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

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

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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.

Original languageEnglish
Article numbere10
Number of pages23
JournalThe Knowledge Engineering Review
Volume39
DOIs
Publication statusPublished - 2 Dec 2024

Bibliographical note

Publisher Copyright:
© The Author(s), 2024.

Research Groups and Themes

  • Intelligent Systems Laboratory

Keywords

  • cs.AI
  • cs.CY

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  • 8459 AI For Collective Intelligence

    Bullock, S. (Principal Investigator)

    1/02/2431/01/29

    Project: Research, Parent

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