Mind the gap: connecting AI innovation to widespread public value

Neil D. Lawrence; Jessica K. Montgomery

doi:10.1093/scipol/scag070

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Mind the gap: connecting AI innovation to widespread public value

Neil D. Lawrence, Jessica K. Montgomery

Science and Public Policy, 2026.

Abstract

Public dialogues have produced clear demand signals for AI. These dialogues imagine innovations that improve our shared wellbeing and prosperity while developing under democratic control. AI development has largely advanced along another trajectory. We argue that this gap is a structural feature of an innovation system whose incentives are captured by the attention economy. Closing it requires a different driver of the innovation cycle. We propose an attention reinvestment cycle, in which efficiency gains accrue as freed time that can be invested in community innovation, with frontline professionals adapting and sharing tools that meet priority needs. Operating the cycle at scale requires institutional infrastructure—dialogic, absorptive, and distributive capacities—that the existing science-policy system has yet to develop.

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Cite this Paper

BibTeX


@Article{publications/mind-the-gap-connecting-ai-innovation-to-widespread-public-value,
  title = 	 {Mind the gap: connecting AI innovation to widespread public value},
  author = 	 {Lawrence, Neil D. and Montgomery, Jessica K.},
  journal =      {Science and Public Policy},
  year = 	 {2026},
  doi = 	 {10.1093/scipol/scag070},
  url = 	 {/publications/mind-the-gap-connecting-ai-innovation-to-widespread-public-value.html},
  abstract = 	 {Public dialogues have produced clear demand signals for AI. These dialogues imagine innovations that improve our shared wellbeing and prosperity while developing under democratic control. AI development has largely advanced along another trajectory. We argue that this gap is a structural feature of an innovation system whose incentives are captured by the attention economy. Closing it requires a different driver of the innovation cycle. We propose an attention reinvestment cycle, in which efficiency gains accrue as freed time that can be invested in community innovation, with frontline professionals adapting and sharing tools that meet priority needs. Operating the cycle at scale requires institutional infrastructure—dialogic, absorptive, and distributive capacities—that the existing science-policy system has yet to develop.
}
}

Endnote

%0 Journal Article
%T Mind the gap: connecting AI innovation to widespread public value
%A Neil D. Lawrence
%A Jessica K. Montgomery
%J Science and Public Policy
%D 2026	
%F publications/mind-the-gap-connecting-ai-innovation-to-widespread-public-value
%R 10.1093/scipol/scag070
%U /publications/mind-the-gap-connecting-ai-innovation-to-widespread-public-value.html
%X Public dialogues have produced clear demand signals for AI. These dialogues imagine innovations that improve our shared wellbeing and prosperity while developing under democratic control. AI development has largely advanced along another trajectory. We argue that this gap is a structural feature of an innovation system whose incentives are captured by the attention economy. Closing it requires a different driver of the innovation cycle. We propose an attention reinvestment cycle, in which efficiency gains accrue as freed time that can be invested in community innovation, with frontline professionals adapting and sharing tools that meet priority needs. Operating the cycle at scale requires institutional infrastructure—dialogic, absorptive, and distributive capacities—that the existing science-policy system has yet to develop.

RIS


TY  - JOUR
TI  - Mind the gap: connecting AI innovation to widespread public value
AU  - Neil D. Lawrence
AU  - Jessica K. Montgomery
DA  - 2026/10/08	
ID  - publications/mind-the-gap-connecting-ai-innovation-to-widespread-public-value
DO  - 10.1093/scipol/scag070
UR  - /publications/mind-the-gap-connecting-ai-innovation-to-widespread-public-value.html
AB  - Public dialogues have produced clear demand signals for AI. These dialogues imagine innovations that improve our shared wellbeing and prosperity while developing under democratic control. AI development has largely advanced along another trajectory. We argue that this gap is a structural feature of an innovation system whose incentives are captured by the attention economy. Closing it requires a different driver of the innovation cycle. We propose an attention reinvestment cycle, in which efficiency gains accrue as freed time that can be invested in community innovation, with frontline professionals adapting and sharing tools that meet priority needs. Operating the cycle at scale requires institutional infrastructure—dialogic, absorptive, and distributive capacities—that the existing science-policy system has yet to develop.

ER  -

APA


Lawrence, N.D. & Montgomery, J.K.. (2026). Mind the gap: connecting AI innovation to widespread public value. Science and Public Policy doi:10.1093/scipol/scag070 Available from /publications/mind-the-gap-connecting-ai-innovation-to-widespread-public-value.html.

Related People

Neil D. Lawrence

The DeepMind Professor of Machine Learning, Cambridge University

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Jess Montgomery

Director, ai@cam and Accelerate Science, Cambridge University

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Related Projects

AI Adoption

The AI Adoption programme studies how institutions take up AI in ways that deliver public value — through public dialogue, practitioner partnership, and emerging theory on judgement, model minimisation, and the information topography of organisational change.

Public Dialogue and AI

Our work examines how public dialogue can contribute to the democratic direction of AI and to better technological and institutional choices. It asks how societal priorities can be surfaced early enough to influence research and innovation; how public perspectives can inform decisions about AI adoption; and how institutions can develop the capacity to continue listening and responding as technologies and their uses change.