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2020 – today
- 2024
[c7]Shomik Jain
, Vinith M. Suriyakumar, Kathleen Creel, Ashia Wilson:
Algorithmic Pluralism: A Structural Approach To Equal Opportunity. FAccT 2024: 197-206- [c6]Shomik Jain, Kathleen Creel, Ashia Camage Wilson:
Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized. ICML 2024 - [i5]Shomik Jain, Kathleen Creel, Ashia Wilson:
Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized. CoRR abs/2404.08592 (2024) - 2023
- [c5]Connor Toups, Rishi Bommasani, Kathleen Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang:
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. NeurIPS 2023 - [i4]Rishi Bommasani, Dilara Soylu, Thomas I. Liao, Kathleen A. Creel, Percy Liang:
Ecosystem Graphs: The Social Footprint of Foundation Models. CoRR abs/2303.15772 (2023) - [i3]Connor Toups, Rishi Bommasani, Kathleen A. Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang:
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. CoRR abs/2307.05862 (2023) - 2022
- [c4]Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang:
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? NeurIPS 2022 - [c3]Nick Parlante, Julie Zelenski, Eric S. Roberts, Jed Rembold, Ben Stephenson, Jonathan Hudson, Stephanie Valentine, Juliette Woodrow, Kathleen Creel, Nick Bowman, Larry Joshua Crotts, Andrew Matzureff, Mike Izbicki:
Nifty Assignments. SIGCSE (2) 2022: 1067-1068 - [i2]Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang:
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? CoRR abs/2211.13972 (2022) - 2021
- [c2]Kathleen Creel, Deborah Hellman:
The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision Making Systems. FAccT 2021: 816 - [i1]Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.:
On the Opportunities and Risks of Foundation Models. CoRR abs/2108.07258 (2021)
2010 – 2019
- 2019
- [c1]Roberto Confalonieri, Tarek R. Besold, Tillman Weyde, Kathleen Creel, Tania Lombrozo, Shane T. Mueller, Patrick Shafto:
What makes a good explanation? Cognitive dimensions of explaining intelligent machines. CogSci 2019: 25-26
Coauthor Index
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