Research

Research Fellow Article: Auditing large language models: a three-layered approach

Siegel Research Fellow Jakob Mökander, Visiting Scholar at the Princeton Center for Information Technology Policy, published a paper alongside collaborators at the University of Oxford which seeks to expand the methodological toolkit available to tech providers and policymakers who wish to analyse and evaluate LLMs from technical, ethical, and legal perspectives.
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Research Fellow Article: Humans and algorithms work together — so study them together

Researchers must develop a science to study the collective patterns of human–algorithm behavior so that it is possible to regulate adaptive algorithms and ensure they have a safe, beneficial role in society argues Siegel Research Fellow J. Nathan Matias in a Comment piece published in Nature this week.
Read MoreResearch Fellow Article: Humans and algorithms work together — so study them together