Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. - Masoud Mansoury; Himan Abdollahpouri; Jessie Smith; Arman Dehpanah; Mykola Pechenizkiy; Bamshad Mobasher (FLAIRS, 2020)

P4KxSpotify: A Dataset of Pitchfork Music Reviews and Spotify Musical Features. - Anthony T. Pinter; Jacob M. Paul; Jessie Smith; Jed R. Brubaker (ICWSM, 2020)

RecSys 2020 Challenge Workshop: Engagement Prediction on Twitter's Home Timeline. - Vito Walter Anelli; Amra Delic; Gabriele Sottocornola; Jessie Smith; Nazareno Andrade; Luca Belli; Michael M. Bronstein; Akshay Gupta; Sofia Ira Ktena; Alexandre Lung-Yut-Fong; Frank Portman; Alykhan Tejani; et al. (RecSys, 2020)

Exploring User Opinions of Fairness in Recommender Systems. - Jessie Smith; Nasim Sonboli; Casey Fiesler; Robin Burke (CoRR, 2020)

Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline. - Luca Belli; Sofia Ira Ktena; Alykhan Tejani; Alexandre Lung-Yut-Fong; Frank Portman; Xiao Zhu; Yuanpu Xie; Akshay Gupta; Michael M. Bronstein; Amra Delic; Gabriele Sottocornola; Vito Walter Anelli; et al. (CoRR, 2020)

Integrating Ethics into Introductory Programming Classes. - Casey Fiesler; Mikhaila Friske; Natalie Garrett; Felix Muzny; Jessie J. Smith; Jason Zietz (SIGCSE, 2021)

Fairness and Transparency in Recommendation: The Users' Perspective. - Nasim Sonboli; Jessie J. Smith; Florencia Cabral Berenfus; Robin Burke; Casey Fiesler (UMAP, 2021)

REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. - Jessie J. Smith; Saleema Amershi; Solon Barocas; Hanna M. Wallach; Jennifer Wortman Vaughan (FAccT, 2022)

Developing a Human-Centered Framework for Transparency in Fairness-Aware Recommender Systems. - Jessie J. Smith (RecSys, 2022)

Recommender Systems and Algorithmic Hate. - Jessie J. Smith; Lucia Jayne; Robin Burke (RecSys, 2022)

RecSys Fairness Metrics: Many to Use But Which One To Choose? - Jessie J. Smith; Lex Beattie (CoRR, 2022)

Incorporating Ethics in Computing Courses: Perspectives from Educators. - Jessie J. Smith; Blakeley H. Payne; Shamika Klassen; Dylan Thomas Doyle; Casey Fiesler (CoRR, 2022)

The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation. - Jessie J. Smith; Anas Buhayh; Anushka Kathait; Pradeep Ragothaman; Nicholas Mattei; Robin Burke; Amy Voida (FAccT, 2023)

Incorporating Ethics in Computing Courses: Barriers, Support, and Perspectives from Educators. - Jessie J. Smith; Blakeley H. Payne; Shamika Klassen; Dylan Thomas Doyle; Casey Fiesler (SIGCSE (1), 2023)

Scoping Fairness Objectives and Identifying Fairness Metrics for Recommender Systems: The Practitioners' Perspective. - Jessie J. Smith; Lex Beattie; Henriette Cramer (WWW, 2023)

Recommend Me? Designing Fairness Metrics with Providers. - Jessie J. Smith; Aishwarya Satwani; Robin Burke; Casey Fiesler (FAccT, 2024)

Pragmatic Fairness: Evaluating ML Fairness Within the Constraints of Industry. - Jessie J. Smith; Michael Madaio; Robin Burke; Casey Fiesler (FAccT, 2025)

The Generative AI Ethics Playbook. - Jessie J. Smith; Wesley Hanwen Deng; William H. Smith; Maarten Sap; Nicole DeCario; Jesse Dodge (CoRR, 2025)