Data science for urban equity: Making gentrification an accessible topic for data scientists, policymakers, and the community. - Bernease Herman; Gundula Proksch; Rachel Berney; Hillary Dawkins; Jacob Kovacs; Yahui Ma; Jacob Rich; Amanda Tan (CoRR, 2017)

Synthetic Data for Social Good. - Bill Howe; Julia Stoyanovich; Haoyue Ping; Bernease Herman; Matt Gee (CoRR, 2017)

An Algorithmic Equity Toolkit for Technology Audits by Community Advocates and Activists. - Michael A. Katell; Meg Young; Bernease Herman; Dharma Dailey; Aaron Tam; Vivian Guetler; Corinne Bintz; Daniella Raz; P. M. Krafft (CoRR, 2019)

Advancing diversity in human centered data science education through games. - Bernease Herman; Cecilia R. Aragon; Sarah A. Evans; Lea Shanley (ASIST, 2020)

Toward situated interventions for algorithmic equity: lessons from the field. - Michael A. Katell; Meg Young; Dharma Dailey; Bernease Herman; Vivian Guetler; Aaron Tam; Corinne Bintz; Daniella Raz; P. M. Krafft (FAT*, 2020)

Face Mis-ID: An Interactive Pedagogical Tool Demonstrating Disparate Accuracy Rates in Facial Recognition. - Daniella Raz; Corinne Bintz; Vivian Guetler; Aaron Tam; Michael A. Katell; Dharma Dailey; Bernease Herman; P. M. Krafft; Meg Young (AIES, 2021)

An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and Activists. - P. M. Krafft; Meg Young; Michael A. Katell; Jennifer E. Lee; Shankar Narayan; Micah Epstein; Dharma Dailey; Bernease Herman; Aaron Tam; Vivian Guetler; Corinne Bintz; Daniella Raz; et al. (FAccT, 2021)

Game Development as Speculative Design: Teaching Data Science Ethics Using Decentralized Research Groups. - Mimi Byun; Sarah A. Evans; Bernease Herman; Cecilia R. Aragon; Diana Rojas-Ponce (ASIST, 2022)

Ontologue: Declarative Benchmark Construction for Ontological Multi-Label Classification. - Sean Yang; Bernease Herman; Bill Howe (NeurIPS, 2022)

Rethinking Streaming Machine Learning Evaluation. - Shreya Shankar; Bernease Herman; Aditya G. Parameswaran (CoRR, 2022)

Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. - Lucas Rosenblatt; Anastasia Holovenko; Taras Rumezhak; Andrii Stadnik; Bernease Herman; Julia Stoyanovich; Bill Howe (CoRR, 2022)

Laboratory-Scale AI: Open-Weight Models are Competitive with ChatGPT Even in Low-Resource Settings. - Robert Wolfe; Isaac Slaughter; Bin Han 011; Bingbing Wen; Yiwei Yang 009; Lucas Rosenblatt; Bernease Herman; Eva Maxfield Brown; Zening Qu; Nic Weber; Bill Howe (FAccT, 2024)

Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. - Lucas Rosenblatt; Bernease Herman; Anastasia Holovenko; Wonkwon Lee; Joshua R. Loftus; Elizabeth McKinnie; Taras Rumezhak; Andrii Stadnik; Bill Howe; Julia Stoyanovich (SIGMOD Rec., 2024)

A Framework for Measuring and Benchmarking Fairness of Generative Crowd-Flow Models. - Jiaqi He; Apoorva Sheera; Jack W. McFarland; Feiyang Wang; Manurag Khullar; Sakshi Chavan; Bernease Herman; Ekin Ugurel; Afra Mashhadi (ACM J. Comput. Sustain. Soc., 2025)

Understanding Privacy Norms Around LLM-Based Chatbots: A Contextual Integrity Perspective. - Sarah Tran; Hongfan Lu; Isaac Slaughter; Bernease Herman; Aayushi Dangol; Yue Fu; Lufei Chen; Biniyam Gebreyohannes; Bill Howe; Alexis Hiniker; Nicholas M. Weber; Robert Wolfe (CoRR, 2025)