Certifying and removing disparate impact M Feldman, SA Friedler, J Moeller, C Scheidegger, ... proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 1856 | 2015 |
Machine-learning-assisted materials discovery using failed experiments P Raccuglia, KC Elbert, PDF Adler, C Falk, MB Wenny, A Mollo, M Zeller, ... Nature 533 (7601), 73-76, 2016 | 1293 | 2016 |
Fairness and abstraction in sociotechnical systems AD Selbst, D Boyd, SA Friedler, S Venkatasubramanian, J Vertesi Proceedings of the conference on fairness, accountability, and transparency …, 2019 | 816 | 2019 |
A comparative study of fairness-enhancing interventions in machine learning SA Friedler, C Scheidegger, S Venkatasubramanian, S Choudhary, ... Proceedings of the conference on fairness, accountability, and transparency …, 2019 | 625 | 2019 |
The (im) possibility of fairness: Different value systems require different mechanisms for fair decision making SA Friedler, C Scheidegger, S Venkatasubramanian Communications of the ACM 64 (4), 136-143, 2021 | 608 | 2021 |
Runaway feedback loops in predictive policing D Ensign, SA Friedler, S Neville, C Scheidegger, S Venkatasubramanian Conference on Fairness, Accountability, and Transparency, 2018 | 426 | 2018 |
Auditing black-box models for indirect influence P Adler, C Falk, SA Friedler, T Nix, G Rybeck, C Scheidegger, B Smith, ... Knowledge and Information Systems 54, 95-122, 2018 | 367 | 2018 |
Problems with Shapley-value-based explanations as feature importance measures IE Kumar, S Venkatasubramanian, C Scheidegger, S Friedler International Conference on Machine Learning, 5491-5500, 2020 | 310 | 2020 |
Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis X Jia, A Lynch, Y Huang, M Danielson, I Lang’at, A Milder, AE Ruby, ... Nature 573 (7773), 251-255, 2019 | 161 | 2019 |
Hiring by algorithm: predicting and preventing disparate impact I Ajunwa, S Friedler, CE Scheidegger, S Venkatasubramanian Available at SSRN, 2016 | 79 | 2016 |
Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management IM Pendleton, G Cattabriga, Z Li, MA Najeeb, SA Friedler, AJ Norquist, ... MRS Communications 9 (3), 846-859, 2019 | 76 | 2019 |
Principles for accountable algorithms and a social impact statement for algorithms N Diakopoulos, S Friedler, M Arenas, S Barocas, M Hay, B Howe, ... Dagstuhl working group write-up: https://www.fatml.org/resources/principles …, 2016 | 70 | 2016 |
Gaps in Information Access in Social Networks B Fish, A Bashardoust, D Boyd, S Friedler, C Scheidegger, ... The World Wide Web Conference, 480-490, 2019 | 56 | 2019 |
Fairness in representation: quantifying stereotyping as a representational harm M Abbasi, SA Friedler, C Scheidegger, S Venkatasubramanian Proceedings of the 2019 SIAM International Conference on Data Mining, 801-809, 2019 | 55 | 2019 |
How to hold algorithms accountable N Diakopoulos, S Friedler MIT Technology Review 17 (11), 2016, 2016 | 54 | 2016 |
Assessing the Local Interpretability of Machine Learning Models D Slack, SA Friedler, C Scheidegger, CD Roy NeurIPS Workshop on Human-Centric Machine Learning, 2019 | 50 | 2019 |
Proceedings of the 1st Conference on Fairness, Accountability and Transparency J Buolamwini, T Gebru, SA Friedler, C Wilson Proceedings of Machine Learning Research 81, 77-91, 2018 | 49 | 2018 |
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal Data D Slack, S Friedler, E Givental Conference on Fairness, Accountability, and Transparency, 2020 | 48 | 2020 |
Energy Usage Reports: Environmental awareness as part of algorithmic accountability K Lottick, S Susai, SA Friedler, JP Wilson Workshop on Tackling Climate Change with Machine Learning at NeurIPS 2019, 2019 | 48 | 2019 |
Automated congressional redistricting HA Levin, SA Friedler Journal of Experimental Algorithmics (JEA) 24, 1-24, 2019 | 44 | 2019 |