Friedler, Sorelle A.

Certifying and Removing Disparate Impact

Feldman, M., Friedler, S. A., Moeller, J., Scheidegger, C., & Venkatasubramanian, S. (2015) · Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Ethics and Social Impacts of AIDiscrimination and Equality Law

Cited by 1,827

Machine-learning-assisted materials discovery using failed experiments

Raccuglia, P., Elbert, K. C., Adler, P. D. F., Falk, C., Wenny, M. B., Mollo, A., Zeller, M., Friedler, S. A., Schrier, J., & Norquist, A. J. (2016) · Nature

Machine Learning in Materials ScienceComputational Drug Discovery Methods

Cited by 1,727

Fairness and Abstraction in Sociotechnical Systems

Selbst, A. D., Boyd, D., Friedler, S. A., Venkatasubramanian, S., & Vertesi, J. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 1,631

A comparative study of fairness-enhancing interventions in machine learning

Friedler, S. A., Scheidegger, C., Venkatasubramanian, S., Choudhary, S., Hamilton, E. P., & Roth, D. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 601

Auditing black-box models for indirect influence

Adler, P., Falk, C., Friedler, S. A., Nix, T., Rybeck, G., Scheidegger, C., Smith, B., & Venkatasubramanian, S. (2018) · Knowledge and Information Systems

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 280

Auditing Black-Box Models for Indirect Influence

Adler, P., Falk, C., Friedler, S. A., Rybeck, G., Scheidegger, C., Smith, B., & Venkatasubramanian, S. (2016) · 2016 IEEE 16th International Conference on Data Mining (ICDM)

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 280

The (Im)possibility of fairness: different value systems require different mechanisms for fair decision making

Friedler, S. A., Scheidegger, C., & Venkatasubramanian, S. (2021) · Communications of the ACM

Ethics and Social Impacts of AIPolitical Philosophy and Ethics

Cited by 262

On the (im)possibility of fairness

Friedler, S. A., Scheidegger, C., & Venkatasubramanian, S. (2016) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 247

Problems with Shapley-value-based explanations as feature importance measures

Kumar, I. E., Venkatasubramanian, S., Scheidegger, C., & Friedler, S. (2020) · arXiv

Explainable Artificial Intelligence (XAI)Privacy-Preserving Technologies in Data

Cited by 228

Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis

Jia, X., Lynch, A., Huang, Y., Danielson, M., Lang’at, I., Milder, A., Ruby, A. E., Wang, H., Friedler, S. A., Norquist, A. J., et al. (2019) · Nature

Machine Learning in Materials ScienceEthics and Social Impacts of AI

Cited by 222

Runaway Feedback Loops in Predictive Policing

Ensign, D., Friedler, S. A., Neville, S., Scheidegger, C., & Venkatasubramanian, S. (2017) · arXiv

Ethics and Social Impacts of AIPolicing Practices and Perceptions

Cited by 161

Fairness in representation: quantifying stereotyping as a representational harm

Abbasi, M., Friedler, S. A., Scheidegger, C., & Venkatasubramanian, S. (2019) · Proceedings of the 2019 SIAM International Conference on Data Mining

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 44

Active meta-learning for predicting and selecting perovskite crystallization experiments

Shekar, V., Nicholas, G., Najeeb, M. A., Zeile, M., Yu, V., Wang, X., Slack, D., Li, Z., Nega, P. W., Chan, E. M., et al. (2022) · The Journal of Chemical Physics

Machine Learning in Materials ScienceMachine Learning and Algorithms

Cited by 25