Position: Technical Research and Talent is Needed for Effective AI Governance

Anka Reuel, Lisa Soder, Benjamin Bucknall, Trond Arne Undheim
Proceedings of the 41st International Conference on Machine Learning, PMLR 235:42543-42557, 2024.

Abstract

In light of recent advancements in AI capabilities and the increasingly widespread integration of AI systems into society, governments worldwide are actively seeking to mitigate the potential harms and risks associated with these technologies through regulation and other governance tools. However, there exist significant gaps between governance aspirations and the current state of the technical tooling necessary for their realisation. In this position paper, we survey policy documents published by public-sector institutions in the EU, US, and China to highlight specific areas of disconnect between the technical requirements necessary for enacting proposed policy actions, and the current technical state of the art. Our analysis motivates a call for tighter integration of the AI/ML research community within AI governance in order to i) catalyse technical research aimed at bridging the gap between current and supposed technical underpinnings of regulatory action, as well as ii) increase the level of technical expertise within governing institutions so as to inform and guide effective governance of AI.

Cite this Paper

BibTeX
@InProceedings{pmlr-v235-reuel24a, title = {Position: Technical Research and Talent is Needed for Effective {AI} Governance}, author = {Reuel, Anka and Soder, Lisa and Bucknall, Benjamin and Undheim, Trond Arne}, booktitle = {Proceedings of the 41st International Conference on Machine Learning}, pages = {42543--42557}, year = {2024}, editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix}, volume = {235}, series = {Proceedings of Machine Learning Research}, month = {21--27 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/reuel24a/reuel24a.pdf}, url = {https://proceedings.mlr.press/v235/reuel24a.html}, abstract = {In light of recent advancements in AI capabilities and the increasingly widespread integration of AI systems into society, governments worldwide are actively seeking to mitigate the potential harms and risks associated with these technologies through regulation and other governance tools. However, there exist significant gaps between governance aspirations and the current state of the technical tooling necessary for their realisation. In this position paper, we survey policy documents published by public-sector institutions in the EU, US, and China to highlight specific areas of disconnect between the technical requirements necessary for enacting proposed policy actions, and the current technical state of the art. Our analysis motivates a call for tighter integration of the AI/ML research community within AI governance in order to i) catalyse technical research aimed at bridging the gap between current and supposed technical underpinnings of regulatory action, as well as ii) increase the level of technical expertise within governing institutions so as to inform and guide effective governance of AI.} }
Endnote
%0 Conference Paper %T Position: Technical Research and Talent is Needed for Effective AI Governance %A Anka Reuel %A Lisa Soder %A Benjamin Bucknall %A Trond Arne Undheim %B Proceedings of the 41st International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2024 %E Ruslan Salakhutdinov %E Zico Kolter %E Katherine Heller %E Adrian Weller %E Nuria Oliver %E Jonathan Scarlett %E Felix Berkenkamp %F pmlr-v235-reuel24a %I PMLR %P 42543--42557 %U https://proceedings.mlr.press/v235/reuel24a.html %V 235 %X In light of recent advancements in AI capabilities and the increasingly widespread integration of AI systems into society, governments worldwide are actively seeking to mitigate the potential harms and risks associated with these technologies through regulation and other governance tools. However, there exist significant gaps between governance aspirations and the current state of the technical tooling necessary for their realisation. In this position paper, we survey policy documents published by public-sector institutions in the EU, US, and China to highlight specific areas of disconnect between the technical requirements necessary for enacting proposed policy actions, and the current technical state of the art. Our analysis motivates a call for tighter integration of the AI/ML research community within AI governance in order to i) catalyse technical research aimed at bridging the gap between current and supposed technical underpinnings of regulatory action, as well as ii) increase the level of technical expertise within governing institutions so as to inform and guide effective governance of AI.
APA
Reuel, A., Soder, L., Bucknall, B. & Undheim, T.A.. (2024). Position: Technical Research and Talent is Needed for Effective AI Governance. Proceedings of the 41st International Conference on Machine Learning, in Proceedings of Machine Learning Research 235:42543-42557 Available from https://proceedings.mlr.press/v235/reuel24a.html.

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