Stoyanovich, Julia

Measuring Fairness in Ranked Outputs

Yang, K., & Stoyanovich, J. (2017) · Proceedings of the 29th International Conference on Scientific and Statistical Database Management

Ethics and Social Impacts of AIGame Theory and Voting Systems

Cited by 378

DataSynthesizer: Privacy-Preserving Synthetic Datasets

Ping, H., Stoyanovich, J., & Howe, B. (2017) · Proceedings of the 29th International Conference on Scientific and Statistical Database Management

Privacy-Preserving Technologies in Datademographic modeling and climate adaptation

Cited by 144

Diversity in Big Data: A Review

Drosou, M., Jagadish, H. V., Pitoura, E., & Stoyanovich, J. (2017) · Big Data

Ethics and Social Impacts of AIBig Data Technologies and Applications

Cited by 140

A Nutritional Label for Rankings

Yang, K., Stoyanovich, J., Asudeh, A., Howe, B., Jagadish, H., & Miklau, G. (2018) · Proceedings of the 2018 International Conference on Management of Data

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 103

It’s Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public Policy

Bell, A., Solano-Kamaiko, I., Nov, O., & Stoyanovich, J. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

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

Cited by 103

Think about the stakeholders first! Toward an algorithmic transparency playbook for regulatory compliance

Bell, A., Nov, O., & Stoyanovich, J. (2023) · Data & Policy

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 44

The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice

Bell, A., Bynum, L., Drushchak, N., Zakharchenko, T., Rosenblatt, L., & Stoyanovich, J. (2023) · 2023 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 21