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Lisa Soder

dblp:361/7129 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2025
0009-0001-6972-4491ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%
Artificial intelligence
1 paper
Trustworthy machine learning · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities
AI governance
0.812024
Position: Technical Research and Talent is Needed for Effective AI Governance · ICML 2024
Machine learning › Trustworthy machine learning › AI governance
AI regulation
0.212024
Position: Technical Research and Talent is Needed for Effective AI Governance · ICML 2024
YearPublicationVenuePosition
2025 More than Marketing? On the Information Value of AI Benchmarks for Practitioners
Amelia F. Hardy, Anka Reuel, Kiana Jafari Meimandi, Lisa Soder, Allie Griffith, Dylan M. Asmar, Oluwasanmi Koyejo, Michael S. Bernstein, Mykel J. Kochenderfer
IUI4
2024 Position: Technical Research and Talent is Needed for Effective AI Governance
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.
Anka Reuel, Lisa Soder, Ben Bucknall, Trond Arne Undheim
ICML2