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  Smith; Theresa Smith; Hywel Williams

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 Smith, Theresa Smith, Hywel Williams

Research output: Contribution to journal › Article › 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 trans-national 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 language	English
Pages (from-to)	1-24
Journal	The Knowledge Engineering Review
Early online date	9 Nov 2024
Publication status	Published online - 9 Nov 2024

Keywords

AI,
societal challenges,
collective intelligence

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Embargoed Document

AI4CI_KER_2024_accepted
Author Accepted Manuscript, 4.96 MB
Licence: CC BY-NC-ND
Embargo ends: 4/05/25

Embargoed Document

published version
Final published version, 9.41 MB
Licence: CC BY
Embargo ends: 9/05/25

Cite this

Bullock, S., Ajmeri, N., Batty, M., Black, M., Cartlidge, J., Challen, R., Chen, C., Chen, J., Condell, J., Danon, L., Dennett, A., Heppenstall, A., Marshall, P., Morgan, P., O'Kane, A., Smith, L., Smith, T., & Williams, H. (2024). Artificial Intelligence for Collective Intelligence: A National- Scale Research Strategy. The Knowledge Engineering Review, 1-24. Advance online publication.

@article{d52d145bf9714799814aed397c717e87,

title = "Artificial Intelligence for Collective Intelligence: A National- Scale Research Strategy",

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

keywords = "AI,, societal challenges,, collective intelligence",

author = "Seth Bullock and Nirav Ajmeri and Mike Batty and Michaela Black and John Cartlidge and Robert Challen and Cangxiong Chen and Jing Chen and Joan Condell and Leon Danon and Adam Dennett and Alison Heppenstall and Paul Marshall and Phil Morgan and Aisling O'Kane and Laura Smith and Theresa Smith and Hywel Williams",

year = "2024",

month = nov,

day = "9",

language = "English",

pages = "1--24",

journal = "The Knowledge Engineering Review",

issn = "0269-8889",

publisher = "Cambridge University Press",

}

TY - JOUR

T1 - Artificial Intelligence for Collective Intelligence: A National- Scale Research Strategy

AU - Bullock, Seth

AU - Ajmeri, Nirav

AU - Batty, Mike

AU - Black, Michaela

AU - Cartlidge, John

AU - Challen, Robert

AU - Chen, Cangxiong

AU - Chen, Jing

AU - Condell, Joan

AU - Danon, Leon

AU - Dennett, Adam

AU - Heppenstall, Alison

AU - Marshall, Paul

AU - Morgan, Phil

AU - O'Kane, Aisling

AU - Smith, Laura

AU - Smith, Theresa

AU - Williams, Hywel

PY - 2024/11/9

Y1 - 2024/11/9

N2 - Advances in artificial intelligence (AI) have great potential to help address societal challengesthat are both collective in nature and present at national or trans-national scale. Pressingchallenges in healthcare, finance, infrastructure and sustainability, for instance, might all beproductively addressed by leveraging and amplifying AI for national-scale collective intelligence.The development and deployment of this kind of AI faces distinctive challenges, both technicaland socio-technical. Here, a research strategy for mobilising inter-disciplinary research to addressthese challenges is detailed and some of the key issues that must be faced are outlined.

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

KW - AI,

KW - societal challenges,

KW - collective intelligence

M3 - Article

SN - 0269-8889

SP - 1

EP - 24

JO - The Knowledge Engineering Review

JF - The Knowledge Engineering Review

ER -

Artificial Intelligence for Collective Intelligence: A National- Scale Research Strategy

Abstract

Keywords

UN SDGs

Embargoed Document

Embargoed Document

Fingerprint

Cite this