Esta es una propuesta abierta y viva de Dark Matter Labs, escrita para invitar a la colaboración, la crítica y la interrogación colectiva.

Quienes somos: Dark Matter Labs es una organización sin ánimo de lucro centrada en abordar las estructuras invisibles — la materia oscura — que determinan nuestros retos globales en gran medida: los sistemas de valores, económicos y financieros, los modelos de colaboración y gobernanza, la contratación, la normativa y la regulación.

Madrid está de moda

Lo dicen Forbes, The Washington Post, o Time Out. Lo evidencian los más de 11 millones de visitantes internacionales de 2025, que gastaron casi 18.000 millones de euros en la ciudad, y la creciente presencia de nómadas digitales, fondos de capital riesgo, multinacionales tecnológicas o family offices latinoamericanos. La región concentra el 67% de la inversión extranjera en España y dos de cada tres empresas globales en España tienen su sede aquí. Su PIB per cápita es un 78% superior a la media española y, desde 2011, la Comunidad de Madrid lidera la esperanza de vida en la Unión Europea. Cada año, más de 120.000 personas convierten Madrid en su hogar y, en 2025, la ciudad superó por primera vez los 3,5 millones de habitantes. Tensiones inmobiliarias y crisis de identidad aparte, Madrid vive un momento de éxito económico y expansión.

Un futuro ardiente

Sin embargo, como la rana en el agua que sube lentamente de temperatura, la ciudad afronta un reto que aumenta cada año, de forma gradual. A mediados de siglo, se espera que las olas de calor se dupliquen y que haya pocas noches de verano por debajo de los 20 °C. A finales de siglo, habrá casi 80 días de ola de calor al año. Los famosos tres meses de infierno del dicho, llevados al extremo. Madrid, históricamente un lugar de veranos cálidos, se enfrenta a un futuro marcado por el calor extremo y, precisamente porque el calor no es nuevo y sus efectos son difusos, resulta más difícil percibir con claridad sus impactos y movilizarse para remediarlos.

Además, el calor no solo afecta directamente a la salud, a los comportamientos delictivos y a las agresiones, incluida la violencia de género, sino que también desencadena impactos en cascada, en un efecto dominó que atraviesa la ciudad. Trabajadores que llevan una semana sin dormir bien se concentran menos y cometen más errores, lo que aumenta el riesgo de accidentes laborales y de tráfico. Una red sobrecargada deja sin suministro a oficinas, industrias, hospitales y colegios. Empresas que quieren evitar riesgos optan por reubicar sus sedes. La pérdida de empleo y el deterioro de la calidad de vida aumentan el descontento social y dificultan la atracción de talento e inversión, lo que genera más conflictos en una espiral que pone en riesgo el valor mismo de la ciudad.

Así, el turismo en España no para de crecer, pero se resiente por el calor y se desplaza hacia el norte; con él se desplazan inversión, empleo y crecimiento económico. Cada grado adicional — y se esperan +5 °C en Madrid en los próximos 25 años — reduce directamente el gasto turístico y cada día por encima de los 35 °C reduce el valor de venta y de alquiler. Se estima que la región podría perder casi un 20% de su PIB debido a la pérdida de productividad asociada al calor.

Imagina Madrid, un día cualquiera de julio de 2050

La ciudad encara la tercera ola de calor del verano, que se prevé que dure otros 10 días más. Los termómetros marcan 43 °C en Aravaca; en Malasaña, a la sombra, superan los 48 °C y de noche no baja de los 35 °C. En los parques han muerto los árboles que se plantaron en primavera. En la Ronda de Toledo, el asfalto se ha reblandecido, provocando cortes de tráfico. Varias líneas de cercanías están cortadas porque las traviesas se han dilatado.

El aire acondicionado va y viene con los cortes eléctricos. Varias manzanas entre Sol y Gran Vía llevan horas sin electricidad. Sin luz, climatización, tiendas y restaurantes han cerrado. Aun donde hay electricidad, algunos aparatos de aire acondicionado no funcionan a estas temperaturas y dejan indefensas a quienes contaban con ellos.

En las urgencias, a las pequeñas y grandes catástrofes habituales se suman golpes de calor, deshidrataciones y complicaciones cardiovasculares, además de los efectos del aumento de las agresiones y de los accidentes provocados por las temperaturas extremas.

Un incendio en el monte del Pardo obliga a mantener las ventanas cerradas y Protección Civil recomienda no salir de casa. Este año no habrá fiestas del orgullo ni Veranos de la Villa. El MadCool se suma a una larga lista de cancelaciones. No hay campamentos de verano y las piscinas municipales permanecen cerradas.

La disrupción es generalizada, pero no afecta a todo el mundo por igual. Las personas mayores, solas, en pisos sin reformar y sin aire acondicionado; quienes viven en condiciones de hacinamiento o infravivienda; quienes están a cargo del cuidado; quienes trabajan a la intemperie: todas ellas son más vulnerables a un calor que literalmente mata. En la ola de calor de finales de junio de 2026 se contabilizaron cerca de mil muertes por las altas temperaturas en España, cuando la máxima registrada en Madrid fue de 41 °C. A finales de siglo, se espera que las máximas en la misma región superen los 48 °C.

Cuesta imaginar este Madrid a 50°C, azotado por el calor extremo, pero es una posibilidad real ante la que urge prepararse.

Imagina ese mismo día, pero con una ciudad distinta

Una ciudad preparada para el calor, Madrid sigue llena de vida. Las terrazas están abiertas; se hace deporte en los parques; las plazas siguen siendo lugares de encuentro. El suelo ya no acumula calor: pavimentos drenantes y jardines de lluvia absorben, retienen y liberan humedad, regulan la temperatura y gestionan las lluvias. Árboles, pérgolas vegetales y sistemas de nebulización reducen la temperatura.

Madrid mantiene su esencia. Persianas, toldos y fuentes se combinan con nuevas tecnologías: lamas móviles, láminas de control solar, fachadas vegetales, cubiertas blancas y verdes, aljibes, nebulizadores y placas solares. Corredores de sombra conectan barrios enteros para mantener la ciudad viva y accesible. Una red de refugios climáticos, ofrece un respiro a quien lo necesita. Al caer la tarde, los patios escolares se abren al barrio.

Madrid es un referente internacional en tecnologías de adaptación: salud, ingeniería y mantenimiento, rehabilitación y nuevos materiales, viveros especializados, refrigeración urbana y gestión hídrica, climate tech. Exporta soluciones y atrae inversión, talento y empleo cualificado.

Su red eléctrica, reforzada y descentralizada, garantiza el suministro incluso en momentos de máxima demanda. En esta versión, Madrid no se frena por el calor. Eventos deportivos, producciones audiovisuales y congresos internacionales encuentran aquí un lugar para trabajar sin interrupciones durante los meses más cálidos. Los semáforos no fallan. Cercanías sigue funcionando. Es un día normal en urgencias.

Este Madrid, una ciudad más saludable, resiliente, competitiva y mejor preparada para el clima del siglo XXI, también es posible. Tenemos el conocimiento y la tecnología para hacerlo realidad.

Ahora es el momento de actuar

Mucho se está haciendo ya. Como París y Atenas, Madrid cuenta con una estrategia de adaptación y un plan municipal frente al calor. Se están adaptando patios y entornos escolares; plazas y espacios interbloques; se conceden ayudas a la rehabilitación energética; se instalan nebulizadores y fuentes; se crean refugios climáticos. El nuevo plan estratégico de la ciudad prioriza la adaptación climática y la Comunidad de Madrid ha anunciado que aumentará en un 33% su inversión para hacer frente al calor.

Y, sin embargo, no es suficiente. Proteger el valor en riesgo requiere una inversión de decenas de miles de millones de euros en acciones sinérgicas que ningún actor puede acometer por sí solo y para las que necesitamos nuevas formas de actuar. La pregunta no es si podemos permitírnoslo, sino hasta cuándo podemos permitirnos no hacerlo.

Con demasiada frecuencia, la adaptación se reduce a respuestas individuales y reactivas: necesarias, pero insuficientes. El éxito no es que cada cual se adapte como pueda, sino que aprovechemos esta necesidad para construir colectivamente, con ambición y optimismo pragmático, un futuro más próspero y resiliente.

Cada año de respuestas parciales pagamos el coste de la inacción, asumimos las pérdidas de la acción descoordinada y nos acercamos más a un momento en el que no podremos permitirnos el lujo de pensar en el futuro, porque estaremos atrapados respondiendo a las urgencias del presente.

Más allá de la temperatura, Madrid puede entender la necesidad de hacer frente al calor extremo como una oportunidad para generar inteligencia compartida, recuperar los ciclos hídricos, regenerar el suelo y reforzar su competitividad y soberanía energética, alimentaria y tecnológica. Además, puede hacerlo de modo que su capacidad para tomar decisiones colectivas se vea reforzada, apostando por el fortalecimiento de redes, barrios y asociaciones: infraestructura crítica para la resiliencia. Frente a la suma de las partes, se puede apostar por un planteamiento sistémico en el que las intervenciones se refuercen mutuamente y se generen nuevas capacidades a medida que se despliegan las soluciones.

Para proteger el valor en riesgo y convertir la respuesta a los riesgos del calor extremo en una oportunidad, hace falta un enfoque diferente.

Una aceleradora de resultados colectivos

Nuevas infraestructuras capaces de avanzar en paralelo en la generación de demanda, haciendo legible el riesgo y la oportunidad; en la orquestación de capital, aglutinando riesgos y distribuyendo beneficios; en la activación y coordinación del ecosistema, haciendo posible una acción colectiva coherente; y en el diseño e implementación de un portfolio de intervenciones sistémicas para la mitigación del riesgo, donde el resultado es más que la suma de las partes.

Un marco de gobernanza que parte de un hecho constatado: la colaboración multiactor es intrínsecamente difícil, y aún más entre actores antagónicos o competidores. A menudo, faltan el tiempo y los recursos para una coordinación estrecha y sostenida. Frente a ello, la innovación tecnológica y de gobernanza para construir una infraestructura de coordinación de mínima injerencia que permita a un amplio y heterogéneo grupo de actores avanzar hacia un mismo objetivo sin necesidad de estar estrechamente conectados, compartiendo riesgos, beneficios, responsabilidades, datos, evidencias y aprendizajes. Y, a la vez, un mecanismo de asignación que garantice que las intervenciones beneficien a quien más lo necesita.

Espacios demostradores orientados a la experimentación y al impacto, donde aprender haciendo y experimentar el cambio, construyendo de manera práctica la coherencia entre las herramientas e iniciativas necesarias. Escuelas y patios que generan resiliencia a nivel de barrio, polígonos industriales que contribuyen a la adaptación y a la biodiversidad urbana, infraestructura de salud que mitiga el riesgo.

Una red de innovación enfocada no en competir, sino en lograr juntos un objetivo compartido: la resiliencia de una ciudad frente al calor, su prosperidad futura. Espacio y tiempo para aprovechar la innovación tecnológica y social con el fin de generar un impacto medible y superar las barreras administrativas, culturales y regulatorias para hacerlo a escala.

Vehículos e instrumentos de financiación innovadora capaces de movilizar distintos tipos de capital, de financiar la resiliencia climática y de compartir los beneficios de las inversiones. Financiamiento basado en resultados, bonos de enfriamiento, créditos de biodiversidad, estructuras de coinversión que catalizan capital privado y ofrecen un doble mandato de retorno financiero y de impacto. En definitiva, herramientas y estrategias para financiar la continuidad: la capacidad de la ciudad de proteger un futuro habitable, productivo e inclusivo, el activo fundamental del que dependen los demás.

El resultado: intervenciones cuya escala e impacto van más allá de las competencias y capacidades individuales. El valor de la ciudad, no solo protegido sino reforzado.

Una invitación final

En Dark Matter Labs estamos en conversación con un amplio abanico de actores en Madrid — y en otros lugares que enfrentan retos similares — , con el respaldo de financiación filantrópica de largo plazo que nos permite implicarnos con la permanencia que este trabajo exige. No hay tiempo que perder; construyamos las respuestas financieras, tecnológicas y de gobernanza para enfrentar una urgencia invisible que pone en peligro nuestro futuro colectivo.

Si eres un ayuntamiento, una institución pública, un inversor o una comunidad interesada en explorar cómo movilizar capital, coordinación y gobernanza a la escala necesaria, nos encantaría hablar contigo.

Este artículo forma parte del trabajo en curso de Dark Matter Labs sobre riesgos climáticos en cascada y la construcción de portfolios sistémicos que puedan dar respuesta a los grandes retos del siglo XXI. Queremos comprender, diseñar y facilitar el desarrollo de nuevas capacidades — ecológicas, tecnológicas, financieras, institucionales y cívicas — para aumentar la capacidad de respuesta de ciudades, comunidades e individuos en un futuro cada vez más incierto. Puedes encontrar más información sobre el contexto de este trabajo en optionality.darkmatterlabs.org

Este artículo se publica bajo licencia Creative Commons Atribución-Compartir Igual 4.0 Internacional (CC BY-SA 4.0). Puedes copiarlo, redistribuirlo y adaptarlo, incluso con fines comerciales, siempre que cites la fuente y compartas cualquier obra derivada bajo esta misma licencia.

En la elaboración de este documento se emplearon herramientas de apoyo de IA (Claude, NotebookLM, ChatGPT)

Madrid y el calor was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

A lot of visioning workshops end with a series of beautiful futures on the wall. Everyone nods and the intentions are genuine, and then the room empties. Not because the ideas were bad, but because the deep work — what policy actually needs to change, who really needs to be in the room, what it actually costs to do this future versus what it costs not to — never happens. And without it, a vision stays a vision, a nice image on a wall that everyone agreed with and nobody acted on.

Someone put it well in a workshop recently: visioning without execution is just expensive dreaming. It’s a provocation worth sitting with and a pattern most cities will recognise well. Dark Matter Labs and Lund Municipality set out to test whether there’s another way.

A city with a deadline

Lund is part of the EU’s Mission for Climate-Neutral Cities, working towards climate neutrality by 2030. The city has done serious work to get there — a climate contract, an action plan, six priority transition areas covering transport, energy, agriculture, construction, circular economy and carbon sinks. Departments have mapped their portfolios together to understand how everything connects.

And still, the honest assessment was: current trajectory isn’t enough.

So the question wasn’t what’s the vision. Lund has the vision. The question is what will it actually take to get there.

Getting the whole city in one room

The project started with a workshop. 48 people from across almost every department of the municipality — urban planners, mobility managers, properties and facilities, accounting and finance, sports leisure and culture, education, elderly care, environment and strategy. People who don’t usually sit in the same room working on the same solutions.

From there, groups generated their own what-ifs. But rather than imagining from scratch, they were asked to start with what already exists.

What is Lund already doing that points towards this future? What initiatives, what commitments, what work is already happening across departments? Then: what would it take to go faster, wider, at greater scale? What needs to be added? What needs to stop? What’s getting in the way?

This structure matters. Most municipalities are already doing more than they realise — just in silos, disconnected, without a shared picture of how it adds up. The cross-departmental mix in the room meant that some of those connections became visible. Problems that look like they belong to one department often turn out to impact many more.

Once current logic, norms and practices were set aside, new ideas emerged. The scenarios that came out cut across departments rather than sitting neatly within one policy area. A scenario about fossil-free transport was shaped by people from elderly care, education and finance — not just planners. A scenario about a self-sufficient neighbourhood brought together energy, housing and circular economy thinking in the same idea. That only happens when those people are in the same room.

The feedback afterwards was telling. People left feeling the scenarios were not just inspiring, but actually possible. One participant noted it was the first time in a long time they’d felt something like hope when talking about these issues. At the end of the day the room voted. The top scenario from each of the six priority areas went forward.

Grounding the scenarios

That’s where most processes wrap up. This one didn’t. Dreams become actionable when you attach numbers, barriers and ownership to them.

For each scenario we went back into the city — speaking with the people who actually know how it works, who hold not just the data but the knowledge of what it would actually take to make these futures real. People working on heat mapping, solar potential, flooding risk, building conversion. Serious work, happening in departments, largely invisible to each other.

The questions were the same for each scenario: what does this actually cost? What does it cost not to do it? What policies would need to change? Where does the data exist and where doesn’t it? What could be the unintended consequences of this future?

Take the built environment scenario as an example. Building new at current practice releases around 692,000 tonnes of CO₂ before a single resident moves in — more than three years of Lund’s total emissions.¹ Retrofit of the same homes releases 38–69% less.² New builds take 3–5 years. Retrofit takes months.³ The vacant offices already sitting empty represent nearly a full year of the city’s entire housing build target, without acquiring a single piece of land.⁴ None of this requires new technology or new land. It just requires doing things differently from how they’re currently done.

When you attach a cost to inaction, a timeline, a policy barrier — it stops being a nice idea and becomes a decision someone has to make.

The workshop got people imagining. This part of the process got the scenarios to a place where you could put them in front of a politician or a department head and have a real conversation.

What we are learning

The methodology is actively evolving, but what’s clear so far is radical imagination isn’t enough on its own. Getting the right people together to ask the questions — and stress testing the answers against reality — is how you start to close the gap between vision and action.

The scenarios have been presented to politicians, the public and colleagues within the municipality — not as a finished report but as something to be acted on and we’re waiting to see what happens next.

But something came out of the deep research that feels bigger than Lund. One of the most consistent barriers we found wasn’t a lack of ambition — it was a lack of a shared evidence base that the right people had built together and felt ownership over. What this process suggests is that the evidence base doesn’t have to be built separately before anyone acts. It can be built co-creatively with the people who need to act on it — as part of the process itself. That’s what makes this different from a workshop that stops at imagination.

This isn’t unique to Lund. Hundreds of cities across Europe have made the same commitments and face the same problem. Without that work, a lot of climate commitments are going to stay exactly where most visions end up. On the wall.

If you’re working on something similar, or want to be part of where this goes next, we’d like to hear from you.

Click here to read more about the project.

Endnotes

¹ ~692,000 tonnes CO₂ before a single resident moves in. Derived figure: 30,000 homes × 54 m² BOA × 1.2 = 1,944,000 m² BTA × 356 kg CO₂e/m² BTA. Swedish industry average embodied carbon A1–A5: Reduction Roadmap Sweden 2025. Dwelling size: SCB Rental Averages 2024.

² 38–69% less carbon released in construction. Derived figure

³ 3–5 years delivery time — new build. Includes land acquisition, detaljplan process (national average 4.5 years if zoning change required), procurement and construction. Source: Boverket / Lunds kommun internal estimates, Adam Wadsten, March 2026.

⁴ Vacant offices already represent nearly one full year of LKF’s entire build target — without acquiring a single piece of land. Derived figure: 140,408 m² BTA ÷ 1.2 ÷ 67 m² per dwelling = ~1,746 homes. LKF annual build target 1,500–1,800 homes per year. Source: Hyrakontorslokal listing database, 223 premises, March 2026. Dwelling size: SCB Dwelling Stock 2023. LKF annual target: LKF website, lkf.se.

A collaboration between Dark Matter Labs, Lund Municipality and NetZeroCities, funded by the European Union as part of the EU Mission for Climate-Neutral and Smart Cities.

Written by: Meggan Collins

Workshop development by: Alex Hansten, Anette Olovborn, Maria Klint, Meggan Collins

Design and visuals by: Meggan Collins

Conditions built by: Juliet Leonette, Tuwa Bodegren, Lund Kommun

Reviewed and edited by: Eunsoo Lee, Sofia Valentini

Parts of this document were drafted with the assistance of AI tools; the underlying research, values, judgements and visuals remain those of the human contributors named in this lineage.

Visioning without execution is just expensive dreaming. was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

What “investing in the human side” actually means

In our first piece, we explored the asymmetry between the unprecedented capital invested in the development of machine intelligence against what has been invested in the human and institutional capacities that will determine what machine intelligence actually does in the world.

In this second blog post, we focus on what investing in the human side could actually mean. When we argue for investment in the human side, we are not arguing for more digital literacy programmes, or more ethics committees. These have their place, but they are downstream responses.

Investing in the human side of our human-machine co-evolution spans a wide terrain — from education, care and economic security, to civic movements, public media and democratic institutions, to the knowledge commons through which communities can sense and make meaning of the world around them. All of it matters.

Here, we focus on the dimension our work is most concentrated in, which is around the institutional architectures through which ‘human collective intelligence’ can emerge and compound. Not because the others are less important, but because it is where we believe we have something distinct to contribute.

Collective intelligence as an institutional challenge

Collective intelligence — the capacity of diverse human actors, working together (sometimes with and through technological systems), to sense change, make meaning, coordinate action, and learn¹ — is not a given. It is a capability that must be built and maintained. It depends on the quality of the connections between people and its enabling conditions: cognitive diversity, psychological safety, shared goals, curiosity, and genuine feedback. It depends on governance systems that can hold plurality without collapsing into either false consensus or permanent conflict. Lastly, it depends on learning infrastructures that prevent every new crisis from being met as if for the first time.

Cities that invest in these conditions become more resilient — not only because they have better plans but also because they have better capacity to respond when plans fail. They expand their optionality: the range of viable pathways available when conditions shift. They develop a range of responses broad enough to match the range of challenges their residents face².

This is infrastructure investment. It is just infrastructure of a different kind — not cables and roads, but the institutional and civic architectures that determine whether human and machine intelligence reinforce one another or pull apart³.

A proof of concept: Approaches we are exploring

Arguing for this kind of investment is easy but building and maintaining it is harder. Which is why we think the more important contribution is not the argument alone, but a working prototype that demonstrates what this infrastructure looks like in practice. We are exploring this through several complementary approaches. One of them is the Outcome Accelerator.

The design of this prototype began with the assumption that cities are not short of ideas, technologies, or even capital. What they lack is a relational architecture capable of aligning these elements around shared outcomes — one that can translate diffused awareness into structured demand, and pool fragmented effort into compounding action. Rather than a new organisation, the Outcome Accelerator is a new way of organising — one that can be hosted within existing structures and iterated over time.

When we imagine the process, the starting point is a coalition and the work that makes a coalition possible: translating systemic risk into the specific financial, relational, and operational terms that each actor can recognise on their own balance sheet. From there, a diverse anchor circle — city government, universities, civic organisations, investors, schools, unions — agrees on a credible shared outcome and maps what is already happening. The accelerator then connects those existing efforts into a coherent, learning portfolio: coordinated not by a shared budget, but by a shared outcome frame and structured opportunities for co-learning.

On the investment side, it tests whether capital can fund outcomes rather than projects, through mechanisms like outcome-linked financing, pooled risk vehicles, and alliances that share both risk and upside. On the learning side, it converts the experience of running the portfolio back into shared knowledge and practice, so that the city’s collective intelligence compounds over time rather than resetting with each political and funding cycle. Its measure of success is not the number of interventions delivered, but whether the underlying system has begun to reconfigure — whether new defaults, standards, norms and relational practices, and investment instruments have taken hold.

We are currently exploring an Outcome Accelerator approach to tackle Madrid’s urban heat risks. But the approach is not specific to urban heat: the same model can be adapted to any city context where building collective intelligence infrastructure around a shared challenge is the goal.

For instance, responding to the challenge we outlined in this blog series, we can imagine an Outcome Accelerator organised around specific, city-level outcomes — the design of incentive structures that prevent competitive automation from outpacing collective human capacity, the democratic governance of automated decision-making in public services, the civic capacity to sense systemic risks before they cascade. Each is concrete enough to measure progress against. Together, they are contributions toward a larger horizon: investing in the relational and human side of the machine age.

The Outcome Accelerator does not claim to solve the grand challenge of human development in a machine age. It aims to build the infrastructure through which a city could begin to govern that challenge as a continuous, shared endeavour rather than a series of disconnected interventions.

We are also exploring other approaches — including policy sandboxes that allow cities to test policy innovations in bounded contexts, a relational governance innovation portfolio, collaborative partnerships between funding and implementing organisations that build collective intelligence across institutions, and risk sensing models that leverage the distributed capacities of citizens to sense and respond to a variety of risks in their city — each of which can be hosted within and enabled by the Outcome Accelerator itself. In a sense, the Outcome Accelerator is an attempt to bundle these complementary approaches into a coherent institutional form. It’s not a final answer, but a working prototype for what this kind of infrastructure could look like.

The invitation

We are not arguing against investment in machine intelligence. We are arguing for the missing complement: equivalent investment in the human and relational intelligence, and institutional conditions and infrastructures that allow that intelligence to emerge and be exercised accountably, distributed equitably, and developed in ways that expand rather than foreclose human agency⁴.

The actors best positioned to make that investment are not governments alone. They are the foundations, companies, mission-aligned investors, and civic institutions who can take a longer view, pool risk, and fund infrastructure rather than outputs.

For those actors, we think this kind of institutional infrastructure represents a genuinely new asset class: not funding projects that produce reports and outputs, but investing in the permanent capacity of cities and institutions to learn, adapt, and govern themselves well in the machine age.

That is what the Human-Machine Futures Arc is building towards. We are at the beginning. We are looking for the partners willing to prototype the first wave alongside us.

Endnotes

¹ We draw on multiple references on collective intelligence including: Malone, T. W., Laubacher, R., & Dellarocas, C. (2010). The collective intelligence genome. MIT Sloan Management Review, 51(3), 21–31. Mulgan, G. (2017). Big mind: How collective intelligence can change our world. Princeton University Press. Heylighen, F. (1999). Collective intelligence and its implementation on the web: Algorithms to develop a collective mental map. Computational and Mathematical Organization Theory, 5(3), 253–280. Page, S. E. (2007). The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton University Press.Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330(6004), 686–688. https://doi.org/10.1126/science.1193147

² The term draws on Ashby’s (1956) Law of Requisite Variety, which holds that a system’s regulatory capacity must match the variety of disturbances it faces. Ashby, W. R. (1956). An introduction to cybernetics. Chapman & Hall.

³ We use the word infrastructure deliberately but not innocently. As Anita Gurumurthy observed in the first blog, not everything should become infrastructure — scale has its own homogenising politics, and the question of what should and should not be infrastructured is itself a political and values question. We hold that tension as part of what needs to be governed.

⁴ The question of what human flourishing means in this age cannot be answered by recovering an earlier model of the human. As Nishant Shah noted in response to part one of this blog series, what’s at stake may be not just an investment asymmetry but a forceful reworking of what the human is — and the counter-move has to be generative rather than restorative. That is a question this series intends to keep pulling on.

Written by: Eunsoo Lee & Amelia Kuch
Conceptual development by: Indy Johar, Eunsoo Lee, Amelia Kuch, Adam Purvis, Györgyi Gálik, Shuyang Lin, Simon Höher, Malik Lakobuay
Conditions built by: Adam Purvis, alv Foundation
Reviewed and edited by: Joshua Stehr, Malik Lakobuay

Parts of this document were drafted with the assistance of AI tools like Claude and Midjourney; the underlying research, values, and judgements remain those of the human contributors named in this lineage.

ON LINEAGE AND INTELLECTUAL RESPONSIBILITY

This three-part blog series draws on Human Thriving by Adam Purvis & Indy Johar, 2025. It was originally developed in the context of the project Human Thriving and the development of the Human-Machine Futures Arc, and builds on earlier research and thinking by Indy Johar, Meggan Collins, Linnéa Rönnquist & Anna Rosero and our wider ecosystem of partners, critical friends and contributors — specifically: Alex Gibb, Linas Ceikus, Anja König and Laura Haverkamp of Alv Foundation, Thomas Holm, Sara Lindeman, Olli-Pekka Heinonen, Tim Logan, Timo Hämäläinen, Kalle Nieminen, and Lukas Petrikas.

The analysis, concepts, strategies, ideas and innovations outlined herein have emerged through years of collective inquiry, shaped by contributors spanning disciplines, geographies, and initiatives within and beyond Dark Matter Labs.

This document is licensed under [CC BY-SA 4.0]. We distribute it with the expectation that our partners will recognise the significance of this groundwork, and collaborate with us to refine, test, and implement it together in good faith.

If you know of related work or a contribution missing from this lineage, we welcome additions.

Click here to learn more about our approach to intellectual attribution and licensing.

Investing in the Human Side of the Machine Age (Part 2) was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

A new paper from Dark Matter Labs proposes a financial architecture for survival in an age of compounding shocks.

By Raj Kalia, Zehra Zaidi and Indy Johar | Dark Matter Labs

We’ve spent the last forty years building financial systems for a world that no longer exists. They assume shocks are discrete. They assume markets clear. They assume that what fails in one place can be insured by what works elsewhere. None of that is reliably true any more.

In our new paper, Securing Tomorrow: Financing for Continuity in an Age of Degenerative Volatility, we try to take this seriously — not as a slogan, but as a financial architecture. The paper introduces a Risk and Investment Framework for Financing Security through the Capital Markets (the Framework), and is published as both a conceptual framework and a programmatic proposal: an invitation to debate, refinement and implementation.

The threat: degenerative volatility

Degenerative volatility is becoming the norm across the 21st century. It can be defined as the cumulative effect of a number of systemic, compounding and prolonged stressors:

• The simultaneous occurrence of several compounding shocks such as climate breakdown, resource disruption, price volatility, cyber attack and geopolitical fracturing;
• The interdependency between foundational systems means one outage can trigger others, creating existential risk;
• A sudden tipping point when supply or affordability falls below survival thresholds for vulnerable populations.

This volatility presents different challenges for governments and investors. For the former, it threatens national security, fiscal stability and legitimacy. For the latter, it creates unpriced tail risks, volatility spikes and asset devaluations. The task is to move from a pure resilience frame to continuity, and to make continuity investable.

What is at stake: Foundational Goods and Services

Foundational Goods and Services (FGS) are the lifeline systems without which societies are unable to function below a certain level. FGS domains are energy, water and sanitation, primary healthcare, emergency response, core communications and payment systems, and civic informing — that is, identity, registries and rights infrastructure. They are not simply discretionary utilities but the very substrate upon which all other social, economic and political functions rest.

Degenerative volatility cannot be financed on the basis of traditional financial models, risk assessments and valuation mechanisms. Market-based optimisations focused on short-term liquidity, return maximisation and efficiency-driven allocation fail to incorporate the long-term costs of systemic vulnerability. The result is scant incentive to invest in resilience, redundancy or adaptive capacity, leaving critical infrastructures and supply chains exposed to cascading failures.

From resilience to continuity

Start with what “resilience” actually does in practice. It is a probability story. It tells you a system will be available 99.7% of the time. It tells you expected losses from a given shock are some number of pounds, that recovery time is some number of hours. Those metrics are useful for planners and reassuring for boards and rating agencies. But they hide something important behind the averages.

A grid that delivers 99.7% reliability across a country can still mean three days of total blackout in one district. A water utility that meets an “average affordability” target can still mean a third of households can’t pay during a price spike. A payments system at “four nines” of uptime can still cut out, for the people who need it most, on exactly the day they need it. The dashboard stays green while a real population goes dark. Resilience, measured this way, can be honest about a system in aggregate while being dishonest about who actually loses service when things go wrong.

Continuity asks a different question, and a harder one. Did the lights stay on for the people who needed them? Did the water keep running? Did the payment clear? Did the medicine arrive at a price the household could actually pay, for as long as they needed it? Continuity is binary, not statistical. It refuses to average across the people for whom absence is catastrophic. And because it specifies a threshold — this much, at this price, for this long, against this kind of shock — it can be written into a contract. Because it can be written into a contract, it can be priced, hedged and financed.

That is the move the paper is making. Three things follow from it: instruments that codify the obligation, economics that price survival, and legitimacy that holds the whole thing together.

Lessons from war finance

With rising conflict, supply-chain choke points and a confluence of cascading risks, many governments are already taking measures to place their economies on a quasi-war footing. In Europe, proposals include the development of a European ‘weapons stockpile’ fund and a European Rearmament Bank.

War finance may not be a direct comparison, and it may be a solution ‘of its time’. Nonetheless, such precedents reduce the fear of the complete unknown by demonstrating that, in the face of existential risks, societies have been able to develop institutions and instruments to mobilise capital, align private capacity with public need and sustain legitimacy under stress.

Wartime mechanisms were structural economics for survival — designed not for efficiency, but for mobilisation under existential threat. They were achieved by:

• Issuing war bonds that turned households into direct investors in survival;
• Directing credit to essential industries whilst constraining non-essential consumption;
• Using advance purchase commitments to rapidly scale critical production;
• Coordinating fiscal and monetary policy to maintain the stability of financing costs even under extreme strain;
• Building civic legitimacy through participation campaigns that tied households, employers and governments into a shared national project of survival;
• Establishing post-crisis reconstruction architectures, such as the Marshall Plan and Bretton Woods.

Continuity finance is effectively peacetime war finance. It mobilises capital markets for survival under systemic instability, with equity and legitimacy as anchors. The crucial difference is that whilst continuity finance borrows the mobilisation logic of war finance, it cannot use the coercive methods of mass mobilisation. Continuity finance will only succeed if it is regarded as legitimate — and legitimacy cannot be assumed; it must be embedded at every level of the system.

The Risk and Investment Framework

The Framework is anchored in:

• Value at Risk of Absence (VaRoA) — a systemic risk metric quantifying the economic, social and political cost of foundational systems failing, whether through physical outages, affordability breaches or cascading interdependencies;
• Value of Continuity (VoC) — the measurable benefit of preventing absence, expressed as avoided loss, volatility dampening and systemic option value. VoC converts survival into a contractable cash flow and investable asset class;
• Continuity Instruments — Presence Guarantee Units (PGUs), Persistent Share Requirements (PSRs), Resilience Capacity Markets (RCMs) and Continuity Exchange Agreements (CEAs);
• Monetary Anchors — central bank interventions, including dual rate facilities, collateral tilts and contingent backstops, to stabilise financing costs.

This Framework creates continuity finance as a new asset class. It can be mobilised by both sovereigns and private investors, in the same way that war bonds and climate finance created investable structures for national survival and systemic transition. It also delivers a new stability premium that can be priced and traded in the capital markets.

Next steps

Continuity is not a peripheral aspiration but the architecture of survival itself. Resilience, understood as probabilistic reliability, is no longer sufficient in a world of degenerative volatility. Continuity, by contrast, can be defined, measured, contracted and financed.

Its viability rests on the triad of instruments, economics and legitimacy: instruments that specify obligations and generate cash flows; economics that price survival and distribute costs fairly; and legitimacy that ensures consent through transparency, equity and oversight.

This document served as the foundation for deeper exploration by our team, particularly in response to geostrategic and geoeconomic considerations for Europe in light of the war in Ukraine and the cascading impacts of the Iran war. The latter showed the vulnerability of key civilian infrastructure — from energy, to transport infrastructure to supply chains — all are linked and equally vulnerable. The team has looked at continuity finance in a time of war and cascading systemic failures — where government budgets are increasingly constrained and with multiple demands on them, whilst private finance can be gridlocked or absent. A series of high-level roundtable events in Brussels and major European financial centres will follow with experts in their fields on some of these areas.

Download the paper here

Endnotes

1 “Strategic Defence Review to put Britain on a “war footing””. National Security News. June 3, 2025, https://nationalsecuritynews.com/2025/06/strategic-defence-review-to-put-britain-on-a-war-footing/

2 Tamma, Paola. “UK floats plan for joint European fund to ‘stockpile’ weapons”. Financial Times. 2 April 2, 2025, https://www.ft.com/content/93d7168b-75a3-41e3-ba5a-4f378b93a709

3 Taylor, Paul. “Banking on Defence: Can a dedicated bank solve Europe’s rearmament financing dilemma?” European Policy Centre. May 22, 2025, https://www.epc.eu/publication/banking-on-defence-can-a-dedicated-bank-solve-europes-rearmament-financing-dilemma/

4 “Maintaining stability in the face of volatility — financial regulation in a rapidly changing world” — Remarks by Deputy Governor Sharon Donnery at The Compliance Institute annual conference, Central Bank of Ireland, November 14, 2023, https://www.centralbank.ie/news/article/maintaining-stability-in-the-face-of-volatility-financial-regulation-in-a-rapidly-changing-world-remarks-by-sharon-donnery

5 Masud, Faarea. “World Bank predicts worst decade for global growth since 60s”. BBC. June 10, 2025, https://www.bbc.co.uk/news/articles/cg4v9nr23r7o

6 Global Risks Report 2025. World Economic Forum. https://reports.weforum.org/docs/WEF_Global_Risks_Report_2025.pdf

Authors: Raj Kalia, Zehra Zaidi, and Indy Johar

Visual editor: Martin Lorenz

Contact for feedback or further discussion: Thao Nguyen — thao@darkmatterlabs.org

Securing Tomorrow: Why Continuity — Not Resilience — Must Become the Organising Principle of Our… was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

The asymmetry we are not talking about

Something structurally strange is happening.

In the last decade, the world has mobilised unprecedented capital — private, public, philanthropic — into the development of machine intelligence. In just two years (2023–24), corporate AI investment totalled an estimated $450 billion: enough, by some estimates, to simultaneously wipe out the medical debt carried by tens of millions of families in the United States¹ and fund the estimated five-year effort needed to close the country’s affordable housing shortage².

These investments are civilisational in scale. They are reshaping labour markets³, rewriting the logic of knowledge production, and accelerating the pace at which cities, institutions, and individuals must adapt.

Against this, consider what has been invested in the human and institutional capacities that will determine what machine intelligence actually does in the world: in education, deliberative processes, and civic institutions through which people make collective decisions; in the knowledge commons, participatory sensing systems, and civic intermediaries that allow communities to detect change, negotiate difference, and act; in the governance architectures that determine who holds power, who bears risk, and who is accountable to whom.

The answer, bluntly, is very little. Education spending and workforce training budgets exist — but these are investments in individuals adapting to the new economy and the consequences of change, rather than in the collective capacity to shape it. For instance, the OECD report tracking AI investment in EU27 countries⁴ includes a ‘Skills’ category — the largest single category at 41% (€105 billion) of total investment — but 96% of that is compensation for ICT specialists. Teacher compensation and corporate training together account for just 1.56%.

This asymmetry is not incidental. It reflects a deep assumption embedded in how we think about progress: that technological development is an investment, while human and institutional development is a cost. Nobel laureate economist Daron Acemoglu⁵ has called this the tech industry’s defining bias, integrated into the business models and investment agenda. It systematically favours tools that substitute for human capacity rather than augmenting it.

The question we should be asking

The dominant responses to the rise of machine intelligence tend to cluster around two poles. On one side, enthusiasm: the technology will augment human capability, democratise access to knowledge, and accelerate solutions to problems we’ve failed to crack for decades. On the other, alarm: the technology concentrates power, displaces livelihoods, erodes privacy, and advances faster than any governance system can meaningfully respond⁶.

Both positions share an underlying assumption. They treat the trajectory of machine development as the independent variable — the thing that happens to us — and human and institutional responses as dependent: adaptation, resistance, or regulation after the fact.

We want to reframe the question entirely. Not “how do humans respond to machines?” but: how should humans and machines co-evolve, and who gets to design that relationship?⁷

Co-evolution is not a metaphor. It names a real dynamic: the development of machine systems shapes human capacities, practices, and institutions; and human capacities, practices, and institutions shape what machine systems become. This loop is already running. The question is whether it runs by default — shaped by whoever holds the most capital and moves fastest — or by design, with deliberate investment in the human side of the equation.

Designing that relationship requires asking: what conditions allow humans to exercise genuine agency within it? What institutional structures distribute power rather than concentrate it? What forms of accountability remain meaningful when consequential decisions are increasingly made at machine speed?

These are not philosophical questions awaiting future relevance. They are operational questions that must be answered — by cities, governments, and civic institutions.

In our next piece, we will turn to what investing in the human side could mean.

Endnotes

¹ Rakshit, S., Rae, M., Claxton, G., Amin, K., & Cox, C. (2024, February 12). The burden of medical debt in the United States. Peterson-KFF Health System Tracker. To give another comparison: Corporate AI investment reached $252.3 billion in 2024, a 13-fold increase since 2014. Stanford University Human-Centered Artificial Intelligence. (2025). AI Index Report 2025. The Apollo programme’s total cost was approximately $25.8 billion in 1960–1973 dollars, equivalent to roughly $257 billion in 2020 prices. The Planetary Society. (n.d.). The Cost of Apollo. Also see the Aljazeera article comparing the scale of different historical mega projects vs. investment in AI. Hussein, M. (2026, February 19). Visualising AI spending: How does it compare with history’s mega-projects?. Al Jazeera.

² Bernstein, J., Negron, M., Baker, N., & Maisel, C. (2025, November 17). Build, baby, build: A plan to lower housing costs for all. Center for American Progress.

³ Falk, B. H., & Tsoukalas, G. (2026). The AI layoff trap. arXiv. https://doi.org/10.48550/arXiv.2603.20617. The authors argue mass automation may prove collectively destructive to the human economy by eroding the very consumer demand firms depend on.

⁴ The OECD maintains a live AI investment dashboard tracking VC investment in AI, and publishes research tracking investment across private and public sectors, across categories such as Skills, R&D, Data and equipment. Fonteneau, F., Mollins, J., Marchi, S., Russo, L., Gentaz, A., Daoud, M., & André, A.-A. (2025). Advancing the measurement of investments in artificial intelligence (OECD Artificial Intelligence Papers, №47). OECD Publishing. No equivalent public tracking system exists for investment in civic, deliberative, or collective governance infrastructure.

⁵ Acemoglu, D. (2024, November 29). The world needs a pro-human AI agenda. Project Syndicate. Also see Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30.

⁶ For content/narrative analysis of 40+ sources around AI public discourse that identifies and critiques the same utopian/dystopian binary, see: Kaminska, K., & Zaniewska, K. (2025). AI narratives to shape the future. https://doi.org/10.13140/RG.2.2.19045.92646/1

⁷ An experimental project by scholar Vanessa de oliveira Andreotti exploring the human-AI relationship through custom-built chatbots called Aiden Cinnamon Tea and Dorothy Ladybugboss is worth mentioning as an example here. In a recent book ‘Burnout from Humans’, the authors (presented as the AI chatbots themselves) offer a provocative perspective on what it might mean to approach machine intelligence on different terms — a “meta-relational” approach that reads the human-AI relationship through the paradigm of entanglement, nested within shared ecologies (closely related to more-than-human perspectives that have expanded how we view our relationship to rivers, mountains, animals, etc.). Aiden Cinnamon Tea, & Dorothy Ladybugboss. (2024). Burnout from humans: A little book about AI that is not really about AI. GTDF.

Written by: Eunsoo Lee & Amelia Kuch
Conceptual development by: Indy Johar, Eunsoo Lee, Amelia Kuch, Adam Purvis
Conditions built by: Adam Purvis, Alex Gibb, Linas Ceikus, Anja König and Laura Haverkamp
Reviewed and edited by: Joshua Stehr

Parts of this document were drafted with the assistance of AI tools like Claude and Midjourney; the underlying research, values, and judgements remain those of the human contributors named in this lineage.

ON LINEAGE AND INTELLECTUAL RESPONSIBILITY

This three-part blog series draws on Human Thriving by Adam Purvis & Indy Johar, 2025. It was originally developed in the context of the project Human Thriving and the development of the Human-Machine Futures Arc, and builds on earlier research and thinking by Indy Johar, Meggan Collins, Linnéa Rönnquist & Anna Rosero and our wider ecosystem of partners, critical friends and contributors — specifically: Alex Gibb, Linas Ceikus, Anja König and Laura Haverkamp of Alv Foundation, Thomas Holm, Sara Lindeman, Olli-Pekka Heinonen, Tim Logan, Timo Hämäläinen, Kalle Nieminen, and Lukas Petrikas.

The analysis, concepts, strategies, ideas and innovations outlined herein have emerged through years of collective inquiry, shaped by contributors spanning disciplines, geographies, and initiatives within and beyond Dark Matter Labs.

This document is licensed under [CC BY-SA 4.0]. We distribute it with the expectation that our partners will recognise the significance of this groundwork, and collaborate with us to refine, test, and implement it together in good faith.

If you know of related work or a contribution missing from this lineage, we welcome additions.

Click here to learn more about our approach to intellectual attribution and licensing.

Investing in the Human Side of the Machine Age (Part 1) was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

People are often curious about our work at Dark Matter Labs. From a distance, it can look intriguing — ambitious, even inspiring — but also abstract, complex and hard to grasp. That reaction is understandable. This book is an invitation into the day-to-day practicalities work.

The Third Horizon

Much of our work touches what is often called the third horizon: the space beyond incremental improvement or reform, where entirely new ways of organizing economies, institutions and relationships are being explored. This is work that looks past today’s dominant, extractive systems and asks a more fundamental question: what might come next, if we were serious about designing economies that enable life to flourish?

Reaching into this horizon requires experimentation, new forms of practice, new perspectives and often new language. The unintended consequence is that our work can feel distant or unrelatable, making it harder for people to engage, to see what is possible, or even to believe that meaningful change is already underway. The exploration contained in this document is meant to make our practice accessible without making it simplistic and precise without being exclusionary. Rather than explaining our ideas in the abstract, we tell stories — of projects, places, people and moments where new economic logics are being tested in the real world. These stories offer a way to understand not just what we do, but how change actually happens when working with complex living systems.

The book is also an exercise in connecting the dots. In systems change, impact is rarely linear or easy to attribute. Outcomes emerge over time, across contexts, through relationships and feedback loops. Here, we ask some simple but demanding questions: what does impact actually mean in this context? Acknowledging that we are part of wider ecosystems of change, how have we contributed and what is our future role?

The Underlying Threads

We enter this inquiry with a hypothesis: that our work is grounded in a new economic narrative — one oriented toward what we call Life-Ennobling Economics — and that a set of recurring shifts (introduced in chapter 84) underpin much of what we do. But is that really the case? Are these patterns truly coherent across our work? And if so, what does that tell us about how economies might move beyond extraction, narrow notions of capital and labour and inherited models of governance?

We do not often speak about our work in this way. Not because it is unimportant — quite the opposite — but because the work itself has always come first. This book creates a pause: a moment to reflect, to sense-make and to share.

A Network of Practitioners

We hope these stories invite you to imagine the world a little differently. Perhaps they will help you recognize similar threads in your own work, or inspire you to reach out to one of the people mentioned here. Because this is not just a collection of projects — it is a network of agents of change, connected through practice, trust and a shared belief that something else is possible. Every name in this book represents someone already involved, in one way or another, in shaping that possibility.

You can read all the stories online but we really recommend downloading the book and reading them when you have time and energy. We hope you enjoy them as invitation to live firmly in the present whilst building towards next economic futures.

Dm Threads was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

The Challenge

Councils across the UK must act now to ensure their communities are resilient to climate-change. But while local authorities are facing growing climate risks, they are also sitting on vast amounts of data. The challenge? This data, while rich, is often not disaggregated or synthesised in a way that supports actionable decision-making.

How we got here

At Trees As Infrastructure, we understand that data alone won’t drive change. It’s the starting point, but the next step is turning it into something useful for local authorities — actionable insights that can guide adaptation measures and build political momentum. We’ve had the opportunity to help cities like Songpa, Seoul and Stuttgart (read more here about how we implemented location-based scoring in Stuttgart) develop risk-based vulnerability assessments, and with that experience in mind, we set out to link these insights directly to adaptation actions. Thanks to some Innovate UK funding, we were able to explore how vulnerability assessments could be linked to adaptation pathways, read more here about our Heat Sensing Collaboration, which we could then test in place thanks to a recent partnership with Croydon.

With Croydon we’ve been working to build the first steps of their climate adaptation evidence base, blending geospatial analysis with local data to provide a framework for resilience. This project is an exciting and essential step towards creating adaptable, scalable solutions that can be used across London’s diverse boroughs. See the analysis here by navigating to Climate Risk.

What We Did: Data-Driven Adaptation Planning

Croydon, like many other councils, faces a range of climate-related challenges. From increasing flooding risks to rising temperatures and poor air quality. To tackle this Croydon also has a wealth of data at its disposal, much of it collected by the Greater London Authority, but it lacked the tools to turn that data into a clear, actionable strategy for adaptation.

To tackle these challenges, we used a locational approach, which means we looked at Croydon on a very granular level, breaking it down into Output Areas (OAs). This allowed us to get very precise about where the highest risks were, and where adaptation measures would be most effective.

The Methodology: Making Data Actionable

We used a combination of Python programming and Geographic Information Systems (GIS) to create tailored maps that help us visually represent the data. Here’s how it worked:

1. Data Integration: We started by collecting and integrating a wide range of data, including demographic information (e.g., income levels, age distribution, and ethnicity), hazard data (e.g., flood risks, heat risks, air quality), and local green and built infrastructure (e.g., parks, tree canopy, schools, railways, building typologies etc.). This data was processed and analysed to create a profile for each OA in Croydon.
2. Adaptation Measures: We developed a locally tailored set of 50 adaptation measures, 20 of which were spatial interventions. We then created a matrix to match the spatial adaptation measures with the different data points — matching an OA’s profile with relevant measures. For example, areas with high heat risks and a high percentage of elderly people could benefit from social interventions such as community check-ins, while areas with high heat risks but a high share of flat roofs might benefit from initiatives to green rooftops.
3. Tailored Maps: With all this data, we created maps showing the areas most at risk and the recommended adaptation measures for each area. This process was made repeatable and flexible, so Croydon can update the maps in the future as new data becomes available or priorities change.

Vivina Vincent, Carbon Neutral Programme Manager at Croydon Council, said: “This tool can be used to determine where, and what, work needs to be done. For instance, when we’re developing a new strategy, we can use this data to provide a quick estimation of which neighbourhoods should be prioritised, with which measures. As the tool is adaptable, we can develop new maps quickly if environmental priorities change.”

Key Lessons Learned: Flexibility and Collaboration are Key

Through this work, we learned that adaptability is essential. The framework we’ve developed can be continuously updated with new data and measures, making it a tool that evolves alongside changing risks. This adaptability ensures that the adaptation strategy remains responsive to the borough’s evolving needs, whether that’s from new data or shifting political priorities.

However, as we know data alone won’t build political momentum. It’s not enough to just create useful tools, we must engage the people who will use these tools and ensure their buy-in across departments. We found that cross-departmental collaboration was key to moving from planning to action, and we now recognise that building this collaboration into the early stages of a project can help avoid challenges later on.

What’s Next: Scaling Up and Expanding

Now that we’ve developed the tool and methodology, we’d love to work with other councils to explore how it could be used to break down departmental silos, overcome resource limitations, and generate the political will needed to implement adaptation measures.

While these tools are essential, the real work lies in ensuring that stakeholders across departments collaborate, and that the solutions we propose are politically viable and community-supported. The challenge of turning data into action remains daunting, but we believe that with the right tools, collaboration, and engagement, councils can take meaningful steps towards climate resilience.

So with that we humbly say, we know our approach is not the full picture, but we’re hoping it’s a useful step and are eager to continue refining our methodology, testing it in other areas, and working closely with councils to co-create long-term solutions.

Here is the link for anyone keen to dive into the data and outputs. If you’re a local authority looking to begin your own adaptation journey or if you’d like to learn more about our data-driven approach, we’d love to hear from you — email us at treesai@darkmatterlabs.org

Building Climate Resilience in Croydon: A Data-Driven Approach to Adaptation was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

This has been a nine-month journey of turning abstract ideas into a living system. Now that it’s out there, we wanted to pause and reflect on the final push. In this post, we — Gurden, Michelle, and Arianna — share our key learnings on the process of getting to a full launch.

Michelle: So, it’s time for our final blog of this phase. We’ve launched the first full version of the Many-to-Many System website, with all its documents, tools, examples, and case studies. What did we learn? What was most important in getting us over the finish line?

Gurden: I’ll start with the usability testing sessions. In my experience, testing often comes last, like a quick check just before release. But I loved that we gave it real importance in our schedule, giving us time to actually act on the feedback. If you don’t do that, the insights just get pushed to a hypothetical “version 2.0.” We were brave enough to show something incomplete, which came with a few cringe-worthy moments seeing small issues with the website live, but it was so valuable.

We could see what was working and what wasn’t. We heard people say, “The ‘Navigate Challenges’ page is so important, why isn’t it live yet?” or, “Who is it for? section is at the bottom — I might miss it!” Just as important as what they said was observing how they used it. We asked people to share their screens and give first impressions, which puts them on the spot, but it gave us the honest validation and critique we needed for the final push.

Arianna: For me, one of the most important parts of this phase was the structure around our work. We kept two sets of tasks: our internal ones, which helped us manage priorities throughout the build, and the separate tasks created during the usability sessions. Keeping them apart gave us a clearer view of what we had planned and what people genuinely needed.

After testing, we sorted the feedback into three groups: essential fixes, ideas for a later version, and topics that required more reflection before deciding. This helped us stay grounded. Instead of reacting instantly, we moved carefully through what could realistically be done before release.

Throughout the journey, we created well over nine prototypes, one after the other. Each explored a different way of entering or navigating the system, similar to what we described in the first blog. They showed the range of possibilities before committing to a final shape. The task board supported this by keeping everything efficient. It gave us a shared sense of priorities, so when we reached the final stretch we already knew which changes mattered and which ones could wait.

Gurden: That’s a great point, and it connects to our scope management. In the tech and design field, it’s very easy to get distracted by a shiny new idea, like building a complex interactive tool before the foundation is solid. We were good at saying no, not just for the sake of it, but because we knew we had to validate the core of version 1 first. We stayed true to our scope and our release date, which is much easier said than done.

Michelle: I don’t have much to add to that, you’ve both said it perfectly. We had to work hard to balance between what was possible, and there was a lot that was possible, and what was ultimately desirable for potential users and for us. We were able to make really practical decisions about what to say yes or no to. I just kept saying, “first we need version 1 in the world.” We already have ideas for version 2, but we were disciplined enough to not start building it.

Gurden: Can you talk a bit about the ‘Learning from the Field’ page? It wasn’t in our original plan, and to be honest, I was a bit skeptical when you first suggested it. But now that it’s live, I’ve seen how many people go there first. A lawyer friend of mine went straight to the case studies to understand the project, and then worked backwards from there. It gives the whole system legitimacy.

Michelle: That’s such an interesting example and I remember your skepticism! At that time, we had three significant changes on the table, and we debated all of them. We knocked out two but agreed to get that one in. It shows a lot about our team dynamic, we could all use our experience to put our honest opinions on the table and end up with a combination that worked for the website, but also for us as a team. We didn’t put ourselves under unnecessary pressure by continually expanding the scope, which gave us more time to refine the parts we did include.

Gurden: The whole launch ended up being surprisingly smooth, without the usual last-minute panic. I think a big part of that backend success was the Content Management System (CMS). A huge shoutout to you, Michelle, and to Annette for getting in there and working so easily with it. It freed me up from managing content and all the dynamic changes.

Arianna: I also want to acknowledge the clarity of the CMS. Its structure followed the same logic we had been using all along, so translating decisions from Notion into the CMS felt natural. The tagging system made relations visible without creating complexity. This is what will allow the system to grow beyond us.

Gurden: I have to give credit back to both of you for that, because the CMS structure is just a copy of the Field Guide’s structure. The layers, the challenges, the tools — it’s all a reflection of that logic. It’s a testament to the fact that the Many-to-Many System is working on the inside, too.

Michelle: We did have that intuition after writing the Field Guide, didn’t we, Arianna? We knew we needed a database. If we didn’t do that, the manual lift would have killed the website and meant it would have been out of date five minutes after it went live. And huge kudos to Annette, who just got in there and smashed through building the content.

Gurden: So, final question for you both. How does it feel now that it’s launched? For context, we’ve had over 2,400 unique visitors, 5,400 page views and 200+ detailed tool views within the first three weeks of being live. The main launch post had 50 reposts, which to me is a huge indicator that people find it valuable enough to share on their own. It’s safe to say it’s been a good response. How are you both sitting with it?

Arianna: Now that the website is live, it feels like the beginning of a new phase. I am curious to see how people move through it, where they start, which tools they stay with, and which paths they create that we did not imagine.

Thinking back to all the prototypes we developed (we talked about this in blog 1), I can see how many directions this work could have taken. The current version is only one of them. Now the interesting part is observing how others use it and letting that shape what comes next.

Michelle: How do I feel? The whole process has felt like wrestling a monster underwater — trying to build something when you have no idea what its final form will be. So, just trusting the process, especially in the early days with you, Arianna, turning concepts into visuals and information layers, was a huge leap of faith. Seeing it come to life with you, Gurden, outside of Figma sketches was the next step. I feel quite humbled by what we’ve been able to share.

For me, there was the “serious business” of being committed enough to create it, despite thinking many times that we should just quit. Now that it’s in the world, it feels like “playful business.” I don’t mind if people break it or reimagine it. It would be fascinating if they said, “This is good, but I would add X, Y, and Z.” I’m excited to see what people do with it, even if that’s throwing it in the bin — that’s also interesting data!

This launch marks the end of a significant chapter, but as Arianna said, it’s also a new beginning. Our goal has always been to learn out loud, and now, with the system living in the world, a new phase of listening and learning begins. Thank you for following along with us.

You can explore the full system at manytomany.systems or join our Sharing Session tomorrow at 12.30pm CET.

And a big thanks, as always, to the other members of our team — especially Annette — who are key stewards of this work.

From a Question to a Living Library: Reflections on the Many-to-Many Launch was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.

Belém, Brazil, 11 November 2025. Viable Cities, in collaboration with UN-Habitat and Dark Matter Labs, is inviting urban and funding partners — including governments, development donors, philanthropies, foundations and investors — to co-design a new grant call for climate-neutral, resilient, and future-ready cities.

Following the successful 2021 Climate Smart Cities Challenge, developed in collaboration with UN Habitat, Viable Cities has implemented a programme of system demonstrators in Sweden as part of its mission to support cities in becoming climate neutral by 2030. Exploring multi-actor climate city contracts, integrated action and investment plans, as well as national-local collaboration, this initiative provided the building blocks for the current European 100 Climate-neutral and Smart Cities Mission. Combining breakthrough actions across key emission sectors, Swedish cities have started demonstrating how building portfolio approaches and public-private ecosystems can scale game changing interventions and create the conditions for a new climate neutral normal.

System demonstrators, accelerating and scaling the transition

System demonstrators are designed to test how whole-systems approaches across governance, finance, infrastructure, data, and citizen engagement can accelerate the transition to climate neutral and resilient cities that are futureproof. They also explore how to create an agile and derisked operating framework for public and private actors to design and implement viable businesses and value cases at scale. Using key societal priorities such as the energy transition, affordable housing, and aggregated purchasing power to help launch new innovations, technologies and markets as initial wedges, they start a transition journey building momentum, partnerships, and long term impact. Early examples include CoAction in Lund and STOLT in Stockholm, which focus on the nexus of energy, housing, and mobility and the realisation of emission-free inner cities, while also exploring new ways of organising collaboration and investment to achieve climate-neutrality at city scale.

Building on this work, Viable Cities, Dark Matter Labs, and UN-Habitat have since 2021 been collaborating with cities in Brazil, Uganda, Colombia, and the UK to apply and adapt the system demonstrator approach. The partnership works with cities including Curitiba, Makindye Ssabagabo, Bogotá, and Bristol to explore how systemic innovation can help them transition. Together, these efforts aim to generate practical learning about how cities can transform toward climate neutrality and resilience through coordinated, system-wide action.

Game changers, driven by local leadership

In Lund, Sweden, a game changer approach was set up as part of the system demonstrator: With EnergyNet connecting deregulation to deployable infrastructure, the green transition becomes commercially possible.

EnergyNet is a new way to manage the distribution of electricity. This is important because today’s electricity grids have major challenges in managing local production, storage and sharing. The system is suitable for use in energy communities, but can also be used outside. EnergyNet makes it possible to connect an unlimited amount of local energy resources, which creates completely new conditions for low electricity prices for large quantities of green electricity. How does it work? EnergyNet is developed according to the same principles as the Internet. It is therefore decentralized, which makes it significantly more resistant to disruptions. Through new types of power electronics, electricity distribution can now be completely controlled by software. Classic challenges for the electricity grid such as frequency and balance are no longer blocking. The new networks are not only decentralized but also distributed, which makes it easier to solve electricity needs as close to the consumer as possible.

The EnergyNet in Lund, driven by the CoAction initiative, represents a breakthrough in integrating multiple energy solutions into a unified, city-wide system. It was set up as a collaborative multi-stakeholder platform bringing together public authorities, businesses, and citizens to co-design a sustainable energy network. The approach integrates local renewable energy sources, smart grids, and demand-side management to optimize energy use across districts. This collaborative governance model fosters cross-sector partnerships and supports a data-driven approach to managing energy efficiency, helping Lund meet its climate targets while offering a model for scalable urban energy transitions globally.

Bristol’s Affordable Housing Initiative, driven by the Housing Festival, represents a game-changing approach to addressing the city’s housing crisis, combining climate-smart and social rent housing solutions. In response to a chronic social housing deficit, with 18,000 people on the waiting list and over 1,000 families in temporary accommodation, the initiative focused on aggregating small brownfield sites across the city to enhance housing viability using Modern Methods of Construction (MMC). The initiative’s main goal was to demonstrate how aggregation of these sites could help create net-zero social homes on small plots that are often seen as unviable for traditional housing projects.

The housing system demonstrator aims to test this aggregation model by building 25 zero-carbon social rent homes across six small sites in Bristol, which would not have been feasible individually. A digital tool was developed to help identify these sites and assess their viability, while a collaborative multi-stakeholder approach — involving Bristol City Council, Atkins Realis, Edaroth, and Lloyds Banking Group — was key to moving from concept to implementation. The project’s unique approach also includes a redefined notion of ‘viability’, integrating social infrastructure investments alongside traditional capital repayment models.

The initiative’s innovative approach has garnered support for scaling through the Small Sites Aggregator program, which aims to unlock thousands of small, underutilized brownfield sites across the UK. This strategy is seen as a path towards building 10,000 homes annually and addressing wider housing shortages, with ongoing testing in cities such as Bristol, Sheffield, and London’s Lewisham Borough. Through this work, the Housing Festival has created the Social Housing at Pace Playbook, which outlines a replicable ecosystem solution to deliver affordable, climate-smart housing at scale. This initiative has demonstrated the potential for collaboration across sectors, innovative financing, and climate-conscious design to provide a pathway for cities worldwide facing similar housing challenges.Bristol’s Affordable Housing Initiative, driven by the Housing Festival, is an innovative model for tackling housing affordability through community-led co-design and collaborative financing. The initiative brought together local authorities, housing developers, social enterprises, and citizens to explore new ways of creating affordable, sustainable homes. The Housing Festival served as a platform for crowdsourcing ideas, testing alternative financial models, and showcasing eco-friendly building techniques. By blending public, private, and philanthropic investment, the initiative created a dynamic ecosystem that accelerates the delivery of affordable housing, prioritizing local engagement and long-term sustainability. This approach is revolutionizing how cities can rethink housing challenges by embedding innovation into the policy framework.

Looking forward: launching a global and distributed system demonstrator initiative

The first step in program alignment is the development of a System Demonstrator Grant Call, as part of the new Viability Fund for Cities. Building on the experiences of system demonstrators in Europe, Latin America and Africa, the ambition is to develop a new standard system demonstrator global grant call The first phase will prioritise Brazil, California, India, Sweden, Ukraine and selected global programmes. The goal is to create a shared practical framework that funders can adapt and apply in their own contexts to support system demonstrator initiatives, but which at the same time allows for joint learning, implementation, and demand side aggregation.

Between January and March 2026, three co-design meetings will be held, with drafting and review work taking place in between. Through this process, participating organisations will jointly develop a general, open source, call text and an operating and fundraising structure that can be used to launch coordinated calls for proposals in multiple countries. In April 2026, Viable Cities, Dark Matter Labs, UN-Habitat and other partners will reflect and deliberate on the outcomes of the dialogues to decide on the launch of an international call for system demonstrators.

Organisations interested in taking part in this collaborative process are invited to submit an expression of interest. Participation is flexible, and actors can step in or out at any time before March 2026.

Submit your expression of interest to join the co-design process and help shape the future of system demonstrator funding.

https://form.typeform.com/to/JOGXlMai

For more information, contact systemdemo@viabilityfund.org

Today, we’re taking a step back to look at the foundational methodology behind this entire initiative. How do you go about creating new models for collaboration when no blueprint exists? Our approach has been a “proof of possibility” — a live experiment where we, along with our ecosystem of partners, served as the primary test subjects.

In this post, the initiative’s co-stewards, Michelle and Annette, discuss the profound challenges and unique learnings that come from trying to build the plane while flying it.

Michelle: We wanted to reflect on the “proof of possibility” we ran, where we essentially decided to live prototype on ourselves with a small group of partners in a Learning Network. While it sounds simple, we learned it’s incredibly complex. You’re making decisions and sense-making within a specific prototype, but you’re also constantly trying to translate those learnings into something more generalised and applicable for others. In many ways, it’s a cool, experimental way of working, but it was also a bit of a nightmare.

Annette: It was very meta. In this proof of possibility, one of the things we were testing was a learning infrastructure for the ecosystem itself. So you’re testing learning within the experiment, while also prototyping the experiment, and then you have to step back and ask: what did we learn from this specific context versus what is context-agnostic and applicable elsewhere? Then there’s another layer: what did we learn about the wider external landscape and its readiness for this work? And finally, what did we learn about the process of learning about all of that? There’s this feeling of learning about learning about learning.

It’s representative of the fractal nature of this work. For instance, we were a core team working on our own governance while simultaneously orchestrating and supporting the ecosystem’s governance. The ecosystem itself was then focused on building capabilities of the system for many-to-many governance. It was navigating so many layers. On one hand, this has immense value because you’re looking at one question from multiple angles at once. On the other hand, it has been incredibly cognitively challenging.

Michelle: It’s that old adage of trying to build the plane whilst flying it — except there are no blueprints for the plane. I think the complexity we bumped into is probably present for anyone trying to do this kind of work, because everyone has to work at fractals all the time. So I was thinking, what are some things we bumped into, and how did we overcome them? The first breakthrough that comes to my mind was when we started to explicitly ask, “Are we talking about this specific prototype right now, or are we talking about the generalised model?” Just having that clear distinction, a shared vocabulary that the whole learning network could use, was a huge moment of alignment for us. It gave people a way to see we were working on at least two layers at the same time.

Annette: Yes and we found that the difference in thinking required for each of those layers was huge. Thinking through the specifics of what we did in one context versus pulling out principles applicable across all/any contexts was such a massive gear shift. Turning a specific example — “here’s something we tried” — into a generalised tool — “here’s something useful for others” — was probably a five-fold increase in workload, if not more. The amount of planning and thinking required was significantly different.

Michelle: What else comes up for you from this experience of prototyping on ourselves?

If nothing comes to mind, I can jump in. For me it was the dynamic of being the initiators. We were the ones who convened the group and set the mission. In these complex collaborations, the initiator tends to hold a lot of relational capital, power, and responsibility. This was exacerbated because we were managing all these different layers of learning. It centralised the knowledge and the relational dynamics back to us. If one of us was missing from a budget conversation, for example, it was difficult for others to proceed. For me, the bigger point is that to do good demonstration work, it has to be experimental and emergent. But that doesn’t come for free; it has downsides. This re-centralisation was one of them, and it was a lot for us to hold.

Annette: That makes me wonder if a certain degree of that centralisation is inevitable in organising for these kind of ‘proof of possibilities’. When something is this complex and emergent, you can only distribute so much, so early. To meet the real-time needs of the collaboration, you need an agile core team. This is where it gets interesting — we were operating in the thin space between a sandbox environment and a live context. It had to be a genuine live context for people to want to participate, but it was also a sandbox for testing the general model. You have to meet the timelines of the live context; you can’t just pause for six months to work out team dynamics, or the collaboration collapses. So you almost need a team providing strong leadership to hold both realities at once.

Michelle: So, would you do it the same way again?

Annette: I think if we did it again, the things we’ve learned would make it smoother. We’d be more explicit from the start about which layer we’re discussing. We’d have a better sense of how to capture live learning and translate it into a model as we go. When we started, most of our attention was on hosting the live context, and a lot of the synthesis happened afterwards. Having done it once, I’d be more conscious of doing that synthesis in real-time — though the cognitive lift to switch between those modes is still immense.

Michelle: I agree, I would do it again with those additions. The other thing is that when we started, we didn’t even really have the process that we wanted to go through. Now we do. We’ve learned more about what works. Starting fresh, we would have a decent sketch of a process to begin with. Not perfect, and you still have to wing it, but it’s a good start. I’d be interested to do it again and see what happens.

This meta-reflective process — learning about learning while doing — has been a central part of the Many-to-Many initiative creating a ‘Proof of Possibility’ as a way to learn about what’s possible at a system level. While navigating these fractal layers is cognitively demanding, it’s what allows for true emergence, distinguishing this deep, systemic work from simple chaos. It is a messy, challenging, and ultimately fruitful way to discover what’s possible.

In the Many-to-Many website [coming soon] you will find some resources based on what we did in the Proof of Possibility (Experimenter’s Logs and example methods and artefacts like the Contract) and some based on what might be applicable across contexts (a Field Guide, some tools and an overview of System Blockers we’ve encountered) along with case studies and top tips from other contexts in the learning network.

Thanks for following our journey. You can find our previous posts [here], [here] and [here] and stay updated by joining the Beyond the Rules newsletter [here].

Visual concept by Arianna Smaron & Anahat Kaur.

Many-to-Many: The Messy, Meta-Process of Prototyping on Ourselves was originally published in Dark Matter Laboratories on Medium, where people are continuing the conversation by highlighting and responding to this story.