Shapes that Aldo Van Eyck used in his playground designs

Recurring patterns for designing playgrounds. Image used with permission from the Aldo van Eyck Archive

If you compare climate change and nuclear war, a lack of humanitarian innovation and a slowdown in scientific discovery, or technology in education and in transport, you might think that these problems are very different from one another. But take a step back and identify what's causing them, and you’ll find they follow similar patterns. We call these patterns problem archetypes.1 Identifying these archetypes can help us identify types of solutions that work across many similar problems.

We’ve been keeping track of problem archetypes as we notice them, and we’re sharing them here as a starting point for developing a more comprehensive list.

So far, we’ve identified eight different problem archetypes. These include:

  1. Lack of knowledge about a problem
  2. Disagreement about values
  3. Lack of potential solutions or evidence of their effectiveness
  4. Insufficient or badly-structured funding
  5. Skill shortages
  6. Misaligned incentives
  7. Missing infrastructural organisations
  8. Coordination problems

1. Lack of knowledge about a problem

If we don’t know a problem exists, we can’t make deliberate progress on solving it. Sometimes discovering the problem leads quickly to action, as when the 1985 discovery of the hole in the ozone layer led to the 1987 Montreal Protocol limiting ozone-depleting substances.

But sometimes this process isn’t so simple. Although smoking was suggested as a major cause of lung cancer in the early 20th century, it took multiple lines of evidence developed over the following decades to prove it in the 1940s and 50s. It took several decades more to convince doctors, politicians, and the public of the problem, in large part because of campaigns by the tobacco industry.

2. Disagreement about values

Sometimes people don’t see something as a problem because of their values. Differences in values are key reasons for disagreement over whether factory farming, economic inequality, and abortion are important problems.

Values also affect people’s approaches to solving problems. For example, anticapitalist climate campaigners often disagree with proposals such as carbon taxes, arguing for a more radical reconfiguration of the economy.

3. Lack of potential solutions or evidence of their effectiveness

In the early stages of solving a problem, there may be a lack of ideas of what to do to get started. The burgeoning field of AI policy is going through this right now: actors in this field are working to identify the different facets of the problem, and propose initial solutions, but there isn't yet consensus over where efforts should be focused.

Later on, there may be plenty of solutions, but inadequate evidence as to what will work best. A lack of good evidence is one of the most common issues we come across. For example, Steve Higgins, Professor of Education at Durham University, says “Most things in education, we have no idea whether they work.” This issue even affects areas with relatively good evidence, such as medicine. For example, many evidence-based medical guidelines have limited applicability when patients have more than one condition.

4. Insufficient or badly-structured funding

Some problems lack sufficient funding. For example, an IPCC report suggests that to limit global warming to 1.5°C we need a $2.4 trillion investment in the energy system every year between 2016 and 2035, which is about 2.5% of global GDP.2 But 2016 saw a global $455 billion spend on addressing climate change overall, which is only 19% of the IPCC recommended investment.

Often there is insufficient funding because a problem affects people who can’t pay for solutions. For example, because snakebite mainly affects poor people in the developing world, there isn’t a big enough financial incentive to make antivenom for them. Similarly, the future people affected by climate change are unable to pay us to prevent it. If they could, there would be much more motivation for people to solve the problem now.

Funding amount is not the only problem - how it is allocated also matters. For example, the humanitarian sector is hampered by funders who are risk-averse, inflexible, and give short-term grants. There is a similar situation in science funding, which constrains research.

The nonprofit sector, in general, suffers from problems with the structure of funding. Donors often prefer charities with low administrative (aka overhead) costs. But this can make it difficult for charities to operate effectively. Another difficulty for charities arises when donors restrict their funding to a particular programme, rather than giving the charity a grant that can be used on any part of their work. This can fragment charities’ strategies.3

5. Skill shortages

Money is not the only resource constraint. Skill is another major one. For example, the humanitarian sector struggles with scaling innovations partly because there is a lack of skill on scale in the sector. In EdTech, teachers and school leaders often lack the expertise to properly evaluate EdTech. In the low-income countries, there is a shortage of many skilled professionals such as psychiatrists.

6. Misaligned incentives

Even if there are incentives to solve a problem, they can be misaligned. This often happens in situations where it is difficult to measure and incentivise what we want, but decisions are made based on these flawed metrics anyway.4 For example, judging teachers based on student’s exam results does fit with the goal of education, but too much emphasis on this metric can lead to teaching to the test.

7. Missing infrastructural organisations

Fields that form to tackle a problem often benefit from the involvement of organisations that provide the field with infrastructural services. Rather than working directly on the problem, these organisations help by coordinating work, developing and sharing evidence, and building networks.5 For example, in global health, there is the Disease Control Priorities Project, which reviews the evidence on interventions to address disease in low-resource settings.

The development of a new type of infrastructural organisation can have a big impact on a field. For example, startup accelerators have become a major part of the tech startup ecosystem, beginning with Y Combinator in 2005. In charity funding, the charity evaluator GiveWell has had a big impact – it estimates that it influences ~$150 million per year in donations.

8. Coordination problems

Sometimes, people want to take action on a problem, but doing so would put them at a disadvantage compared to others. Without a way to trust each other, it’s difficult for any of the parties to take action. For example, this occurs in climate change, where “other industrialized nations such as the USA (as well as Australia and Canada) have balked at taking action for fear of ‘free riding’ on the part of major developing nations who have become trade competitors.”6

Building on this list

Once we build up our understanding of each problem archetype, we plan to draw on fields like systems science, the economics of market failure, and the study of coordination and cooperation to think about corresponding types of solutions that funders and other actors can develop to address these.

But for now, know of any problem archetypes we’ve missed? Drop us a line at goodproblems@science-practice.com

References

  1. This is a similar idea to Daniel Kim’s System Archetypes. While his approach is focussed on any kind of problem, ours is focussed specifically on large-scale problems that altruistically-motivated people might want to solve. His approach is also rooted more in systems science, whereas we draw on our own experience. We plan to investigate the systems approach more and may incorporate it into our problem archetypes analysis. 

  2. “Global model pathways limiting global warming to 1.5°C are projected to involve the annual average investment needs in the energy system of around 2.4 trillion USD 2010 between 2016 and 2035, representing about 2.5% of the world GDP” p. 24 of the IPCC report Global Warming of 1.5°C 

  3. p. 155 of Money Well Spent

  4. The book The Tyranny of Metrics gives many examples of misaligned incentives caused by poor use of metrics. 

  5. Similar to the idea of field-building intermediaries outlined in the article When Building a Field Requires Building a New Organization 

  6. Why Climate Change Collective Action has Failed and What Needs to be Done Within and Without the Trade Regime 

Identifying the right problem to solve is an important part of having an impact, but it’s a hard task. Lists of clearly-described problems offer a starting point for finding the right one. They can also help organisations and individuals coordinate around a set of common priorities, as has happened with the UN Sustainable Development Goals

This is why we’ve been working on what we call problem briefs. These are short documents where we describe a problem, evaluate how important it is, and suggest what a philanthropic funder could do to help solve it. We’d like to develop these into a resource where people can explore problems and see how they could contribute towards solving them. We’ve looked for other organisations doing similar work, and wanted to share what we found:

Developing these kinds of resources is part of a wider project that many organisations are independently working on: finding, understanding, and prioritising problems to work on. We’d like to see more of a unified field develop around this kind of work. A first step towards this would be for organisations to share their work so others can build on it. For example, we’d encourage foundations to publish their analyses of problems, which they often keep as internal documents.

In the longer run, we like Bret Victor’s vision of tools for problem-finding. When thinking about how an engineer might find climate change problems to work on, he suggests that she needs “a tool that lets her skim across entire fields, browsing problems and discovering where she could be most useful.” This is not just something that engineers need - anyone wanting to have a large positive impact would benefit from a tool like this.

Thinking about the future is important for taking effective action in the present. While futures thinking by specialists and elites can be useful, it risks not taking account of the knowledge and values of the public. The field of participatory futures aims to correct this by developing democratic and inclusive processes for people to explore and develop the futures they want.

With this goal in mind, Nesta have been exploring the idea of participatory futures, and have collected many examples of how it can be done. A report currently being developed will push this further. It will clarify what participatory futures is and share available best practice and methods. We have done some initial thinking in this area as well and would like to contribute our findings to this work. In this post, we will outline a series of observed trends that are relevant to participatory futures, propose a way of categorising different methods depending on what one is trying to achieve, and share some future lines of inquiry.

Political and social trends provide new opportunities for the use of participatory methods, and new technologies offer new ways of participating. Digital tools can help scale participatory futures across large populations and can enable access to rich, interactive visions of the future.

Through our initial research, we came across the following interesting trends in participatory futures.

Collective intelligence

The field of collective intelligence could provide new ways of doing participatory futures that combine the capabilities of groups of people with machines. Emerging technologies such as machine learning help make this more possible. An example of this is Climate CoLab, an open problem-solving platform from MIT aimed at exploring and solving complex problems.

Example methods: hybrid forecasting, collaborative argument-mapping software.

Participatory governance

Movements around participatory local governance are gaining prominence, and are using digital technology to help with this. For example, the municipalist movement is a radical movement that seeks to build bottom-up forms of governance using participatory methods. For example, participatory budgeting projects in Paris, Madrid, and Mexico City have used digital methods. One such tool is Empatia, which provides an environment to test out participatory systems.

Example methods: citizens assemblies, participatory budgeting.

Immersive experiences

There is a strand of futures work that puts people in immersive environments so that they can experience the future and use that experience as a stimulus for thought. Emerging technologies such as virtual and augmented reality (VR and AR) are making these experiences much more immersive and can support more constructive discussions about the future. For example, VR and AR have been used in facilitating participatory urban planning decisions. Games also help with immersiveness. For example, IMPACT is a game where participants play different roles in the future and see how future changes could impact those roles. The Block by Block project uses the Minecraft game as a space for children to participate in designing their environment.

Example methods: serious games, speculative design, VR-enabled participatory urban planning.

Creative activism

There has been a trend towards using creative methods in activism. Not all of this is futures-focussed, but some is. For example, temporary autonomous zones such as Burning Man or Freetown Christiania in Copenhagen provide an enclave for a new way of living without having to change the whole of society.

Example methods: temporary autonomous zones, prefigurative intervention, legislative theatre.

Focusing participation on neglected voices

Although all participatory futures methods aim to widen participation, some are particularly focussed on including people that tend to be neglected in discussions about the future. For example, MH:2K involves young people in mental health work as citizen researchers. Similarly, the Guardian’s Gene Gap project involves five different UK communities to help identify different stories to tell about gene editing. Afrofuturism uses science fiction to imagine and explore science, technology, and cultures of the future from the perspectives of the African diaspora.

Example methods: citizen journalism, citizen science, participatory international development.

What types of participatory futures methods are there?

The abundance of different methods for engaging people in conversations about the future makes choosing an appropriate method challenging – where to begin? You could start by asking yourself two questions: Which type of question are you asking about the future? And which actors will be driving the process?

Type of question Ask Example outputs
Predictive What kind of future can we expect? Predictions, scenarios, trends
Value-based What kind of future do we want? Values, visions, ideologies, speculative design
Strategic How can we get the future we want? Plans, strategies
Driving actors Who initiates the process? Who controls the process?
Top-down Traditional authorities (e.g., local governments) The initiating authority
Bottom-up Members of the public The public


Together, these two variables form a framework in which we can place methods.

Predictive Value-based Strategic
Top-down Forecasting competitions
Crowdsourcing platforms
Speculative design
Citizens' assembly
21st century town meetings
Participatory backcasting
Bottom-up Betting markets Temporary autonomous zones
Prefigurative politics
Legislative theatre
Online petitions


In addition to the type of question and driving actors that form these categories, there are several other variables that it might be useful to consider:

  1. What are participants contributing? There are a wide variety of inputs that people could contribute, such as: prediction, observation, knowledge, value, goal, preference, concern, theory, vision, or framing.
  2. Design of the process. The design of the process considers how people will be brought together and think together about the future. It will include: how participants are selected, how they participate and contribute, how they are coordinated, what the output of the process is, how this output is used.
  3. Practical considerations. There are also practical variables such as: money and time cost of running the process, time and energy required from participants, knowledge requirements for participation, political complexity of the topic.

Where next?

This post summarises some initial ideas based on a small amount of research; more in-depth research will challenge and refine them. Further work could also explore:

  • What can we learn from the long history of participatory methods more broadly?
  • What outcomes do we want from participatory futures, and how do we measure them and build up an evidence base?
  • How do we ensure that participatory futures methods are genuinely participatory, and are not co-opted by powerful groups and individuals?
  • Which futures tasks are most suited to participatory methods, vs expert methods? How can experts and the public work together most effectively?

Interested in learning more about participatory futures? You could start by checking out Participedia, a repository of participatory projects and methods. Beautiful trouble similarly presents a database of creative activism techniques. Involve’s participation knowledge base has a wealth of information related to participatory methods. And finally, we’ve also made our own research spreadsheet available for you to download and modify as you wish.

Getting a better understanding of participatory futures methods is an important part of the wider project of democratising futures thinking. We’re glad that Nesta is pushing this field forward and are excited to see further work in this area.

We helped the Humanitarian Innovation Fund translate research into actionable next steps for the humanitarian sector.

Research often leads to piles of information that are hard to act on. If you write this information up without synthesising and communicating it effectively, you will end up with an ineffective report. Because of this, we focus intensively on synthesis and communication in all of our work.

We recently did this kind of synthesis work for Elrha’s Humanitarian Innovation Fund (HIF). They support organisations developing innovations in humanitarian assistance and they’ve noticed that it's often difficult to scale these innovations. They wanted to write a report to help the humanitarian sector understand why scaling is difficult and take action to enable it. We helped them translate their experience and research findings into a set of clear and actionable challenges for the humanitarian sector.

Using challenges to structure thinking

We structured the report around challenges because they are a good way to stimulate action. Challenges are brief statements of a problem, the reasons for the problem, and how it might be solved. They help the reader quickly understand the situation and provide focus for a community of practitioners.

We based our challenges on research that had identified barriers to scale and recommendations for the sector. This research drew on the HIF’s experience in helping innovators scale their projects and on research carried out by Spring Impact, who are experts in scaling social innovation. We analysed this research and proposed a set of challenges and a structure for the report that we refined with the HIF team.

Five key challenges stood out:

  • Too few humanitarian innovations are geared to scale
  • The humanitarian sector has insufficient embedded knowledge and skills for supporting innovations to scale
  • There is a lack of appropriate and adequate funding for scaling innovation in the sector
  • There is insufficient evidence of the impact of humanitarian innovations
  • The humanitarian ecosystem significantly frustrates efforts to scale humanitarian innovation

We developed the following structure to describe each challenge:

  • Barriers: What is causing the challenge and what are the consequences?
  • Current activity: What is the humanitarian sector currently doing about this challenge?
  • Calls to action: What do different humanitarian actors need to do at both an operational and systemic level to address this challenge?
  • Questions for the sector to consider: A series of provocations to encourage the sector to think differently about the challenge.

This structure gives humanitarian actors an understanding of the challenge, provides detail on what’s causing it, and gets them thinking about how they can solve it.

Opening up conversations

It might seem trivial, but something as simple as how research or insights are framed can shape the kind of conversations they enable. Identifying limitations and barriers is important, but advancing informed proposals on what needs to happen to address them can generate much more meaningful conversations.

This report represented an opportunity for the HIF to reflect on their work and consolidate their position as a leader in humanitarian innovation. By articulating concrete challenges and next steps for the sector, they now have a valuable tool they can use to work with stakeholders to unlock the systemic change needed to help innovations to scale.

To learn more about Too tough to scale? Challenges to scaling innovation in the humanitarian sector read the full report here.

What if starting a science venture were as easy as starting a digital one?

In March, we spoke at SXSW 2018 about the kind of support and initiatives that could make it easier for scientists to build successful science-based startups outside of industry and academia. We brought together a panel that talked about the role of an engaged community, shared lab spaces and facilities, venture programmes, and funding.

🎙️ Listen to the audio recording of our SXSW panel here or carry on reading for the key points & updates since.

An ecosystem for science ventures

Becoming an entrepreneur and starting your own digital company is now a common and accessible career option. That’s because, over the past decade, a lot of time and resources have gone into creating programmes, spaces, events and funding opportunities for people to come up with ideas, explore and grow them. The same is now happening for science-based startups.

We have been seeing this in the UK with the emergence of deep-tech focused accelerators and incubators, shared lab space and equipment, events and networking opportunities for scientists looking to start their own businesses, and funders turning to science innovation to increase their impact (and return). But most of these are nascent and often isolated from one another. We wanted to start a conversation to raise awareness of these different initiatives and to start thinking about them as part of a broader system — a system aimed to incentivise and empower scientists to build their own science ventures. Speaking at SXSW offered the perfect opportunity to do so.

South by Southwest (SXSW) is an exciting 10-day conference known for its fantastic diversity of cultural, political and technological events. This year, we added science to the mix. Our panel featured:

  • Gemma Milne, co-founder at Science Disrupt — an organisation whose goal is to promote scientific innovation;
  • Harry Destecroix, founder at Unit DX — the UK’s first independent science incubator;
  • Dominic Falcão, co-founder at Deep Science Ventures — a science-focused venture builder;
  • Ana Florescu, head of our Good Problems team — working with science and innovation funders to develop problem-driven programmes.

Ecosystem components

We discussed four ecosystem aspects — community, facilities, venture programmes, and funding. Below we provide a brief description of how these differ for science ventures and provide a couple of UK example initiatives.

1. A community of like-minded people 

If you’re an entrepreneur looking to start a digital company, there’s a wide range of events, communities and conferences you can join to help meet potential collaborators, investors, and test your ideas. If you’re a scientist looking to set up a science business outside of academia or industry, your options are limited (although the Hello Tomorrow conference deserves a worthy mention here). 

It was this gap that Gemma Milne and Lawrence Yolland tried to fill when they created Science: Disrupt — an organisation connecting innovators, iconoclasts and entrepreneurs interested in creating change in science. They have an online slack community with around 800 members, they produce podcasts, write editorials, and run events, all intended on sharing existing initiatives in this space, raising awareness of opportunities available for scientists beyond academia and industry. As part of the panel, Gemma talked about the value of having spaces where entrepreneurs can meet like-minded people, exchange ideas, and learn from each other.

2. Physical spaces for scientists to experiment and build their ideas

To create a digital startup you need a laptop and internet. To build a science startup you will most likely need a lab and equipment. Organisations like the London BioHackspace and Clustermarket are making it easier for science entrepreneurs to access the equipment and skills needed to test ideas.

As co-working spaces have demonstrated for digital startups, there is a significant added value in having different entrepreneurs working in the same space, sharing lessons, networks and expertise. These flexible shared work spaces and facilities are currently limited for science entrepreneurs. 

Whilst founding Ziylo, a novel glucose monitoring tech, Harry Destecroix encountered the same problem in terms of lack of facilities for scientific spin-offs from local universities. So he set one up. Unit DX is the UK’s first independent science incubator, and now houses 18 early-stage science companies ranging from quantum to biotech startups. Harry talked about setting up Unit DX and empowering scientists to start their own companies.

3. Venture programmes tailored to science innovation

Going through an accelerator or incubator programme has become part of the regular journey for a digital startup. But programmes designed to support science ventures are still nascent. Examples include RebelBio – the world’s first life sciences accelerator, the BioCity incubators, and Deep Science Ventures (DSV). 

DSV is a hypothesis-led venture builder that aims to create science companies from scratch. Modelled on the Entrepreneur First approach, twice a year they select a multidisciplinary group of elite scientists and engineers and support them in starting high-impact science companies. Dominic Falcão, co-founder at DSV, talked about what a minimum viable product looks like for a science startup and how they’re trying to manage funder and VC expectations when it comes to investing in deep-tech companies (they’ve also written a great piece on this here).

4. Problem-led funding opportunities and support

Innovation funds tend to be skewed towards digital solutions. That means that funders can start seeing solutions quite soon after investing, but the downside is that these often have a limited impact. In an attempt to maximise this impact, funders are increasingly looking at more complex problems that would benefit from science innovation.

Our Good Problems team works with such science and innovation funders. We help them identify relevant challenges and design incentives that can both motivate and support scientists in developing solutions — whether by running prizes, funding calls or offering access to mentors, training or lab space. Ana Florescu, our team lead, talked about the value of good problems and how they can provide an opportunity for scientists to turn their ideas into impactful ventures.

What next?

We’re keen to keep the conversation going and see how we can contribute to building a supportive ecosystem for science entrepreneurs. Here’s what we’ve been up to since the panel:

  • Science Disrupt — Recently launched a new podcast series on ‘Responsible Science’. First two episodes are out, so start listening!
  • Deep Science Ventures — Contributed to The House of Lords Science and Technology Committee’s report “Life Sciences Industrial Strategy: Who’s driving the bus?” and to the CBRE report “Life Sciences: Opportunity Under The Microscope”. And Dom was on a podcast!
  • Unit DX — In April, they hosted the BrisSynBio, a 4-Day MBA designed for budding entrepreneurs, from postgraduates to seasoned academics, interested in starting a synthetic biology-rich business in the biotechnology or life sciences sectors (more here).
  • Good Problems team — We’re currently working on turning our Playbook into a resource for science entrepreneurs and funders interested in finding good problems. If you’d like to find out more, please get in touch!

🎙️ Reminder – You can listen to our full SXSW2018 panel discussion here. Enjoy!

Looking for a good problem?

We are a close team of designers and researchers who are passionate about tackling ambitious and important problems. If you’re looking to grow your impact, we’d love to hear from you!