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Building Human Values into Recommender Systems: An Interdisciplinary Synthesis
Recommender systems are the algorithms which select, filter, and persona...
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Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness
Most proposed algorithmic fairness techniques require access to data on ...
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AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks
Despite interest in communicating ethical problems and social contexts w...
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"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness
As calls for fair and unbiased algorithmic systems increase, so too does...
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Machine Learning Explainability for External Stakeholders
As machine learning is increasingly deployed in high-stakes contexts aff...
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