School of Computer Science, University of Bristol, Bristol BS8 1UB, UK"/> Centre for Advanced Spatial Analysis, University College London, London W1T 4TJ, UK"/> School of Computing, Engineering & Intelligent Systems, Ulster University, Derry/Londonderry BT48 7JL, UK"/> School of Engineering Mathematics and Technology, University of Bristol, Bristol BS8 1TW, UK"/> Institute for Mathematical Innovation, University of Bath, Bath BA2 7AY, UK"/> School of Mathematics, Cardiff University, Cardiff CF24 4AG, UK"/> School of Social and Political Sciences, University of Glasgow, Glasgow G12 8RT, UK"/> School of Psychology, Cardiff University, Cardiff CF10 3AT, UK"/> Department of Psychology, University of Bath, Bath BA2 7AY, UK"/> Department of Mathematical Sciences, University of Bath, Bath BA2 7AY, UK"/> Department of Computer Science, University of Exeter, Exeter EX4 4QF, UK"/>
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2024 Volume 39
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RESEARCH ARTICLE   Open Access    

Artificial intelligence for collective intelligence: a national-scale research strategy

  • School of Computer Science, University of Bristol, Bristol BS8 1UB, UK

  • Centre for Advanced Spatial Analysis, University College London, London W1T 4TJ, UK

  • School of Computing, Engineering & Intelligent Systems, Ulster University, Derry/Londonderry BT48 7JL, UK

  • School of Engineering Mathematics and Technology, University of Bristol, Bristol BS8 1TW, UK

  • Institute for Mathematical Innovation, University of Bath, Bath BA2 7AY, UK

  • School of Mathematics, Cardiff University, Cardiff CF24 4AG, UK

  • School of Social and Political Sciences, University of Glasgow, Glasgow G12 8RT, UK

  • School of Psychology, Cardiff University, Cardiff CF10 3AT, UK

  • Department of Psychology, University of Bath, Bath BA2 7AY, UK

  • Department of Mathematical Sciences, University of Bath, Bath BA2 7AY, UK

  • Department of Computer Science, University of Exeter, Exeter EX4 4QF, UK

More Information
  • Abstract: Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or transnational scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by leveraging and amplifying AI for national-scale collective intelligence. The development and deployment of this kind of AI faces distinctive challenges, both technical and socio-technical. Here, a research strategy for mobilising inter-disciplinary research to address these challenges is detailed and some of the key issues that must be faced are outlined.
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    Seth Bullock, Nirav Ajmeri, Mike Batty, Michaela Black, John Cartlidge, Robert Challen, Cangxiong Chen, Jing Chen, Joan Condell, Leon Danon, Adam Dennett, Alison Heppenstall, Paul Marshall, Phil Morgan, Aisling O’Kane, Laura G. E. Smith, Theresa Smith, Hywel T. P. Williams. 2024. Artificial intelligence for collective intelligence: a national-scale research strategy. The Knowledge Engineering Review 39(1), doi: 10.1017/S0269888924000110
    Seth Bullock, Nirav Ajmeri, Mike Batty, Michaela Black, John Cartlidge, Robert Challen, Cangxiong Chen, Jing Chen, Joan Condell, Leon Danon, Adam Dennett, Alison Heppenstall, Paul Marshall, Phil Morgan, Aisling O’Kane, Laura G. E. Smith, Theresa Smith, Hywel T. P. Williams. 2024. Artificial intelligence for collective intelligence: a national-scale research strategy. The Knowledge Engineering Review 39(1), doi: 10.1017/S0269888924000110
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RESEARCH ARTICLE   Open Access    

Artificial intelligence for collective intelligence: a national-scale research strategy

  • School of Computer Science, University of Bristol, Bristol BS8 1UB, UK

  • Centre for Advanced Spatial Analysis, University College London, London W1T 4TJ, UK

  • School of Computing, Engineering & Intelligent Systems, Ulster University, Derry/Londonderry BT48 7JL, UK

  • School of Engineering Mathematics and Technology, University of Bristol, Bristol BS8 1TW, UK

  • Institute for Mathematical Innovation, University of Bath, Bath BA2 7AY, UK

  • School of Mathematics, Cardiff University, Cardiff CF24 4AG, UK

  • School of Social and Political Sciences, University of Glasgow, Glasgow G12 8RT, UK

  • School of Psychology, Cardiff University, Cardiff CF10 3AT, UK

  • Department of Psychology, University of Bath, Bath BA2 7AY, UK

  • Department of Mathematical Sciences, University of Bath, Bath BA2 7AY, UK

  • Department of Computer Science, University of Exeter, Exeter EX4 4QF, UK

  • Received: 02 July 2024
  • Revised: 31 October 2024
  • Accepted: 31 October 2024
  • Published online: 02 December 2024
The Knowledge Engineering Review  39,  2024, 39(1)  |  Cite this article

Abstract: Abstract: Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or transnational scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by leveraging and amplifying AI for national-scale collective intelligence. The development and deployment of this kind of AI faces distinctive challenges, both technical and socio-technical. Here, a research strategy for mobilising inter-disciplinary research to address these challenges is detailed and some of the key issues that must be faced are outlined.

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    Acknowledgments

    • This work was supported by UKRI EPSRC Grant No. EP/Y028392/1: AI for Collective Intelligence (AI4CI).

    • https://ai4ci.ac.uk.

    • https://www.gov.uk/government/news/bristol-set-to-host-uks-most-powerful-supercomputer-to-turbocharge-ai-innovation.

    • https://www.ukri.org/opportunity/host-sites-for-the-next-wave-of-uk-government-ai-infrastructure; N.B. this investment in hardware was subsequently withdrawn by the UK’s incoming Labour government: https://www.bbc.co.uk/news/articles/cyx5x44vnyeo.

    • https://www.ukri.org/what-we-do/how-we-work-in-ai/ukri-artificial-intelligence-centres-for-doctoral-training.

    • https://www.ukri.org/opportunity/artificial-intelligence-research-to-enable-uks-net-zero-target.

    • https://www.ukri.org/news/13-million-for-22-ai-for-health-research-projects.

    • https://www.ukri.org/news/54m-to-develop-secure-ai-that-can-help-solve-major-challenges.

    • https://www.ukri.org/news/100m-boost-in-ai-research-will-propel-transformative-innovations.

    • https://www.nesta.org.uk/report/future-minds-and-machines.

    • This characterisation of collective intelligence is strongly aligned with approaches developed within socio-technical systems research (Baxter & Sommerville, 2011).

    • ‘Planning for the future’, Department for Levelling Up, Housing and Communities, UK Government, 2023, https://www.gov.uk/government/consultations/planning-for-the-future/planning-for-the-future.

    • The term smart city is used here in two mutually reinforcing senses, first in the sense that novel smart technologies are physically incorporated into these cities, and second in the sense that these technologies underpin new kinds of ‘smart’ behavioural interactions within and across these cities at a range of different time scales (Batty et al., 2020).

    • For example, Data for Good: https://dataforgood.facebook.com; Smart Data Research: https://www.sdruk.ukri.org (formerly Digital Footprints); note the implicit challenges here related to (i) establishing and maintaining the public’s trust in, and engagement with, these potentially intrusive data collection efforts and (ii) countering the inevitable systematic biases that arise from unrepresentative sampling of the collective system as a whole.

    • https://www.gov.uk/government/news/ukhsa-publishes-investigation-findings-following-errors-at-the-private-immensa-lab.

    • For example, https://www.metoffice.gov.uk/research/approach/collaboration/ukcp, the UK Met Office’s Climate Projections dataset.

    • https://www.ipcc.ch/reports/.

    • https://www.gov.uk/government/publications/the-kalifa-review-of-uk-fintech.

    • https://www.fca.org.uk/firms/consumer-duty.

    • https://www.fca.org.uk/firms/innovation/digital-sandbox.

    • https://www.go-fair.org/fair-principles/.

    • https://digital-strategy.ec.europa.eu/en/library/assessment-list-trustworthy-artificial-intelligence-altai-self-assessment.

    • https://www.gov.uk/government/publications/ai-safety-institute-overview/introducing-the-ai-safety-institute.

    • https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai.

    • https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52021PC0206.

    • https://www.flowminder.org/.

    • https://www.gov.uk/government/publications/national-security-and-investment-act-guidance-on-notifiable-acquisitions.

    • https://www.gov.uk/government/organisations/research-collaboration-advice-team.

    • https://www.ey.com/en_us/consulting/businesses-can-stop-rising-ai-use-from-fueling-anxiety.

    • One theoretical framework with promising potential to support and inter-relate the challenges being considered here is that offered by studies in cumulative cultural evolution (Smaldino 2014; Mesoudi & Thornton 2018).

    • There is some debate as to whether notions of ‘trust’ and ‘trustworthiness’ are appropriate for framing the legitimacy of AI systems; compare, for example, the work of Andras et al. (2018) with the position of Bryson (2018). Even the use of a term like ‘guidance’ to describe the kind of support that AI systems might be designed to offer can be reminiscent of previous attempts to shift public behaviour through the ‘libertarian paternalism’ of nudge economics, an approach that was discredited precisely because of its tendency to disempower or even coerce people rather than fully inform or partner with them (Goodwin 2012).

    • https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai.

    • https://ai4ci.ac.uk/themes/.

    • https://ai4ci.ac.uk/events/.

    • https://ai4ci.ac.uk/funding/.

    • https://www.nesta.org.uk/report/future-minds-and-machines/.

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    • This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
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    Seth Bullock, Nirav Ajmeri, Mike Batty, Michaela Black, John Cartlidge, Robert Challen, Cangxiong Chen, Jing Chen, Joan Condell, Leon Danon, Adam Dennett, Alison Heppenstall, Paul Marshall, Phil Morgan, Aisling O’Kane, Laura G. E. Smith, Theresa Smith, Hywel T. P. Williams. 2024. Artificial intelligence for collective intelligence: a national-scale research strategy. The Knowledge Engineering Review 39(1), doi: 10.1017/S0269888924000110
    Seth Bullock, Nirav Ajmeri, Mike Batty, Michaela Black, John Cartlidge, Robert Challen, Cangxiong Chen, Jing Chen, Joan Condell, Leon Danon, Adam Dennett, Alison Heppenstall, Paul Marshall, Phil Morgan, Aisling O’Kane, Laura G. E. Smith, Theresa Smith, Hywel T. P. Williams. 2024. Artificial intelligence for collective intelligence: a national-scale research strategy. The Knowledge Engineering Review 39(1), doi: 10.1017/S0269888924000110
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