Workshop Paper
Emily Denton, Hansa Srinivasan, Dylan Baker, Jilin Chen, Alex Beutel, Tulsee Doshi, Ed H. Chi
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Cite
APA
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Denton, E., Srinivasan, H., Baker, D., Chen, J., Beutel, A., Doshi, T., & Chi, E. H. Learning to Diversify from Human Judgments: Research Directions and Open Challenges.
Chicago/Turabian
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Denton, Emily, Hansa Srinivasan, Dylan Baker, Jilin Chen, Alex Beutel, Tulsee Doshi, and Ed H. Chi. “Learning to Diversify from Human Judgments: Research Directions and Open Challenges” (n.d.).
MLA
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Denton, Emily, et al. Learning to Diversify from Human Judgments: Research Directions and Open Challenges.
BibTeX Click to copy
@article{emily-a,
title = {Learning to Diversify from Human Judgments: Research Directions and Open Challenges},
author = {Denton, Emily and Srinivasan, Hansa and Baker, Dylan and Chen, Jilin and Beutel, Alex and Doshi, Tulsee and Chi, Ed H.}
}
Abstract
Algorithmic ranking and retrieval systems have enormous influence over online media consumption, but run the risk of reflecting and reinforcing social biases. In this work, we outline a proposed research direction aimed at developing algorithmic techniques to increase diversity in such systems and pose open questions and challenges that arise from considering this problem in the realm of image sets.
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Algorithmic ranking and retrieval systems have enormous influence over online media consumption, but run the risk of reflecting and reinforcing social biases. In this work, we outline a proposed research direction aimed at developing algorithmic techniques to increase diversity in such systems and pose open questions and challenges that arise from considering this problem in the realm of image sets.
