McKane Andrus

16 papers C 4Journal 8Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
From Data Activism to Activism in a Time of Data-Centrism: Affirming Epistemological Heterogeneity in Social Movements.
Proc. ACM Hum. Comput. Interact.
McKane Andrus, Sucheta Ghoshal, Sayamindu Dasgupta
2024 J jnl
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis.
Trans. Recomm. Syst.
Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Chloé Bakalar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Xian Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
2023 — conf
Back to " Back to Labor" : Revisiting Political Economies of Computer-Supported Cooperative Work.
CSCW Companion
Joice Tang, McKane Andrus, Samuel So, Udayan Tandon, Andrés Monroy-Hernández, Vera D. Khovanskaya, Sean A. Munson, Mark Zachry, Sucheta Ghoshal
2022 — conf
Attrition of Workers with Minoritized Identities on AI Teams.
EAAMO
Jeffrey Brown, Tina M. Park, Jiyoo Chang, McKane Andrus, Alice Xiang, Christine Custis
2022 J jnl
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis.
CoRR
Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy X. Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
2022 — conf
Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness.
FAccT
McKane Andrus, Sarah Villeneuve
2022 J jnl
Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness.
CoRR
McKane Andrus, Sarah Villeneuve
2021 J jnl
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks.
CoRR
McKane Andrus, Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick
2021 — conf
What We Can't Measure, We Can't Understand: Challenges to Demographic Data Procurement in the Pursuit of Fairness.
FAccT
McKane Andrus, Elena Spitzer, Jeffrey Brown, Alice Xiang
2020 J jnl
"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness.
CoRR
McKane Andrus, Elena Spitzer, Jeffrey Brown, Alice Xiang
2020 C conf
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks.
ISTAS
McKane Andrus, Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick
2020 J jnl
Machine Learning Explainability for External Stakeholders.
CoRR
Umang Bhatt, McKane Andrus, Adrian Weller, Alice Xiang
2019 C conf
Legible Normativity for AI Alignment: The Value of Silly Rules.
AIES
Dylan Hadfield-Menell, McKane Andrus, Gillian K. Hadfield
2019 C conf
On Serving Two Masters: Directing Critical Technical Practice towards Human-Compatibility in AI.
AIES
McKane Andrus
2019 C conf
Towards a Just Theory of Measurement: A Principled Social Measurement Assurance Program for Machine Learning.
AIES
McKane Andrus, Thomas K. Gilbert
2018 J jnl
Legible Normativity for AI Alignment: The Value of Silly Rules.
CoRR
Dylan Hadfield-Menell, McKane Andrus, Gillian K. Hadfield