

 The report advocates for a shift from “predict and provide” to a “decide and provide” approach. The focus shifts from precision to plausibility. “Decide and provide” is a vision-led strategy, where a desired future state is defined and actions set out to help this come into being. It notes some planning initiatives are already taking this approach, which was developed in part from Waka Kotahi’s (NZ Ministry of Transport) futures work in 2014 (see Lyons & Davidson 2016).

The “decide and provide” approach is intended to provide adaptability in response to unanticipated changes. It moves away from reacting to trends and locking in policy decisions and infrastructure, toward what it calls “regime-testing.” This involves more explicit questioning of how the world or system is operating, leading to the development of a vision that informs rather than reacts to policy decisions.

Developing a range of scenarios is advocated. These shouldn’t be used as just descriptions of how the future may look, and then picking one. Instead they help to highlight uncertainties, and shape the vision and the actions to achieve it.

Recognising governance challenges

The report doesn’t just examine the planning process. It also highlights governance challenges associated with changing planning approaches. Overcoming these challenges, the report recognises, is much harder than simply identifying them.

One is siloed organisational structures, which often inhibit taking a broader view of the system the planning activity operates within. Such as having transport planning run by the transport agency, rather than collaboratively by a broader collective of agencies that cover the key influences on transport.

Another is the multi-layered nature of transport governance. This involves local and regional councils or governments, and the national government. Power and incentives usually differ between them, creating conflicts. The power usually rests with those who collect the taxes, but, the report notes, the land use decisions are usually set at the local and regional levels. Such governance complexity will often be common for other foresight projects. This highlights that power structures and differences in values and practices shouldn’t be overlooked when thinking and acting for the longer-term.

A third important challenge is having the organisational capacities to change. The report identifies “professional impotence” as a barrier to change. This is where individuals can see a need for change but the norms and expectations associated with traditional practice make it difficult to actually change.

The report identifies four types of capacities (based on a framework from Hölscher et al.)  needed to transform approaches to governance:

The report closes by noting that transformation doesn’t, and can’t, depend on perfect institutional arrangements. But it is dependent on “… the willingness and openness to reflect, reconsider, explore and challenge established processes and standard ways of thinking and doing.”

Featured image by Nick Fewings on Unsplash

Existential risks are driving thinking about the long term

There is an uptick in discussions about long-term thinking and “existential risks.” Concern about the latter, along with the Covid-19 pandemic and climate change impacts, often drive the former.

Existential risks are events with the potential to wipe out most of humanity (and many other species) – asteroids, nuclear wars, climate crises, malignant artificial intelligence, plagues, etc. Though in a sign that “existential risk” can quickly become a slogan, a United Nations report recently labelled wide-spread disinformation as an existential risk.

“Longtermism” or intergenerational thinking is often a “new to us” western phenomenon. Māori and some other indigenous societies have traditionally incorporated inter-generational thinking into their decision making.

In western societies it usually pops up again after times of crisis - after the second world war and in the 1960s. But some organisations have been in the longer term thinking space before the pandemic. The Long Now Foundation has been championing long-term thinking for nearly three decades.

More recently, Wales established a Future Generations Commissioner, and Finland’s parliament has a Committee for the Future. Singapore’s government too has been building longer term thinking capabilities for over a decade.

There are a variety of approaches to long term thinking. They are distinct by the scale at which they operate, and the values that drive them.

Wrongtermism

At one end of the continuum, William MacAskill’s recent book What we owe the future offers what it calls a guide to extreme long-term thinking. It projects out over the next million years. His premise is focussed on solving existential risks, largely with technologies, to unlock humanities “real potential.” He calls for a “moral revolution” because he contends that the world’s long-run fate depends, at least partly, on the choices we make over the next few decades.

It received a glowing uncritical review in the Guardian, and has be praised by others because it offers what they see as an optimistic view of the future, in contrast to abundant pessimistic ones. Part of its appeal is that it also doesn’t appear to require much change to existing economic systems.

On the other hand, a polemical commentary on the book called MacAskill’s version of longtermism a “quasi-religious worldview.” It highlighted some of the questionable values and ethical views in MacAskill’s and his supporters ideas.

A more reasoned exploration of some of MacAskill’s ideas can be found in an article in The New Yorker. It notes that most of his support comes from a narrow ideological base, who imagine a technological utopia. The economists’ myth of the rational consumer replaced by one driven by data and optimisation. The article also mentions that MacAskill’s future is called most charitably by some critics “clueless”, and that looking so far ahead is pointless.

Even some of MacAskill’s colleagues at Oxford & Cambridge criticise the “techno-utopian approach” to this type of long-term thinking. They point out that insufficient consideration is given to how to prevent existential risks that result from technological developments. And, that the future isn’t a simplistic choice between “technological maturity” and extinction. They criticise the proponents of techno-utopianism of ignoring the visions and values of most of the planet they claim to want to save.

The future isn’t deterministic

MacAskill’s grand narrative of the future mimics the simplistic grand historical narratives of Jared Diamond, Yuval Noah Harari, and Steven Pinker. They favour key historical turning points, involving technological, social, environmental and/or political determinism.

“The Journey of Humanity: The Origins of Wealth and Inequality” by Oded Galor  is another optimistic book about humanity’s future. Taking a macrohistory perspective too, it suggests that we’ll be able to face future challenges, because we have in the past. That comes across as too glib and rosily -tinted hindsight.

An alternative historical view was proposed recently by Graeber and Wengrow in their book The Dawn of Everything: A New History of Humanity. They reject the sweeping narratives of many historians. And they reject determinism too, favouring human improvisations to circumstance. But in their analysis it didn’t always end well.

That’s not a call for inaction now, and reliance on “she’ll be right” and “Number 8 wire” attitudes. Graeber and Wengrow stress the importance of humans not being passive.

Cathedral thinking and colonising the future

Calls to return to “Cathedral thinking” have also become more common over the last five years. This references the vision of cathedral building centuries ago, where multiple generations were required to complete them. Or, more prosaically, (re)planting woods whose timber wouldn’t be needed for a century.

While this metaphor can be useful for inspiration, one risk is that it initiates utilitarian or vanity projects. We must build something big (looking at you Saudi Arabia), rather than change the system.

Another risk is that a cathedral thinking mindset can fail to imagine how values and societies change. Cathedrals can be wonderful to look at, but they are rigid and high maintenance. Today only a small proportion of a city may use them for their intended purpose.

A growing concern for some futures thinkers is that what we start now needs to be considered carefully to avoid what has been referred to as “colonising the future.” How much are we casting our values and needs forward, constraining the future rather than creating foundations for future generations to shape to their needs?

Becoming good ancestors

Roman Krznaric has focused on this, promoting the concept of being a “good ancestor” (derived from the Iroquois nation and other indigenous societies). This helps individuals, communities, and institutions identify things that they can do to, potentially, help future generations (like local habitat restoration projects).

In Japan, this has led to a “future design” movement, where urban design involves participatory democracy and imagining how residents could want to live seven generations into the future. This challenges current ideas about how to design or redesign cities.  

“Seeds of good anthropocenes” is another initiative . It is helping share stories about communities that are creating realistic and optimistic visions of what the world could be. We are seeing examples of that in Aotearoa New Zealand, such as the growing number of local habitat restoration and clean-up projects, and Te Kura Whare.

Rather than one dominant vision of the future these approaches provide space for different ideas, values and approaches at a more local level. And, in illustrating new opportunities.

Where they can struggle is in effecting broader societal or systemic changes.

Breaking through the present

A big challenge to long-term thinking is that it gets crowded out by the present. Grand visions soon topple under the storms of the now. We’ve seen that with the pandemic. Early on, a recognition and desire to make sure “this never happens again.” Now, being ground down to returning to some sort of “normality”, and responding to more immediate social, economic, and political consequences of the past two years (or in reality, the last few decades).

Graeber and Wengrow commented that “Nowadays, most of us find it increasingly difficult even to picture what an alternative economic or social order would be like,”

Overcoming this requires further changes in mindsets and institutional incentives. This is where futures literacy and futures thinking, as well as practical examples, are essential. Necessary, but not sufficient.

The forgotten long-term skills

An underappreciated long-termist challenge is the growing diversity of long-term thinking projects or proposals. On the one hand it is great to see a flowering of ideas and initiatives. An innovators’ delight.

But on the other hand, many of the initiatives may have conflicting values and approaches. And proponents of individual projects can hold strong views on why their approach and goals are right. In turbulent times people can prefer certainty, even if short-sighted.

Rather than creating a metaphorical cathedral, we are potentially heading for many nascent symbolic Towers of Babel. Competition overwhelms cooperation.

Promotion of long-term thinking often assumes that a better future will emerge given the opportunity or vision. But it can neglect how competition and conflicts will need to be shepherded so that future generations are better placed to create their own opportunities.

There won’t be a single perfect long-term vision or idea. This is the oft neglected part in futures. There is no utopia, but a tangled bank of ideas, values and compromises. Like history, the future isn’t a simple narrative with clearly marked tipping points. Futures require active ongoing participation, nurturing, and humility. Skills and attitudes that still are often under developed.

Featured image: Cary Bates on Unsplash

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]]>Thinking over the longer termRobert HicksonWed, 24 Aug 2022 02:25:09 +0000https://www.dayonefutures.nz/blog/2022/8/23/illustrating-complexity-in-environmental-scans58da0ce6e3df28fabb790f1d:5c7b28544785d3d5f26e1430:630571f3e752e017a640ee14Environmental scanning is an essential futures practice. The purpose of scanning is to systematically identify trends, developments, and points of inertia that may influence an organisation’s (or society’s) future operating environment. Scans typically focus on the implications of trends and developments over the short to medium term (from a few years to the next couple of decades), or sometimes the longer term.

Done badly (and it often is) such scans are often just a set of bullet points identifying common trends with little analysis – an ageing workforce, digital transformation, environmental crises, etc. These don’t lead to any real insights into the most important challenges and opportunities facing the organisation.

Done well, environmental scans help set the stage for more detailed examinations of future consequences and potential organisational (or societal) actions and strategies.

Scanning is also not a once and done activity. Things keep changing, so repeated scanning is essential. However, systematic scanning takes a lot of effort, and regular scanning appears to be the exception for many organisations. Or at least for those who publicly release their scans.

New Zealand Search & Rescue’s environmental scan

A local exception is New Zealand Search and Rescue, which provides leadership for the sector. It has updated its environmental scans several times in the last five years. A variety of government organisations, charities, and businesses are involved in providing search and rescue services, so the scans are used to inform a range of stakeholders about how demand for and supply of search and rescue services may be affected by a variety of changes (and lack of change).

I was asked to update their scan this year. While largely a computer-based activity, I supplemented the online research with interviews of people in organisations who are involved in search and rescue operations. This helps to reality check assumptions about general trends or developments.

This year’s scan in addition to providing a general update also considered what the medium-term implications for the pandemic may be, as well as looking more closely at how changing activities and conditions in Antarctica and the South Pacific could affect search and rescue.

Previous year’s scans were designed to be read online, which is a challenge because there is a lot of information. So this year, PDF versions were created to make the current scan (and previous ones) more useful for those who want to browse it offline or have a printable version. [Currently the latest scan is only available in pdf form, an online version is being developed]

Visual summaries

A key challenge with environmental scanning is synthesising different, often voluminous, information into useful insights. Scans are typically based around categories – such as social, technological, economic, environmental, and political trends. It is easy, but unhelpful, to list a lot of different trends and developments under these categories without showing how they could influence each other.

For the latest NZSAR scan we write about how different trends and developments can reinforce or oppose each other. But that can make rather a dense read. A good summary helps, but visuals often illustrate interactions to greater effect.

In general though, I’ve found most diagrams summarising environmental scans are too simplistic. Search for images of “environmental scan” and you’ll see what I mean. They usually don’t show how different trends can contribute (positively and negatively) to several possible outcomes in combination with other trends or developments.

Visualising interactions for the NZSAR scan proved to be challenging, so couldn’t be completed before the end of the contract. Now, though, I’ve developed some charts to illustrate the diversity and patterns of trends and developments. They are based on Sankey diagrams, which can be created relatively easily using SankeyMATIC’s website. They aren’t perfect, but show some promise for further refinement.

Below are five charts that show how demand and supply for search and rescue services may be affected by different trends. The information is drawn from the scan, although there is some additional interpretation for how trends and impacts are categorised in the charts to avoid making them too difficult to interpret. They are intended to highlight some key points, rather than be detailed summaries.

What the diagrams do is show how many “sources” (particular trends or developments, clustered by broad categories) influence different “targets” (factors that contribute to demand &/or supply). For clarity I’ve shown increases and decreases in both demand and supply separately. I’ve also not included the specific trends or developments that lead to the implications (such as number of people active outdoors, and attitudes & behaviours), because that makes them too messy. But I have indicated how many specific trends contribute to each outcome.

For the diagrams I clustered the trends and developments identified in the scan into 14 social trends or developments relevant to search and rescue, two (broad) technological, five economic, two environmental, and two political categories.

Insights from the diagrams

A clear message from the diagrams is that increased demand for search and rescue services is influenced by a larger number of factors than decreasing demand. And, unsurprisingly, different numbers and types of trends contribute to different demand or supply influences. The diagrams show this succinctly compared to the written text.

For example, a large number (14) of different trends or issues contribute to the number of people active in the outdoors, with more than half being social factors (the increasing number of older people, greater ethnic diversity, improved physical activity programmes, greater mobility, etc). The pattern of influences for decreasing demand is, unsurprisingly, different.

Effects on the supply of search and rescue services were looked at in terms of capacity (people and assets) and capabilities (like skills and training). Increases in capacity and capability are likely to be affected more by technological and political factors, while some economic trends adversely affect supply.

The environmental scan also considers how trends influence funding, business and governance models for search and rescue organisations. The diagram of that isn’t as informative as the others.

Limitations

While these charts do provide more insight than a generic illustration, they still have limitations. For me the main one is that the same trend (such as an ageing population) can contribute to several different demand (and supply) outcomes, but Sankey diagrams can’t show that properly. All the charts do is illustrate the number of “source” factors (on the left) that link to each “target” on the right hand side.

 To more clearly illustrate all the targets a trend contributes to requires more specific diagrams. Instead here I have just duplicated trends when they link to more than one outcome, implying a more diverse set of influences.

This limitation can also be overcome by manual creation of the charts in another drawing package, but that requires considerably more work. A simpler work around is to further annotate the diagrams, but this becomes messy as more trends connect with more outcomes.

The second major limitation is that the diagrams can be misinterpreted. So a good description of the diagram is needed. Sankey diagrams are quantitative, so thicker bands/lines could be interpreted as greater influence. That’s not what I’ve used them for. The intent is to just illustrate the number of factors that influence an outcome.

While a large number of social trends affect the number of people who are active it isn’t intended to show that social factors or more people active in the outdoors are the most important factors that will affect demand. A single economic trend could have greater influence on the number of people active outdoors, than several social trends. But the environmental scan didn’t determine which factors may be more or less influential.

The SANDYMatic application also orders and scales the charts automatically, so you can’t keep them consistent between the charts.

Still, I think these types of diagrams, with further refinement, may be useful for helping illustrate insights from environmental scans

IEA’s big shift

In May I noted the significance of the International Energy Agency’s announcement that further investments in new fossil fuel supplies is not needed. 

They have now released their World Energy Outlook-2021 report. This notes that country commitments to reducing carbon emissions won’t achieve the necessary reductions to avoid more than a 1.5 degree temperature increase by 2050. 

The report advocates for a more ambitious effort to replace fossil fuels with cleaner sources of energy. This builds on their strategic shift in May towards renewable energies. The Outlook report emphasises how disruptive the next decade will be in terms of changes in energy sources and supplies, and the consequent potential for geopolitical disruptions.

Kingsmill Bond has an excellent short summary of IEA’s press conference associated with the report’s release, and the change in arguments about energy change that the IEA makes.

It’s not all change though. The IEA report implies that we can mitigate at least some of the impacts of climate change while still having economic growth.

Getting to more sustainable lifestyles

That “growth is good” mantra is being increasingly challenged. Though it is very resistant to fundamental change.

Jeremy Lent argues that “the end of capitalism” is required to solve the climate crisis. That is a point that has been made by many others too. They emphasise that environmental damage isn’t just a consequence of our sources of energy and fuels. It’s a consequence of emphasising consumerism and economic growth.

Lent highlights the vested interests of multi-national corporations and how they are formally and informally excluding other important perspectives from discussions future directions. Not just in energy, but in food and other aspects of life. 

Lent points out some of the initiatives that are taking a more communal or ecological approach to economics.

But I’m wary of throwing the capitalist baby out with the libertarian bathwater. That is a simplistic argument. It’s the unfettered aspects, and prioritising economic factors over others, that seem to be doing the harm.

What it takes to get to fairer and more sustainable consumption is explored in greater detail in the 1.5-Degree Lifestyles report from Germany’s Hot or Cool Institute.

Their 10 “Lessons from research on enabling sustainable lifestyles” on page 30 are particularly useful. Three of my favourites are:

• Change needs to focus on the choice architecture (eg, “nudging”), social values and norms, physical infrastructure, and provisioning systems. 

• It is important to differentiate between the factors that can be addressed at the individual level and those that are beyond individual control, and to recognise how the two are mutually reinforcing. 

• People’s expressions of happiness correlate with the level of trust in the community, social ties, education, health, and meaningful employment; and these tend to be less consumerist. 

The report also emphasises that real change requires inspirational visions that show how needs can be met differently through ways that are less resource-intensive. Currently, the report states, most campaigns emphasise reductions and the loss of familiar ways of living. That doesn’t build a supportive coalition of the willing. 

That’s a point made too by Noah Smith in his critique of the degrowth movement.

Moving on from solutionism 

Going back to Lent, I also disagree with his view that there is a “solution” to the climate crisis. That is taking a simplistic view of a changing climate as a complicated issue that has a solution. It isn’t and doesn’t. There is no real winding back the atmospheric clock now (at least over the next few generations). 

Ironically, a solutionist approach is also the one taken by those keen to keep much of the status quo. Everyone wants a clear solution even if there isn’t one.

Carbon Capture and Storage, for example. This is often most strongly advocated for by backers of fossil fuel and mining interests, has long over-promised and under delivered. There’s Gigatonnes of gap between current demonstration projects and meaningful effectiveness. Critics point to the magical thinking about how quickly such technologies can mature and be viable. 

Plus, it is an approach that reinforces the current system of cleaning up the messes, rather than not creating them in the first place. 

Climate change refugia

The focus is shifting to adaptation, alongside mitigation.

Cass Marketos discusses the emergence of “climate change refugia”. These are conservation efforts focussed not on restoration, but on looking ahead.

Some projects are looking at reforesting areas with species more likely to be able to survive warmer temperatures and more frequent wildfires. Others are about identifying habitats or environments that appear to be more persistent despite changes in the climate. These could provide “slow lanes” enabling species to adapt to changing climates. 

These mostly seem to be focused on terrestrial environments, though marine ones are being looked for too. And it remains to be seen if they work. 

Climate shadows

Emma Pattee has proposed that instead of climate footprints we should be thinking about our climate shadows. 

She makes the very good point that just accounting for your individual climate footprint provides no information about what your real impacts are.

This is illustrated by examples of a frequent flyer climate scientist and a sedentary PR person who works for the oil industry. Their work and influence can have very different impacts on the practices and behaviours of others. 

Your climate shadow is a broader accounting of all of your choices, and how they may influence climate impacts. Something that follows you. It includes a carbon footprint, as well as lifestyle expectations and behaviours, choices (such as the number of children or pets, the type of work you do), and what attention and effort you devote to climate issues.

Pattee doesn’t regard it as a new measure. Most of the things she describes can’t be converted into realistic kilograms of carbon. 

It’s value is as a prompt. Less actuarial and more activating. Improving awareness of what you do and the impacts that you may be having, particularly in the hard to measure behaviours and activities, and seeing if there is anything else that you can do. That applies to organisations as well as individuals.

I’d expand the concept to be an environmental shadow so that it is more inclusive of other environmental impacts (energy and water use, waste and recycling, pest control, etc).

Komorebi - shifting from characterisation to evocation

Metaphorical footprints and shadows are by their nature backward looking. They account for what we’ve done and identify what can be reduced.

But, as the 1.5-Degrees Lifestyles report discusses this doesn’t provide a compelling vision or attractor of the type of lifestyle you (or society) can achieve through making those reductions and changes.

We usually confuse vision with a list of characteristics; like renewable energy, sustainable lifestyles, or a circular economy. Or as Erik Hoel described a lot of technology futures, “plotless sci-fi.”

A motivating vision has to have an emotional allure.

The closest counterpoint to shadow I can come up with at the moment for this type of vision is Komorebi. A Japanese word, variously and imperfectly translated as ‘sunlight filtering through leaves’, or ‘the scattered light that filters through when sunlight shines through trees.’

Something intangible perhaps, or incompletely articulated, but none-the-less it stirs the soul or is evocative. That has got to be something that we need to guide rather than prescribe, to help get us through the coming decades.

I can’t think of examples from the futures field that capture this. There may be some out there, just not in the corporate world. Art and literature do this best.

I’m not going to attempt to describe such a vision here, that’s going to take considerable time and skill. Something to focus on over the summer I hope. 

Many of the articles I’ve included here I came across via Andrew Curry’s great Just Two Things newsletter. He highlights a diverse collection of interesting topics and writers, and provides insightful commentaries on them.

Header photo by Mohamed Nohassi on Unsplash

Are we living in fast times?

Many futures studies focus on how fast the world is changing now. Partly that seems to be a marketing strategy – who’s going to pay attention (and fees) if there isn’t a sense of urgency?

It’s often based on poor analysis. The criteria for declaring “unprecedented change” are typically vague, subjective, or just non-existent. And ignores the fact that not all change is equal. 

There’s often a lot of presentism to overcome in futures. We tend to over-emphasise the changes were are experiencing now, so can easily overlook or under-estimate the scale of change from earlier times.

Kavanagh et al. do a good job of exposing this, with their analysis of social changes. They examine the question “Are we living in a period of particularly rapid social change?” Their conclusion is no.

“… there is no doubt that we are living in a period of change, but so does every generation.” Kavanagh et al.

They note that many changes are just current manifestations of long-term trends. Based on the data they use they propose that there was more social change in the first half of the 20th Century than between 1970 and now.

The future abhors a smooth curve

Social change doesn’t occur in long waves. Fitting social and other changes to nice orderly curves is common practice in futures work. This is used, consciously or subconsciously, to bring order to a messy situation. But not necessarily objectively. Yes, there can be general cycles, but particulars matter.

Kavanagh et al. find that their data set suggests a model of long periods of relative stability followed by radical or punctuated change. I’ve also previously described the long and winding rivers of social change.

They end their paper by rhetorically asking why, and to whose benefit, is there so much talk about living in a period of rapid and unprecedented change.

Being lulled by transitions

While social and technological changes may not be unprecedented, the pace and scale of some other changes definitely are. And, we are usually pretty tardy at changing quickly ourselves when the real need arises. That’s the message in an article by Alex Steffen.

The word “transition” can be a dangerous futures term. It is used often and is meant to signify a major change or set of changes. I’ve covered some of these previously. 

However, it can also be used, or interpreted as, a “don’t scare the horses” expression. A relatively smooth change where challenges can be addressed in an orderly manner. Just the message Ministers, Chief Executives, and senior management teams want to hear.

It is easy to focus on the end point of the transition, rather than all the messy stuff that happens during the transitional stages – competing world views, disagreements about decisions and the real nature, scale and pace of changes required.

That’s where methods such as the Three Horizons Framework are useful. They help people engage in the “horizon two”, the period of transition where consequential decisions need to be made. An example is one I used in BRANZ’s issue paper Environmental Challenges, Opportunities & Transitions for Construction in NZ.

It is a very good method, but the smooth schematic curves can sooth the managerial mind, rather than stimulate urgency.   

Beware the discontinuities

Alex Steffen makes the point, in relation to climate change and other environmental crises, that the time has passed for an orderly transition. We aren’t in a period, he contends, of managing “issues” but in a change in era. He refers to this as a “discontinuity”, where slight improvements to old things and systems aren’t sufficient.

What is required is new things done in new ways, and at a faster pace and bigger scale. That is what many futures people point out too. However, it is easy to say but hard to do.

Groups can agree about the need to change, but not about the nature and pace of required changes. Promises of bold actions combined with the continuation of current practices and systems amounts, in his view, to magical thinking.

We see that in discussions about climate change. Steffen argues that declaring big but distant goals (such as net zero carbon by 2050), and proposing incremental steps to achieve them may be more to deflect criticism and show an organisation is “doing enough” or “doing its bit.”

This was illustrated recently by Supran & Oreskes' analysis of ExxonMobil’s rhetoric on climate change, and Culhane et al’s analysis of lobbying in Massachusetts. 

Incrementalism can also be a sign not of resistance to change but of a failure to grasp the nature and urgency of change required. That, though, is getting harder to accept.

The latest IPCC report suggests that net zero by 2050 is achievable, but requires immediate, rapid and large-scale reductions of all greenhouse gases, Something it was also saying three years ago.

Discontinuities require different capabilities

A third factor is that organisations, institutions and individuals can lack the capabilities to deal with discontinuities.

One of Steffen’s key points is that organisations (both public and private) need decision-makers with better sets of incentives and interests, the drive to act quickly, and expertise not centred on maintaining current systems. 

Some will actively resist such change, due to avarice, fear or other factors. Changing that will often require external pressure:  

“We cannot build a better future without leveraging the power of governments—and we cannot leverage that power without exerting even greater democratic pressure through advocacy.” Steffen

Steffen emphasises the need for developing acumen (the ability to make good judgements and take quick decisions) for times of “upheaval, chaos and weirdness.”  

Discontinuities are rare, so most people have no expertise in how to handle them. Therefore quick and influential learners are essential. The challenge for foresight and strategy professionals is to discourage incremental thinking, and make the case for developing the acumen to address discontinuities. Don’t invite a futurist if all you want is reassurance.

He provides 12 ideas to help develop your own acumen.

 A good tip is that if people are spending a lot of time saying they are “doing their bit” then they probably don’t have a sense of urgency of the problem.

Discontinuity isn’t to be confused with “disruption”, another commonly used futures term. Steffen sees disruption as part of the response to discontinuity – developing “disruptive” solutions (whatever that may mean), or disrupting existing patterns of thought and practices. 

Competence matters more than clarity

As we have seen in the pandemic, rapid development of competence to deal with a novel fast moving situation is essential. 

With climate change and other environmental crises the same attitude and approach is needed. Pay more attention to our ability to change quickly, rather than describing how quickly the world we are part of is changing. 

Featured image by Leio McLaren on Unsplash

Temporally, there’s three types of futures too. Short-term, medium-term, and long-term. 

Those are all relative, depending on what you are looking at. Some technologies, for example, change very quickly, so “long-term” may be less than a decade. In contrast, societal change often plays out over decades, while environmental changes may occur over a century or more.

Unlike for Goldilocks, none of these futures timeframes will be “just right”, because the future isn’t edible or a piece of furniture. Nor is it a destination. But it’s important to consider which timeframe(s) best suits the issue(s) you are interested in.

Often futures reports seem to pick a date out of the ether and then fit the subject matter into it, regardless if that timeframe is “too hard or too big” (that is, too long) or “too soft or too small” (too short) for what’s under consideration. Or they avoid trying to think in several timeframes.

Many recent futures projects by governments, and other organisations, seem to be going for the soft futures option. Twenty to thirty years is now seen as ambitious. This may reflect how seldom we look ahead, and how poorly we handle uncertainty. There is a reluctance to stray too far from what we can anticipate. 

Three decades is only six to 10 election cycles, and roughly one new generational cohort. Not long-term thinking at all. But it gives the impression of confidence that we can plan out to that date.

España 2050

A recent example of the shorter term futures approach comes from Spain.

Spain is seeking to transform itself by 2050. It has produced a huge report, España 2050 (in Spanish, naturalmente), that sets out how education, health and social services, the public sector, transportation, regional development, and the tax system need to change.

The Spanish government is asking for feedback on the plans, and will be holding a “national dialogue” later this year.

Aspects of the report are summarised in English here.

Sensible stuff for the most part, though changing taxes and pension schemes will be sure to create heated discussions. 

Notice the nice smooth curves. Very soothing. Nothing messy or chaotic. And it is going up, so that must be good. Everything is under control.

On the whole the report is technocratic rather than inspiring. Useful as far as it goes, but it seems to focus on attributes – better educated young people, more efficient health system, a more productive economy. There’s no bigger picture, such as what Spaniards would like their lives and society to be like in 30 years.

It has defined the preferred future and is asking for feedback, rather than involving communities and businesses in exploring a range of futures. 

Apart from proposing new taxes, it seems to be promoting a “business as largely usual” and “catching up with the neighbours” approach, with new money into old systems. Some structural changes, but nothing much deeper.

New Zealand’s myopia

New Zealand is still struggling to think just a few years ahead. Goldilocks hasn’t got very far inside the house yet.

An example is the Public Service Act 2020. This includes a requirement (in Schedule 6) that departmental chief executives publish a long-term insights briefing to the appropriate Minister at least once every 3 years and must do so independently of Ministers. The purpose of these are to make publicly available “information about medium- and long-term trends, risks, and opportunities that affect or may affect New Zealand and New Zealand society.”

You would have thought that this type of activity is already a core part of the public service. It’s a belated start, given how the world has changed over the last few decades.

As Dennis and colleagues point out there isn’t much internal capability for these briefings. There is a risk that departments will do them poorly if they view them as simple in-house exercises using staff inexperienced in foresight practices. 

I’ve read plenty of “insights” documents from the public and private sector, and most present very few real insights. See my Types of futures reports post for a visual summary. [And if you are looking for help in developing good insights reports Day One Futures can assist]

Examples of futures thinking in New Zealand

There are some kiwi beacons. But on the whole they are short-termist.

Several years ago the Ministry of Transport looked 25 years ahead to consider demand. That’s reasonable for what they were looking at.

Taranaki’s 2050 Roadmap looks to the region’s economic and social future. Developing it involved considerable community engagement, though implementing the roadmap now appears to be a problem.

Predator Free 2050 is already working on achieving its vision. 

And, The McGuinness Institute has been promoting discussions about a long term future for Aotearoa New Zealand. 

On a much longer time scale Kono (a food and beverage company) has a 500 year vision to “preserve and enhance their taonga for the benefit of current and future generations.” Other Maori organisations are also thinking multi-generationally. The strategies for achieving these aren’t, though, always clear.

Zealandia and other ecosanctuaries have 500 year visions with more tangible plans and outcomes. 

 So, we have tended to look ahead in terms of decades, with a few ultra-long term aspirations at the other end.

The 100 year gap 

Thinking five-to-30 years out is a start. It can help build familiarity, capabilities and confidence. It may be a realistic frame for the issue, such as modelling transport demand. Sometimes, as with Predator Free, the timeline provides a strong challenge that stimulates action and innovation.

But we shouldn’t limit futures thinking just to two or three decades. We can fool ourselves that real change can be quicker to achieve than it often is, or that more radical change isn’t feasible. Twenty or 30 years out is often seen as a destination, rather than just a way point.

Thinking in terms of five centuries can be inspiring, but is just aspirational if it isn’t linked to more than short term actions or a set of principles. 

What we shouldn’t overlook is the 50-to-100 year timeframe. I’ve found very few examples of that in New Zealand. (I’m currently working with an organisation that is looking 50 years ahead).

This is the realm where you are forced to accept uncertainty, and explore a range of more diverse futures. For some it will be more uncomfortable than just looking ahead two decades. For others it will be liberating. The consequences of system changes usually emerge within this time zone, and it takes us out of thinking about our own lives and generation.  

It is more than just having a set of sentiments or picking off attributes (like greater socio-economic equity, or more environmentally sustainable) that we address in isolation. It is about imagining what living in those worlds could be like, making choices now about them, and developing actions to help us start creating a better future for coming generations.

“Where does New Zealand want to be 100 years from now?” is a critical question for us. This requires creating a shared vision and actions to move toward realising it, not just a slogan. Having a longer term collective focus makes it more than likely we’ll be more able to help shape the future, rather than just reacting to change. Something, the pandemic has highlighted.

Elsewhere, some have been calling for more “Cathedral thinking” – setting long term goals, or a far-reaching vision that won’t be fully realised for several generations. This shouldn’t be just narrowly focussed mission-style problem solving.

Reducing carbon footprints, mitigating the impacts of climate change, and eradicating pests don’t give us much insight into how we will be living our lives once (or if) we achieve these. Aotearoa New Zealand hasn’t got to this stage of thinking yet.

In the end Goldilocks is discovered and thrown out, so the house’s inhabitants can go back to their comfortable life. The tale is sometimes viewed as a cautionary tale, warning about the hazards of wandering off and exploring unknown territory.

In contrast, futures thinking and foresight is about that wandering and exploring. We shouldn’t be settling for the first chair, bowl of porridge, bed, or reassuring time frame we come across. 

Featured image: Arthur Mee and Holland Thompson, eds. The Book of Knowledge (New York, NY: The Grolier Society, 1912), Public domain, via Wikimedia Commons

The International Energy Agency has long been criticised for misreading renewable energy trends. Last week though, in their report Net Zero by 2050 they made a recommendation: 

There is no need for investment in new fossil fuel supply in our net zero pathway

That is a major shift. The report makes it seem like they are one of the first to come to this conclusion. But it’s a major change from an agency known to stick closely to the status quo.

Good intentions?

In a similar vein, the CEO of Shell stated that half of the company’s energy mix will be “clean” later this decade.

If we do not make that type of process by the middle of this decade, we have a problem not just as a company but as a society.

They leave out what happens and when to the other half.

And BlackRock, the world’s biggest asset manager, has indicated that it will push companies it invests in to improve their efforts to protect the environment from deforestation, biodiversity loss and pollution of the oceans and freshwater resources.

Good intentions, but as the company’s former head of sustainable investment, Tariq Fancy, has indicated the free market can’t solve the climate crisis. Its incentives are to make profits, so he thinks companies more often look to avoid investing where they risk having lower profits, rather than address climate change directly.

Fancy argues that it is governments that need to lead change in relation to the climate. There are systemic causes that individual companies can’t or won’t address. 

This is illustrated by Ford motor company. Their electric F-150 Lightning truck has received good coverage over the last week. Big points of discussion have been the number of electric outlets it has (11!), and the ability to act as a backup power source for the home. Ford’s Executive Chairman said the truck  

will fulfill our promise to our children and our grandchildren that our generation is committed to leaving them a cleaner planet.

This is more spin than substance. Ford’s vision (and many other vehicle companies) seems to be we can keep building oversized vehicles, just make them electric. It ignores the resources required to manufacture them, and assumes that life can go on pretty much as usual, sans sacrifice.

Sure, there will be some need for utility vehicles, but seeing the future as the same as today, just electrified, isn’t fulfilling any promise to future generations.

A recent study found that the emission savings from replacing internal combustion engines with zero-carbon alternatives will not occur fast enough. A greater focus on active transport, such as cycling, in cities is required. 

Rethinking the system, not the technology, is critical. 

 “A judgement for the century”

A quite different context and quote signalling change, comes from our own justice system. Kennedy Warne has highlighted what he calls "a judgment for the century", which grants customary marine title to hapū from Te Whakatōhea in the Bay of Plenty.

This placed tikanga (the belief systems, values and life experience of the tangata whenua), rather than at the heart of the decision. Property rights were interpreted through the tikanga lens, rather than tikanga being considered through a property lens.

The judgement states

Whether or not an applicant group has established that they held an area in accordance with tikanga is to be determined by focusing on the evidence of tikanga, and the lived experience of that applicant group. The exercise involves looking outward from the applicant’s perspective rather than inward from the European perspective and trying to fit the applicant’s entitlements around European legal concepts.

As Warne notes, that “outward perspective” is significant, especially in legal decisions. He highlights that judges have been taking the lead on incorporating Māori tikanga into decision making.

That’s a subtle, but definite, sign of change.

Photo by Jens Lelie on Unsplash

There are very good reports out there. You just need to read with a critical eye.

Photo by Markus Spiske on Unsplash

Irregular labour

Is the private sector the best provider and facilitator of “gig work”? That’s challenged in a New Yorker profile of Wingham Rowan, an English social entrepreneur. For many years he has been trying to get governments to develop a platform to help people find gig work (or “irregular labour”). 

Rowan views gig work as being better run as a public utility rather than as a private company. This is because the utility model would focus on finding work for people that matches their skills across a range of employers, and in ways that are more likely to provide them with good working conditions and liveable incomes. 

Current private sector gig work typified by Uber, DoorDash and similar companies, is largely about people getting relatively unskilled work, with no benefits, in one particular task.

Persuading governments (national and local) has proven difficult. This is due to political, ideological and technical reasons. Governments focus on full-time work, and they may lack (or think they do) the technical skills to develop good on-line platforms. Rowan thinks that governments can improve employment if they focus more on improving the nature and benefits of gig work.

This has elements of the “Sharing economy” but broader and larger in scale.

The article notes some recent promising developments by some local governments in the US and UK. 

The pandemic is in part helping that shift, through challenging the notion that the private sector is always superior (a myth long challenged by Mariana Mazzucato). Though there are also societal changes too, with peoples’ preferences for when and how they work changing. 

Traditional full-time employment may not be the norm in the future, so government perceptions need to change.

 “Twenty-somethings talk about having a job like having a fax machine,” Wingham Rowan

No Robo-pocalypse?

A recently published paper in the Journal of Information Technology suggests that the “artificial intelligence” story has been hijacked, but has become too good to be false. What is often called artificial intelligence today, the authors suggest, is just “statistics on data steroids”.

What we are seeing at the moment in terms of “AI” is physical robots, robotic process automation and cognitive automation (such as image identification).

Several influential studies have predicted that automation leads to job displacement, assuming that will be little job creation, that organisations and societies will be poorly prepared for the rapid spread of automation, and that human capabilities have little role to play in the future of work.

The paper links to recent research that challenge these predictions and assumptions, and forecast lower impacts on job losses. It suggests that too little consideration has been given to human qualities that are not easily automated or replaceable, especially in combination, and are likely to remain vital at work. 

The paper concludes that a “Robo-pocalypse” may be more likely to happen not because of AI but because we fail to deal with the massive shift in skills required over the next one or two decades.

The Economist has also just highlighted that earlier predictors about automation-induced job losses haven’t yet come to pass.

Fragility

Matt Stoller notes that the now unstuck Ever Given cargo ship has highlighted not just the risks of concentration of global trade supply chains, but the problem of too much focus on efficiency in many areas. 

“What is new isn’t the vulnerability of the Suez Canal as a chokepoint, it’s that we’ve intentionally created lots of other artificial chokepoints.” Matt Stoller 

As Andrew Curry points out, two of Stoller’s suggestion for re-designing globalisation seem too simplistic because they undercut things that do make globalisation function.

“Just in time” efficiency works until it doesn’t, exposing the importance of building in robustness (or that ephemeral term “resilience”) or what Nassim Taleb called “antifragile.”

The pandemic refocused attention on some of New Zealand’s already recognised fragilities – being at the end of long, complex trade routes, and the heavy reliance of international tourists, workers, and student.

At the end of his piece Stoller asked for other examples of disasters-in-waiting. One suggestion was a looming shortage of phosphate, largely dependent on supplies from the Western Sahara (and that’s a discussion NZ has had before).

Another suggestion was the risk of a large cargo ship sinking at the entrance to a critical harbour like Rotterdam. That would take much more than a week to solve, and disrupt the port and its land-based transport networks (and not to mention the environmental impacts).

Getting away from these fragile states isn’t quick or simple, and some aren’t issues that NZ has much control over. But that doesn’t mean that we shouldn’t be putting energy and effort into addressing them.

Fixes vs Values

In a long essay on sustainability in the Boston Review Duncan Kelly suggests that a focus on technological fixes, constitutional amendments, and some political arrangements (like forms of constitutional dictatorship) can keep us in the status quo rather than opening up new futures. This is because, he suggests, they pre-commit us to contemporary values. (Though not all contemporary values should be discarded)

This risk of “colonising the future” is being recognised in discussions about futures thinking and foresight.

Quite a lot of futures thinking can be about reviving older models of growth, economics and governance and reframing them in new forms.

So, ideas like Universal Basic Income can be seen as just a tweak to existing social welfare systems (though with fewer strings attached). 

Whereas, Rowan’s ideas about new public utilities, which connect broader questions of value to political and economic thinking, can open up new avenues that benefit individuals, communities and the state. 

Featured photo by Nathan Powers on Unsplash

Take, for example, the UK’s Food, Farming and Countryside Commission. Their recent report “Farming for change: Mapping a route to 2030” looks at what it calls “Agroecology”. It examines how feasible it is to produce enough food for the UK in 2050 (despite the report title) while reducing fertilisers, pesticides and greenhouse gas emissions, improving habitats, animal welfare and peoples’ diets, and ensuring small scale farms are viable.

Based on modelling they find that it is feasible, and still have some products to export.

New Zealand’s Pure Advantage promotion of regenerative farming is similar.

That’s bucolic and inspirational as far as it goes. Producing safe, nutritious, affordable and healthy food responsibly is essential. But regenerative agriculture looks to foundational changes, rather than transformative ones.

Its focus is on individual farms and producing traditional products, just more sustainably.

Moving from the farm system to the farming system

To become more broadly transformative requires generative as well as regenerative approaches.

Firstly, while the food system is often mentioned, most regenerative discussions are focused just on the traditional farm. Improving agricultural practices is essential, but more thought needs to be given to integration with emerging food production systems, such as urban farming, vertical farming, and “lab-based” foods. And also to aquaculture.

Aquaculture is having its own separate discussions (and here) about regenerative farming. That’s understandable because the environments and methods are quite different. However, if you want a transformed food production system all of these bits need to come together. Identify where the different parts can complement each other rather than just compete.

There is also the need to reimagine the logistics of processing and delivering food (and their waste cycles). Otherwise, it is like focussing on a shift from petrol-powered cars to electric vehicles without paying too much attention to the rest of the transportation system. 

The approaches being taken to reimagine the electricity system provide another example for thinking about integration of different food production components.  (See the Oxford Martin School’s synthesis report too).

Farming more than food

Secondly, the regenerative discussion is typically about food production and environmental restoration. Viewing farms as commodity producers and environmental service providers. In the future regenerative agriculture is likely to be a bottom line. Everyone will be doing it, so where are the added value and market opportunities going to come from?

There is the need to imagine farms as providing other services and products. For example, as part of the energy production system. Not just for their own use but for other communities. Electron farms as well as food farms. 

A bigger challenge is finding what higher value (non-food) products and materials can be produced. Some in the aquaculture sector are heading this way, but there is plenty of scope to consider how industrial ecology and other approaches could lead to novel medical, environmental and industrial applications for land-based agriculture too. 

That’s not easy or trivial. Huge amounts of investment and research have gone into that already with limited success so far. Biofuel companies have shifted to personal care products as a more profitable market.

The 21st Century has been touted by some as the century of biotechnology. Most of the action is currently in the lab, but we shouldn’t neglect looking for more opportunities in the field, or water.

In my 2015 “constant gardener” scenario I suggested that a key step to improve innovation is a multidisciplinary consultancy that acts as a connector across the range of interested stakeholders. That’s still valid today, and something that New Zealand could excel at.

A few years ago I also suggested the need to think bigger about the opportunities for Predator Free 2050. More imagination should be applied to the farming system too.

Creating a “pest free” country and a regenerative agricultural system are great, but we shouldn’t see them as the end points. We should be thinking about the other new opportunities that we create along the way, and what happens after we achieve those initial value-based goals.

Feature photo by Fallon Michael on Unsplash

Top “x” lists of technology developments, breakthroughs and trends aren’t hard to find. But how useful are they?

MIT’s “Breakthrough Technologies”

This time every year MIT’s Technology Review magazine produces a “10 breakthrough technologies” list. This showcases what it sees as the year’s most important technologies.

For 2021 their breakthroughs are:

1. mRNA vaccines

2. GPT-3 (a system that uses deep learning to produce human language-like text)

3. Tik Tok’s recommendation algorithm (which doesn’t just reflect what’s popular)

4. Lithium metal batteries

5. Data trusts (legal entities that collect and manage people’s personal data on their behalf)

6. Green hydrogen (produced using renewable energy)

7. Digital contact tracing

8. Hyper accurate positioning (going from metres down to centimetres or millimetres)

9. Remote everything

10. Multi-skilled AI (where the artificial intelligence is competent in at least two things, such as vision and audio)

A subscription is required to read more about each one. Previous years’ breakthroughs are accessible.

MIT doesn’t have clear criteria for what gets on the list. Some have already “broken through”, such as mRNA vaccines. But others, like GPT-3 still have some way to go.

Some aren’t even technologies, such as “data trusts”.

The articles on the technologies do often discuss some of their challenges, as well as recent progress. So, eclectic but informative.

CB Insights’ “Game changing technologies”

Firms like CB Insights also produce technology lists – “game changing technologies” in their corporate lingo. (Registration required for the report).

1. Intelligent tutoring

2. Cookie-busting ads

3. Creator platforms

4. Differential privacy

5. Protein fermentation

6. Own-a-piece of everything

7. Space-based R&D

8. Green hydrogen

9. Bioprinting

10. Ambient intelligence

Their "report" (more a set of slides) is also thin on methodology. One aspect CB Insights reports on is the amount of investment into the technology, another is news headlines. So they are often reporting on hype rather than feasibility.

But such lists generate interest and attention. Their usefulness, apart from signalling that the publisher is in the know, is in highlighting some recent developments and what is seen as “hot” or hyped at the moment.

But they can be distracting because they give undue attention to technological developments.

Five Forces of Disruption

Other lists do focus on a broader set of disrupters (real or imagined). The “Re_Set Forecast” report selected five forces of disruption that will, they confidently claim, bring about “real, positive and sustained change”:

1. Rise of the activist brand – where companies address (potential) customer values and societal impacts

2. Digital acceleration – widespread adoption of digital business models

3. Sustainability & biodiversity – the increasing influence of a “green agenda”

4. Workplace & culture – reflecting more agile and inclusive work environments, and a greater focus on wellness

5. Shifting strategies – to develop flexible long-term strategies that can deal with change

The report emphasises the opportunities for innovation that such disruptions provide. Another weakness is the overly confident prediction of what will be influential.

Deep Tech

We’ve had steam tech, information technology, biotech, nanotech, cleantech, and now there’s “Deep Tech”. The term has been around for some time but is now being used more widely. For example, Rocket Lab describes itself as a deep tech company.

At a simplistic level deep tech refers to where science meets advanced engineering. The hard stuff, moon shot-like programmes, not new dating apps or online game engines.

Those involved in it describe deep tech as being problem oriented rather than solution oriented.  It’s not one discipline or technology, deep techers claim. They design, build, test, learn, and repeat (this sounds like any IT company though).

A recent report on deep tech (registration required), from promoters of it, emphasise that it’s an approach not a technology.  What disrupts, they say, isn’t usually a technology, but the applications and business models. Still, its a technology-centric perspective.

It also seems like a label constructed, in part, to attract attention and funding (like previous technology descriptors).

You can't deny, though, that there are some very interesting deep tech companies out there - space-based services & exploration, synthetic biology, geoengineering.

Techo Chambers

As a recent article in The Atlantic points out, reports like the ones above often reflect in part a “mercantile approach” in foresight, where “… readers can not only prepare for what’s coming, but also profit from it.”

On the other hand, they also help raise awareness of particular developments and trends.

Too often though they seem to become “Techo chambers”. Technology as destiny, and people techno-dropping terms into discussions – VR, IoT, hydrogen, deep tech – without any meaningful explorations of how they could and couldn’t affect the now and near term.

More value comes from considering the consequences of these types of developments and disruptions, and the context within which they sit.

An example is Edison International’s “Reimagining the grid”, which considers how the power grid needs to evolve due to a variety of technological and non-technological factors. Here it’s less about prediction and more about preparing for changes.

Old tech and social systems

A different discussion of technologies can be found in an essay by Genevieve Bell called “Touching the future”. (Thanks to Andrew Curry’s “Just two things” newsletter for highlighting this).

After discussing the early days of artificial intelligence and post-war computing Genevieve reflects on technologies through the example of the Brewarrina Aboriginal Fish Traps in Australia. These river traps, built using stones, date back thousands of years.

She reflects that their importance is less about the traps as a technology and more about the system the traps helped create, and are embedded in.

When thinking about technologies we need, she suggests, to think about the cultural and ecological elements too. Along with the people and the places involved, and the ideas that build and sustain the system.

This mirrors concepts in Mātauranga Māori, highlighting that more recent western technological developments can separate rather than connect people from their environment and society.

“The technical, cultural and ecological elements cement the significance of this place, not only as a heritage site but as a knowledge base on which contemporary systems could be built. Ideas about sustainability; ideas about systems that are decades or centuries in the making; ideas about systems that endure and systems that are built explicitly to endure. Systems that are built to ensure the continuities of culture feel like the kind of systems that we might want to be investing in now.” Genevieve Bell

So, read the lists of technologies, but think about the systems that they sit within. Involve different perspectives and ask different questions about the futures we need.

Featured image: ThisisEngineering RAEng on Unsplash

Yesterday’s Gone

A Canadian report from the Brookfield Institute identifies eight megatrends that may affect employment by 2030. It notes that the pandemic has accelerated some existing trends and shifted the importance or impact of others.

The eights trends they highlight are:

1. An increasing shift from in-person to virtual interactions and activities

2. Greater questioning of capitalism

3. Pervasiveness of digital technologies, and the growth in biotech and space technologies

4. Growing recognition of a climate crisis

5. Movement toward racially just and inclusive futures

6. Re-evaluations of work-life balances and wellbeing

7. Geopolitical and demographic power shifts

8. Developed countries’ reliance on immigration

8 “core truths” about the future of work?

A report from the commercial real estate company CBRE identifies what it calls “8 core truths” about the future of work. These are derived from surveys of employers and employees across several countries. The focus is on office workers rather than on a range of other types of work.

CBRE found that only 28% of employees desire fully remote working, with most preferring a mix of home & office-based working.

The “core truths” relate to the themes of talent, location, occupancy, and design & experience:

1. Increased desire for choice and flexibility by employees

2. Changed workforce policies to enable hybrid workstyles

3. Decentralised office strategies

4. Worker migration to lower cost areas with better quality of life

5. Embracing planning amid uncertainty

6. More flexible workspaces

7. Reimagined workplaces that enhance wellbeing and productivity

8. Use of digital technologies in ways that improve work environment and employee experiences

“Core truths” is marketing spin, implying much more certainty than is warranted. Whether some of the current desires will continue post-pandemic is uncertain. However, it is reasonable to assume that there has been a shift in expectations by office workers. This builds on the pre-pandemic interest in improving work-life balance, though, for example, four-day working weeks.

What the report doesn’t assess is how desires match realities. For example, for workers with families and strong social connections uprooting to move elsewhere while desirable in a work sense may not be feasible due to other factors.

Geopolitics on a chip

The investment analysis firm TS Lombard highlight that Taiwan and South Korea are becoming the “new OPEC”. They are the leaders in semiconductor production. While China and the US are racing to improve their own chip manufacturing capabilities, Taiwan and South Korea still dominate. The two countries account for 83% of global processor chip production and 70% of memory chip output. This, the blog post states, means that China can’t exert too much economic pressure on Taiwan, though military threats remain an option.

The “Paris effect”

A report from SYSTEMIQ discusses the impacts that the 2015 Paris Agreement on climate change is having on shifts towards lower carbon economies. It notes that while there have been rapid and encouraging changes, and the appetite by firms and governments for further reductions is growing, there is still a lot to do, particularly beyond the power generation sector.

Their illustration of past, present and future low carbon solutions is useful in showing what else still needs to be done.

Reducing artificial fertilisers

Nitrates and their environmental and health impacts are currently topical. Pivot Bio is using bacteria that produce nitrogenase, which converts atmospheric nitrogen into ammonia, as a replacement for artificial fertilisers for crops. They already have several hundred thousand acres of maize growing with their product.

The method does not involve genetic modification, but how they enable the bacteria to start producing nitrogenase is proprietary.

Several other companies are also seeking to develop sustainable fertilisers.

Too many solar panels can be bad

Colonising deserts with solar panels sounds like a good idea. Lots of sun, few other uses for the land, cheap clean energy. But a new modelling study indicates that very large scale solar farms in the Sahara (more than 20% of the area) could change the climate in other regions. This is because the solar panels don’t distribute the heat in the same way as the sand, leading to an increase in local temperature, which in turn affects sea and atmospheric conditions that can disrupt rainfall elsewhere.

A useful warning that illustrates that any very large scale project needs to be carefully scrutinised no matter what potential benefits are promised.

The future of cooling

Staying with the temperature and energy topic, the International Energy Association says that nearly 20% of electricity use in buildings goes to running air conditioners and fans.

Demand for cooling is rising rapidly, and they predict that by 2050 around 2/3 of the world’s households may have an air conditioner, with about half of these being in China, India and Indonesia.

Reducing the need to cool buildings will have a significant impact on energy requirements, and carbon emissions.

Arctic ocean open for business year round now

A cargo ship has travelled through the Northern Sea Route in the Arctic ocean. It is normally impassable for commercial ships during winter, but not this year.  Arctic may now be open to shipping year round, signalling not only the changing climate, but also risking other environmental damages due to increased shipping and commercial activities.

AI’s lacklustre contribution to the pandemic

Using artificial intelligence in health care is hard. Remember IBM Watson and the company’s hype about AI revolutionising health care? Watson was discharged from health care services a few years ago, and IBM now seems to be trying to sell it completely.

Similarly, despite attracting huge amounts of funding, other health care-related artificial intelligence applications haven’t had a big impact in the Covid-19 pandemic, as a commentary in Politico points out. AI has been better at helping health care workers identify which Covid-19 patients to focus on, rather than being a good diagnostician.

One area where AI has performed relatively well is in identifying potential treatments (through assessing information on large numbers of existing compounds). However, only two treatments – dexamethasone and remdesivir – have so far received FDA approval, and these didn’t require AI to identify.

It’s not that AI in health care is inevitably hopeless, it’s more that health care is complex and not just about finding correlations. A review in The Lancet found that many diagnostic applications have reporting and analytical biases. Greater transparency about the algorithms, more collaboration, and larger & better designed tests are required.

Featured image: Javier Allegue Barros on Unsplash

The short answer is no. A slightly longer response is that's not the most important question to ask about the future of science.

A tool, not a solution

DeepMind’s success in determining quite accurate 3D protein structures in a competition made headlines last week. Rightly so because it is an impressive achievement.

The company is understandably gung ho on the future scientific possibilities

“The progress announced today gives us further confidence that AI will become one of humanity’s most useful tools in expanding the frontiers of scientific knowledge, and we’re looking forward to the many years of hard work and discovery ahead!”

It is easy, though, to get carried away with hype. Solving a protein’s structure is just one step (often a very important one) in understanding functions and interactions, and developing drugs.

The protein folding problem also hasn’t been “solved” by an algorithm. AlphaFold, and all other computational methods, predict. Protein scientists need to confirm structures experimentally.

As Vishal Gulati points out,  just knowing more protein structures doesn’t lead to more drugs. You need to find structures that can be targeted by drugs.

But better predictions of protein structures will help with the study of protein-protein interactions and misfolded proteins, and inform the design of novel (or at least not yet identified) proteins.

Be cautious about AI hype

Some applications of AI haven’t ended well. IBM’s Watson healthcare system was quietly placed on sick leave in 2019 after over promising and under delivering.

Gary Marcus and Jeffrey Funk have also noted other examples where results and expectations about AI haven’t stood up to scrutiny. Or, after the big press release, nothing seems to happen.

Progress is often more gradual, or not progress at all.

You need to have a critical mindset. Technology Review suggested 5 questions to ask about AI news:

1. What is the problem that needs to be solved?

2. How is the company, or lab, approaching that problem with AI methods?

3. How do they source the training data?

4. Do they have processes for auditing the products and results?

5. Should they be using AI methods to solve this problem?

DeepMind's AlphaFold gives good answers to these questions.

Additional questions I include:

1. Do they explain their method(s) clearly for a more general audience?

2. Do they discuss limitations and potential biases?

Over-estimating short term developments and underestimating long term progress is as common to AI as to many other new technologies. So you can't assume current successes and failures describe the future.

It’s not all hype

There are many examples of artificial intelligence methods being used in scientific research, and applications are increasing rapidly. Often without much fanfare.

Last year The Royal Society produced a report highlighting the potential of AI in research. It provided examples of the roles it can play as an enabler of research and development in many fields.

Applications are being used to identify drug combinations that can inhibit cancer cells, create artificial proteins, and categorise galaxies.

AI isn’t just in the lab either. Conservation biology is also an adopter, as described a recent Nature article.  An example being its use to see if it can detect elephant poachers.

New Zealand’s Cacophony Project uses AI to detect predators, and NEC and Victoria university are using machine learning to identify bird calls.

AI methods are being used in a variety of ways in Covid-19 research. For example, to identify genes interacting with SARS-CoV-2, or existing drugs that may be useful, analysis of the research papers, or to process medical images.

A year ago, the use of AI would probably have been in the paper’s title. Now they are just part of the methodology section. That is a real indicator of progress.

Another article in Nature suggests that what is really going to help advance AI in research is better collaboration and transparency. Not sharing data sets and models creates barriers to progress rather than bridges. That's not just an issue with AI. Many areas of science would benefit from more collaboration and sharing, as the pandemic has illustrated.

The most interesting question that The Royal Society posed in its report was:

“Is there a rigorous way to incorporate existing theory/ knowledge into a machine learning algorithm, to constrain the outcomes to scientifically plausible solutions?"

This highlights that we often need to adapt new tools to suit the tasks rather than adopt them without too much thought. So it's not always about how will AI shape science, but how will, or should, research shape AI applications.

Don’t consider AI in isolation

As I flagged at the start of this post, it's unhelpful to focus too much on the role of artificial intelligence. That's "singularity thinking". Yes, AI is likely to become increasingly important in many areas of science.

In reality, there are many things shaping the future of science. Such as automation more generally. Arup produced a report in 2018 (and lightly updated a couple of months ago) looking at the future of labs. It highlights not just automation, but also some of the social, political and financial factors influencing research over the coming decade.

An increasingly important aspect of science is how different knowledge systems are woven into together. A Guide to Vision Mātauranga highlights the experiences of Māori researchers in the New Zealand science system, the challenges and the opportunities for valuing Mātauranga Māori (Māori knowledge systems) alongside Western science. The Building cultural perspectives report from Superu describes how different streams of knowledge can both work alongside each other and work together.

The pandemic may also nudge researchers, and research organisations, to change how science is conducted as well. In good ways and not so good.

As DeepMind's AlphaFold has shown, AI can be good at helping solve some types of puzzles. But science is about investigating mysteries too. This is where there isn't one answer or solution, or when the answer naturally emerges from gathering all the facts.

If it is to continue to help us better understand the world, and do more good and less harm, science will need to become more socially intelligent - responsive to social expectations and needs - rather than just algorithmically more sophisticated.

Update 10 Dec: A paper just out in Nature describes natural language processing programs that analyse and summarise thousands of scientific papers. The next goal is to try and get programs to synthesise information from different papers.

Featured image: Photo by Mathew Schwartz on Unsplash, transformed using Deep Dream

Writing in the magazine Foreign Affairs Scoblic & Tetlock highlight that the US spends over a trillion dollars a year on national security but is continually being surprised by events. This they put down to taking the wrong approach in thinking about the future.

The tendency (not just in the US) is to extrapolate from (and so plan for) past events, and/or focus too much on some issues, and dismiss others too quickly.

Making better predictions 

Scoblic & Tetlock propose combining two approaches to be better prepared for the future. The first, scenario planning, often considers futures in terms of plausibility rather than probabilities. The second, probabilistic forecasting (in which Tetlock’s research on “superforecasters” has become well known ), tries to calculate the odds of possible specific short-term outcomes.

They note that forecasters, policy makers, and strategists often view scenarios as vague, possibly misleading, and failing to identify courses of action. On the other hand, policy makers can view the questions that probabilistic forecasters focus on as exceedingly narrow, and so also don’t provide enough information to inform decision-making.

They take an American-centric view of scenario planning. In their description rigorous scenario planning exercises involve identifying key uncertainties and then imagining how different combinations could yield situations that are different from what extrapolation of the present would suggest. This is the classic business consultant scenario approach.

I think that is too simplistic, and old fashioned. As Pierre Wack pointed out decades ago (in that bastion of American centrism the Harvard Business Review)

“… simply combining obvious uncertainties did not help much with decision making. That exercise brought us only to a set of obvious, simplistic, and conflicting strategic solutions.”

Such scenario matrices give the false impression that the uncertainties, once identified, can be managed. Wack noted that these types of scenarios are only a stepping stone to developing more useful ones that aid decision making.

Scoblic & Tetlock do acknowledge that the role of scenarios is to be provocative not predictive

“… challenging planners’ assumptions, shaking up their mental models of how the world works, and giving them the cognitive flexibility to better sense, shape, and adapt to the emerging future.”

Still, if you develop a set of  simple scenarios you may not be challenging assumptions as much as you need to.

The power of a good set of questions

They suggest that once these scenarios have been developed then sets of questions need to be crafted that give early, forecastable indications of which (if any) scenario is likely to emerge - signposts for what is emerging.

This seems fairly obvious. It is already adopted to some extent in European and Asian foresight work, and by some US practitioners.

But Scoblic & Tetlock's approach is also anachronistic. They say the scenarios are provocative not predictive, but then assume they are predictive by developing questions to test them.

However, their emphasis on the need for precise questions is valuable. They call these “diagnostic questions”, which they suggest help identify trajectories.

The questions should, they stress, not allow wiggle room. They must pass a “clairvoyance test” – where a genuine clairvoyant (if one existed) would be able to answer it without having to ask for clarification.

“Will we ‘bounce back’ from the pandemic?” would not pass the test. “Will revenue from international tourism be at least 75% of January 2019 levels by January 2022?” is.

A diverse set of questions is also required to ensure that the most information about an emerging future is gathered and avoid giving too much weight to a potentially unimportant signal or signpost. Asking diagnostic and diverse questions also help decrease confirmation biases.

Puzzles vs mysteries

Scoblic and Tetlock's approach has superficial attractiveness, but several weaknesses.

Some quick and simple scenarios with some focused questions can provide an illusion of rigour and insight.  The plausible range of futures isn't covered by four scenarios based on uncertainty matrices. If none of the scenarios seem to be developing then you are back where you started.

I also think they may be misled by being focused on events and questions that are predictive – will?, what?, when?, how?  In their portrayal there is little scope for  questions that develop an understanding about what’s really going on – “Why is the situation emerging in this way?"  

Scoblic and Tetlock seem to view futures as a puzzle, like a jigsaw, where the picture emerges once you have enough pieces (answers to diagnostic questions). The CIA pointed out, in 1999, that this isn’t how such analyses usually work. Analysts, the CIA claim, usually start with a picture and select the pieces that fit. One piece can often fit several different puzzles.

Scoblic and Tetlock’s diverse question sets are intended to avoid this. But they are probably daunting to compile if you only have descriptions of change not hypotheses.

The CIA view intelligence analysis more like a medical diagnosis (or a scientific hypothesis). Indicators (symptoms) of what is happening are collected, then knowledge of how the body works is used to develop hypotheses that might explain the observations. Tests or collection of additional information is used to evaluate the hypotheses, then a diagnosis is made. This can be more “mystery” than “puzzle.”

While there are similarities between the two approaches, Scoblic & Tetlock's already has a narrow range of "solutions" in mind, that will likely influence what the questions are.

It is worth noting that the CIA don’t have a stellar foresight record. Tetlock’s own work found that CIA analysts weren’t that good in probabilistic forecasting.

Improve mental models not metaphorical balls

That CIA chapter, called Do you really need more information? is particularly helpful for futurists or forecasters. It points out how few variables people use to make informed judgements. In experiments (some involving horse betting) they found that providing additional information didn’t tend to improve accuracy, but it did make the analyst more confident, and sometimes overconfident. This is similar to some of Tetlock’s superforecasting findings.

But the CIA discuses in much more depth mental models, tools for thinking, and cognitive biases. Lack of information was not the main obstacle to accurate intelligence analysis. The chapter concludes that

“efforts should focus on improving the mental models employed by analysts to interpret information and the analytical processes used to evaluate it. “

It acknowledges that this is difficult, but would have greater impact than improving collection of information. How we see (that is, what we pay attention to and how we interpret it) is more important than what we see.

Tetlock’s work with the Intelligence Advanced Research Projects Activity was called the “Good judgement project”, so it’s surprising that Scoblic and Tetlock mention mental models only in passing. Mental models are the frame, or window, through which we perceive and make sense of things.

They called their article “A better crystal ball” (or at least the editor made it the title), reflecting a need for certainty, rather than for a better way of looking at and thinking about the world. A crystal ball isn’t very good if you are looking at it through an old, cracked window.

Featured photo by Abby Pena on Unsplash

By Robert Hickson • 11/09/2020 

Published on SciBlogs. Written for the Science Media Centre

Five things we’ve learnt

1. We know where the virus ultimately came from

We know that the virus originally came from bats, and most probably a species of horseshoe bat in South East Asia. However, the spike protein in SARS-CoV-2, which allows the virus to attach to cells and infect them, is more different than those from horseshoe bat sequences. While the sequence of this protein is more similar to one in a coronavirus from pangolins, researchers now think this is because the bat sequence has recombined, rather than pangolin being an intermediate host. However, this has not yet been verified.

Some epidemiologists think that a less pathogenic version of the virus may have been circulating in people from Vietnam, Laos and/or Myanmar before it appeared in Wuhan, China. This too, hasn’t been proven yet.

Thousands of genomes of the virus have now been sequenced. Analysis of these has helped to monitor how the virus is evolving (not much), and how the pandemic has spread around the world and within communities. These are illustrated in interactive graphics on the NextStrain website.

2. We know a lot about how the virus spreads

SARS-CoV-2 appears to be slightly more infectious than the flu, but less easily spread than the two other recent coronaviruses that came from animals (SARS and MERS).

• It is mainly spread by droplets and aerosols

The virus infects the respiratory system, so it is spread mainly by coughing, sneezing and talking. Singing can also spread infections. The virus can survive on surfaces for a few days, but the frequency of this route of transmission is unclear.

• Closed spaces, crowded spaces and close contact favour infection

The virus is known to be most easily spread indoors where people are in close contact. Most cases of transmission appear related to infections within households, and in healthcare facilities where there are poor infection control measures. Most clusters of transmission outside of households are associated with “3Cs”: closed spaces with poor ventilation, crowded places, and close-contact settings. Examples include churches, bars and cruise ships.

• Symptoms take about a week to develop, but people can spread the virus before then

Symptoms typically appear about one week after infection and last generally for another two weeks. The virus appears to be spread mostly from 2-3 days before symptoms are noticed and up to one week after symptoms appear. A review of many studies estimated that 48% to 62% of transmission may occur before people show symptoms.

• Some people may not show symptoms, but can still spread the virus

Some people do not show symptoms after infection (or don’t notice mild symptoms), but can still pass on the virus. It is unclear how many people fall into this “asymptomatic” category since it varies by setting, and depends on having good testing. Estimates vary from 6% to 81% (on a cruise ship), with the WHO estimating a general asymptomatic level of 16%, the Centres for Disease Control and Prevention estimating 40% in the US, and another study considering 40-45% may show no symptoms. More systematic testing makes the asymptomatic infection estimates more accurate.

3. We know a lot about how the virus affects the body, but are still learning too

The virus is different from the flu and SARS due to the broad range of symptoms and conditions that it can cause.

An international review found that the most common symptoms in those who go to hospital with Covid-19 are fever (70%-90%), dry cough (60%-86%), shortness of breath (53%-80%), fatigue (38%), muscle pains (15%-44%), nausea or diarrhea (15%-39%), and general weakness (25%). Loss of smell may be the only symptom in about 3% of infected individuals.

While the virus commonly causes respiratory complications, it can also lead to a range of other injuries and diseases. It is less certain whether the virus directly causes all of these impacts, or whether they may be due to an overstimulated immune response. An unbalanced immune response is associated with more severe complications.

About 5% of patients with severe symptoms can require intensive care, and more than 75% of hospitalised patients have needed oxygen.

Those without symptoms may also still show tissue damage.

4. We know who is most at risk

Those most at risk of developing severe conditions, or dying, are men, older people, those who are obese or overweight, those who are socially deprived, and those from non-white ethnic groups (in Western countries). Patients older than 80 can be at least 20 times more likely to die from Covid-19 than those in their 50s. The elderly may be at more risk due to a variety of factors, such as weaker immune responses, but these factors are still being studied. The socially deprived are usually less likely to get medical help earlier, and may have lower-quality health care.

However, young people and those without pre-existing health conditions can sometimes become severely ill and can die from Covid-19.

5. We know some effective treatments and interventions

Regular handwashing and avoiding close contact with others are known to reduce risks. Wearing well-fitted masks also helps reduce the chance of spreading infection, though by how much is less certain. Avoiding large gatherings and confined spaces, particularly where there is singing or shouting is also known to be effective.

Lying patients on their stomachs, providing extra oxygen, and using ventilators are effective treatments for those who have difficulty breathing due to Covid-19. Hospitals are improving their care as they treat more people, so patient outcomes are improving.

The antiviral drug remdesivir has shown promise in treating patients with lung infections, if it is used in combination with other drugs. One study has shown that it shortens recovery time. However, so far it hasn’t been shown to reduce deaths.

The steroid dexamethasone, and some other corticosteroids, have been shown to reduce deaths amongst those with severe disease, such as those on ventilators. The effects of these steroids on people with less severe conditions is still being investigated.

Five things we still don’t know

1. Why do people respond differently?

While we know some factors that influence the risk of becoming very sick, we often do not know why that is. For example, why do older men appear to be at more risk than older women? It is also unknown why some people don’t show any symptoms, although this is seen for other coronavirus infections too. Some infected people, called “long haulers”, take months to recover, and it is not known why. It is likely that a combination of factors, such as genetics, behaviours, and the individuality of people’s immune systems, play a role.

2. Do people develop immunity, and how long could it last?

People do develop antibodies and cellular immune responses after being infected. However, we don’t yet know if this prevents further infections, or reduces the severity of the infection. Studies have shown that people can get re-infected with other coronaviruses within a year, and cases of re-infection of SARS-CoV-2 are emerging, so there may not be any long-lasting immunity to Covid-19.

3. How well will a vaccine work?

There are over 300 possible vaccines being tested. Some vaccines have begun phase 3 clinical trials, which will indicate how effective they may be. Results are likely to start becoming available before the end of the year. Vaccines may not provide long term immunity. They could moderate symptoms rather than prevent infection.

However, combined with other treatments even an imperfect vaccine can help slow or eliminate the spread and reduce the impacts of the virus.

Producing and distributing vaccines is complicated and takes time, so even if/after vaccines are approved most people may have to wait months (if not longer) before they can be vaccinated.

4. Will Covid-19 become more, or less, dangerous?

One research paper suggested that the virus was mutating to become more infectious. However, this hasn’t been proven. Neither is there evidence to show that the virus is causing more severe disease as it spreads, or is becoming less infectious.

Viruses do mutate, but the mutation rate for SARS-CoV-2 – about two mutations a month, or every second or third transmission – is similar to other RNA viruses like influenza.

5. What will the next pandemic be?

There are thousands of viruses in animals with the potential to infect people, but we are not studying them systematically to identify the main risks.

But we do know what needs to be done to reduce the likelihood of further pandemics:

• Reduce habitat destruction that increases the risk of contact between humans and wild animals,

• Eliminate markets for wild animals,

• Develop epidemic and pandemic plans (and test them),

• Ensure there are good stockpiles of personal protective equipment,

• Improve surveillance for new diseases, and

• Respond quickly to outbreaks.

International scientific and political collaboration and coordination are also essential. The Covid-19 pandemic has shown that good science and good governance are essential to prevent and fight pandemics.

Robert has been tracking COVID-19 research on behalf of the Science Media Centre – sign up for his weekly updates.

There have been several hyped technological developments in the last few weeks. Nothing unusual in that, but they provide useful examples of the need to adopt a critical mindset when considering the significance of developments and trends.

Some futurists seem to just scrape the headlines for content without questioning the reports. That just feeds an uncritical futures frenzy.

Others enjoy debunking them. But there is the risk of being too dismissive and overlooking the broader significance of developments, even if a particular event doesn’t actually show what it claims. 

Too good to be true?

First up, reports of a cheap “game changing” battery, that lasts for hundreds of years, could power just about anything, and gets rid of nuclear waste. What’s not to like?

A company called NDB – Nano Diamond Battery – is promoting a self-charging battery that encases in diamond carbon-14 from nuclear power plant waste. They are in the prototype stage and have been getting some positive media attention. 

The obvious first question is “does it actually work?”

A YouTube video takes apart the claims the company makes. The video is overly long and repetitious but notes that similar batteries – or more accurately energy harvesters – already exist. These produce only very small amounts (microWatts) of energy. The video points out that the company doesn’t provide many technical details and seem to have removed some earlier, more revealing, information that helps assess its claims.

Seems more like simple marketing, rather than technological revolution at this stage. The nano diamond battery sits in the hype space. Something to keep an eye on but, like C-14, treat with caution.

However, things like NDB can have value by alerting you to the emergence of different approaches to challenges. There is a lot of interesting and exciting energy-related technological development going on. You just have to be discerning about what is being promoted.

Neuroscience is harder than rocket science

Elon Musk’s recent demonstration of Neuralink’s “brain implant”, involving three little pigs, is closer to the “plausible tech” space.

Musk showed that the implant, with the help of machine learning, could predict an animal’s leg movements. Unlike his previous electric vehicle and rocket events, it relied more on tell than show. Though he did have a big robot on stage. 

The critical question to ask here is what is the gap between the demonstration and medical (or entertainment) uses?

Mostly the demonstration seemed to be a combination of marketing and recruitment.  Musk promoted at one point the future potential medical applications, but then drifted towards such devices being used for playing video games, summoning your Tesla, or helping keep up with artificial intelligence. 

“Neuroscience theatre” according to Technology Review. “Solid engineering, but mediocre neuroscience” was the diagnosis of a neuroscientist. 

Neuralink, according to some reports, appears to be in some trouble, with several of the original neuroscientists leaving, and concerns over an internal culture characterized by hasty timelines and a “move fast and break things” attitude. Not something that you’d want from a medical device company. 

Brain machine interfaces have been developed over the last 50 years. (Think cochlear implants). Other companies and university labs have developed similar, or better, devices than Neuralink’s, so it pays to also consider some of the less flashy developments in academia. 

Unlike NDB, Neuralink has shown proof of concept. But there is still a gap between the underlying science and the technology. We don’t know yet what the feasible and acceptable uses of brain implants will be, or when they’ll be more generally available. Or what the problems will be. 

Still, it seems reasonable to consider that the future will have more devices that connect to our nervous systems. Now is a good time to think about the ethical and regulatory frameworks that we’ll need.

Top Gun AI

Recently in DARPA’s AlphaDogfight trials one of the artificial systems was able to beat an F-16 pilot five-nil in a virtual fight. 

Some commentators immediately jumped to a future of autonomous warfare, and maybe Skynet.

Others, usually aviators, focused on the artificiality of the trial, pointing out human skills that are also needed in aerial combat.

Jumping to an extreme state or highlighting the limitations are common responses to new developments. But the the application may follow a different path.

This is reflected in analysis from a Navy pilot. His view is that it isn’t about replacing human pilots soon, but a signal of how there will be increasing human-machine “symbiosis” in combat (and non-combat) situations. There already is a lot of automation in flying and warfare, so use of more artificial intelligence in other rule-based operations is to be expected, if not welcomed.

The important question to consider in these cases is will the technology augment rather than replace people.

A related question for this particular case is do we have good safeguards to cover both situations.

The US has policy that allows for the use of “lethal autonomous weapons systems”, though none appear operational yet. The policy requires that such systems “allow commanders and operators to exercise appropriate levels of human judgment over the use of force.” What “appropriate levels of human judgement” means allows for plenty of wriggle room.

It would be great to have some human-machine collaborations that stop us getting to the point of shooting at each other in the first place.

But will it really fly?

I wrote about flying cars in 2017, and several other companies have entered the air space since then. A Japanese company, SkyDrive, has joined the ranks of those who have test flown a flying car. They say they expect to have full autonomous flying by 2030. These things are often 10 years away.

However, flying cars have to contend not only with the laws of physics, but the laws of economics. Earlier this year Kitty Hawk’s Flyer was grounded because it “could not find a path to a viable business.” The company, though, isn’t giving up on flying vehicles. It is concentrating on a longer range flying taxi it calls Heaviside.

Like every other technology, flying vehicles sit within a bigger system. Futurists need to think about those other factors too to make sense of the significance of individual developments.

A recent paper identified what it called “seven domains of interest” in relation to developing and regulating flying cars: 

• Safety

• Training

• Infrastructure

• Environment

• Logistics & Sustainability

• Cybersecurity, and 

• Human Factors

Progress in all of these are still poorly developed, so the operational feasibility of flying cars still has a lot of uncertainty. Even for ground-based vehicles semi-autonomous or “active driver assistance” capabilities, despite often years of development,  “do not perform consistently, especially in real-word scenarios.” That will change but, as I wrote previously, may not be as quickly as software developers expect.

Flying cars will come, but as an important transport option or a minor one isn’t easy to tell yet.

Beyond the coolness and science-fiction-becomes-fact desire, advocates of flying cars emphasise speed, efficiency and independence. Much like early car and plane developers.

As PR man Rory Sutherland pointed out, perspective is everything. A more valued social objective would be to put more effort into making existing public transport options more appealing. For example, by improving their efficiency, comfort, safety, accessibility and affordability.

So, in addition to considering what else needs to happen, good futures thinkers need to look at what the technologies may affect or inhibit.

Tips for technology thinkers

So, when reading those technology headlines consider:

1. Have they proven what they claim?

2. What still needs to happen?

3. What are more likely ways it will be used?

4. What else may it affect?

Featured photo by Atul Vinayak on Unsplash

An article in the EETimes suggests that advances in autonomous vehicles are not moving as quickly as expected because those working on them have confused complicated problems with complex ones. 

Engineering can only take you so far in complex worlds. Complicated systems tend to have fairly predictable inputs, processes and outputs. Complex systems (like city streets) not so. Complicated systems are often designed, while complex ones are more organic.

The article notes that some of the autonomous vehicle companies are directing their focus to more predictable operating environments such as retirement villages, campuses, and long-distance trucking. These are less complex than navigating chaotic (to algorithms at least) urban streets.

It feels like we are confusing the complicated and the complex in other areas too.

The allure of the complicated

An article in Nautilus starts off well highlighting the risk, mid- to post-pandemic, of focusing on the wrong things; not seeing the collapse of multiple complex systems. It tends to drift away from that at the end (as you tend to do when encountering complexity), but it is a point well made. The introductory paragraph (while not an example of complexity) of looking at where returning RAF planes were shot is an example that I’ve kept in mind for many years.

In many recent discussions about the pandemic and what comes next government and private sector attention seems to focus on where the damage is, and respond by proposing structural changes and building stuff. That’s the complicated stuff. It’s what they know and what they can control. 

As I noted in a previous post, people are eager to demonstrate that they are acting. Some of the responses are necessary. But we can’t just focus on the “shovel ready” complicated activities.

Yes, there are discussions about changing systems – more regenerative farming, lower carbon energy systems, different economic policies and systems. They aren’t so easily or quickly implemented. But there is also the risk that we bring complicated perspectives to complex issues.

Politicians want, and are encouraged, to come up with (or fund) “solutions.” That can work well for complicated issues.

A different mindset needed for complex issues

Will Allen, a kiwi, has noted that for complex issues there is the need to avoid thinking about “a change” that will fix the system, and instead consider what the key points of leverage are that will improve the system. 

Allen also highlighted earlier observations made by Irene Ng that complicated outcomes can be determined, but complex outcomes are enabled. And, complicated systems can be specified, but we can only intervene in complex ones. 

Enabling and leverage were also identified as critical in an excellent 2002 report on complex systems (focused on healthcare) by Glouberman & Zimmerman. They point out that the types of questions you ask about complicated systems are different from those for complex systems:

“Questions that assume a complicated problem tend to be laden with constraints of limited resources, lack of leadership, trade-offs, external control of the future and individual rights. They paint a picture of an intractable problem where compromises are necessary but not likely to satisfy many. The complex questions have a more optimistic tone as they look for existing resources.”

Energy systems as complex rather than complicated

For example, consider the recent proposal in New Zealand to examine pumped storage to help ensure a 100% renewable energy grid. 

This, in the framing of Glouberman & Zimmerman, is a partial answer to a question assuming a complicated problem:

“What are the structures that we need to make our energy system sustainable?”

Rod Oram, on his Tuesday Nine to Noon radio spot, commented that the storage issue is important, but that pumped storage may not be the best solution. Not least because technology is developing quickly. He suggested that battery storage may become more viable. But big banks of batteries are already being questioned in the UK.

However, in the face of rapid technological changes, alongside other social, economic and environmental changes, the energy system isn’t a complicated problem.

Seeing the energy system as a complex issue leads to questions like

“How do we build on current structures and practices to improve sustainable energy use and generation?”

They take a broader look at the issue, such as the practices and uses, not just generation, storage and transmission.

Oram noted that political parties seem to be taking a piecemeal approach to energy, focusing on projects or plans, and not picking up on some of the good thinking in the Productivity Commission’s 2018 Low-emissions economy report.  Even the Green Party’s clean energy plan seems to view it as a complicated rather than complex issue.

Enabling the future

The most important observation I think Oram made is that the main political parties still have what I call a Field of Dreams “build it and they will come” mindset. 

They aren’t thinking about inter-generational governance and operation of the big structures they propose. “We’ll build more dams, geothermal plants, or wind farms and our job is done”-type thinking.

This is something that isn’t commonly picked up by futures thinkers. They tend to focus on new trends and developments, and less about governing for the long-term. There are, of course exceptions, like Jonathan Boston’s Governing for the future.

Political parties also don’t seem to be thinking as much about how they, alongside the private sector, can help enable rather the determine change.

That seems just like patching up the holes we can see and not thinking too hard about the ones we don’t.

This isn’t limited to the energy sector. As the Nautilus article notes, there is damage to multiple systems that we are not looking at, or for.

Real “transformation” won’t come from just more infrastructure and other projects. It will come when we perceive the challenges differently, and change the questions we ask.

Photo by Kacper Chrzanowski on Unsplash