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At the Centre for Collective Intelligence Design, we focus on the practical skills and knowledge needed to bring humans and technology together in a way that enables groups to become smarter than the sum of their parts, and to mobilise human intelligence at greater scale. Find out about the experiments we are supporting in designing collective intelligence for social good.

In September 2018 we launched the first round of the Collective Intelligence Grants, offering up to £20,000 for experiments that advance knowledge on how to design and apply collective intelligence to solve social problems.

Find out about our twelve winning experiments from around the globe.

Improving collective decision-making

With society’s most pressing challenges becoming increasingly complex, opinions more and more polarised, and solutions more difficult to agree on, it is more important than ever to find new ways of thinking and acting together.

  • Unanimous AI, a technology company based in San Francisco, will test whether algorithms modelled on ‘swarm’ behaviour in bees and fish can enable groups with conflicting political views to find collectively acceptable solutions.
  • fanSHEN, a Newcastle-based theatre company, will investigate the importance of empathy and metacognition skills for group decision-making, and will test how such social skills can be fostered through immersive storytelling.
  • ISTC-CNR, the Italian National Research Council’s Institute of Cognitive Sciences and Technologies, will test whether artificial agents can mitigate the bias of social influence in collective decision-making.
  • The Artificial Intelligence Lab at the Vrije Universiteit Brussel will look into whether introducing artificial agents will change people’s behaviour in discussions about collective risks, such as climate change.

Making better use of the insights generated through collective intelligence

As the volume of data generated by crowds increases, so do the challenges of navigating and analysing it. This means that its full potential may go unrealised.

Four of our experiments will use machine learning to unlock new insights in large volumes of citizen-generated data. They will also explore how this changes its uptake and use to address social problems.

  • The Alan Turing Institute will test whether natural language processing is a useful technique to cluster similar proposals from ‘like minded citizens’ on a digital democracy platform, so that citizens on the platform with shared interests can work together more effectively.
  • HURIDOCS, a human rights organisation based in Switzerland, will look into whether machine learning can increase the efficiency of human rights defenders in curating large collections of documents.
  • Belgium-based company CitizenLab will use machine learning technologies to translate unstructured citizen-generated ideas and insights on digital democracy platforms into actionable policy recommendations for public authorities.
  • Swansea University will test whether using machine learning to classify and organise crowdsourced footage of airstrike images increases the uptake of such open-source digital evidence by legal practitioners in court.

Increasing the effectiveness and participation of citizens in collective intelligence initiatives

The success of collective intelligence initiatives often depends having an engaged crowd. How can we make sure that people are motivated to take part in collective intelligence initiatives, and what does it take to make their participation as effective as possible?

  • The University of Southampton will test different strategies to sustain crowd analysis of drone footage in humanitarian and emergency response efforts.
  • The University of Edinburgh will compare two types of intelligent recommendation algorithms on a citizen science platform to make it easier for citizen scientists to discover the projects that best match their interests and capabilities.

New use-cases for collective intelligence

At the Centre for Collective Intelligence Design, we’ve been studying how collective intelligence is helping to address environmental issues, improve health and deliver better democracy. We believe collective intelligence has the potential to help solve many of the the most pressing issues we face today. Two of our experiments will test new use-cases for collective intelligence - in education and tackling urban food waste.

  • The Hong Kong Baptist University will test whether using a collective intelligence platform can support the coordination of food rescue activities by volunteers in Hong Kong.
  • The Behavioural Insights Team, a social purpose company based in London, will be using data from online maths assessment platform Eedi to see if collective intelligence can uncover new insight into effective teacher feedback.

Over the next ten months, the people behind the experiments will be working on generating new insights into human-machine collaboration; shedding light on how the world looks to others; and on producing results that will be relevant and useful to collective intelligence practitioners and academics alike.