Responsible AI Research Needs Impact Statements Too

no code implementations • 20 Nov 2023 • Alexandra Olteanu, Michael Ekstrand, Carlos Castillo, Jina Suh

All types of research, development, and policy work can have unintended, adverse consequences - work in responsible artificial intelligence (RAI), ethical AI, or ethics in AI is no exception.

Ethics

Unified Browsing Models for Linear and Grid Layouts

no code implementations • 19 Oct 2023 • Amifa Raj, Michael Ekstrand

These metrics take user browsing behavior into account in their measurement strategies to estimate the attention the user is likely to provide to each item in ranking.

Fairness Position

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

no code implementations • 20 Jul 2022 • Jonathan Stray, Alon Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan

We collect a set of values that seem most relevant to recommender systems operating across different domains, then examine them from the perspectives of current industry practice, measurement, product design, and policy approaches.

Causal Inference Ethics +1

Estimation of Fair Ranking Metrics with Incomplete Judgments

no code implementations • 11 Aug 2021 • Ömer Kırnap, Fernando Diaz, Asia Biega, Michael Ekstrand, Ben Carterette, Emine Yilmaz

There is increasing attention to evaluating the fairness of search system ranking decisions.

Attribute Fairness