Briana Vecchione
I'm a Technical Researcher with the AI on the Ground team at Data & Society Research Institute. My work focuses on auditing and accountability in algorithmic systems—particularly at the intersection of social justice, participatory design, and policy. Recently, I’ve been interested in the intersection of large language models, psychology, mental health, and the limitations of using LLMs to contribute to knowledge production.
I hold a Ph.D. in Information Science from Cornell University and a B.S. in Computer Science from Pace University. My work has been supported by Google, Facebook, Microsoft, the National Science Foundation, the MacArthur Foundation, the Mozilla Foundation, and the Notre Dame-IBM Tech Ethics Lab.
Publications
Red-Teaming in the Public Interest
Ranjit Singh, Borhane Blili-Hamelin, Carol Anderson, Emnet Tafesse, Briana Vecchione, Beth Duckles, Jacob Metcalf
Data & Society. 2025.
Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling
Victor Ojewale, Ryan Steed, Briana Vecchione, Abeba Birhane, Inioluwa Deborah Raji
CHI Conference on Human Factors in Computing Systems. 2025.
Algorithm auditing: The Broken Bus on the Road to Algorithm Accountability
Abeba Birhane, Ryan Steed, Victor Ojewale, Briana Vecchione, Inioluwa Deborah Raji
2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). IEEE, 2024.
Auditing Work: Exploring the New York City algorithmic bias audit regime
Lara Groves, Jacob Metcalf, Alayna Kennedy, Briana Vecchione, Andrew Strait
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency. 2024.
Best Paper Award
Null Compliance: NYC Local Law 144 and the Challenges of Algorithm Accountability
Lucas Wright, Roxana Muenster, Briana Vecchione, Tianyao Qu, Pika (Senhuang) CAI, Alan Smith, COMM/INFO 2450 Student Investigators, Jacob Metcalf, J. Nathan Matias
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency. 2024.
Navigating the Complexities of Algorithmic Auditing: Challenges and Considerations
Briana Vecchione
Cornell University. 2023.
Algorithmic Auditing and Social Justice: Lessons from the History of Audit Studies
Briana Vecchione, Solon Barocas, Karen Levy
Proceedings of the 1st ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization. 2021.
view talk
Datasheets for Datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford
Gebru, Timnit, et al. "Datasheets for datasets." Communications of the ACM 64.12 (2021): 86-92.
Short version appeared at Proceedings of the 2018 ACM Conference on Fairness, Accountability, and Transparency
Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste
Zahra Nazari, Christophe Charbuillet, Johan Pages, Martin Laurent, Denis Charrier, Briana Vecchione and Benjamin Carterette
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 2020.
Other Written Works
Chatbots in Disguise: How Participants Use GenAI to Hack Qualitative Research
Ranjit Singh, Livia Garofalo, Briana Vecchione, Emnet Tafesse
Data & Society Points. 2025.
The Algorithmic Impact Methods Lab: Methods from the Field
Tamara Kneese, Briana Vecchione, Ranjit Singh, Emnet Tafesse, Meg Young, Jacob Metcalf
Data & Society Points. 2024.
Defining Public Interest Technology: Key Questions to Consider
Briana Vecchione
Cornell Tech Digital Life Initiative. 2022.
(Workshopped at CSCW 2022)
Addressing Economic Inequality in NYC through Social Impact Tech Research at Blue Ridge Labs
Briana Vecchione
Cornell Tech Public Interest Technology Initiative. 2021.
Select Talks, Workshops, & Engagements
Mind, Machine, and Me: Mental Health Chatbots and Techno-selfhood
Livia Garofalo, Briana Vecchione
STS Italia. 2025.
Databite No. 161: Red-Teaming Generative AI Harm
Lama Ahmad, Camille François, Tarleton Gillespie, Briana Vecchione, Borhane Blili-Hamelin
Data & Society Databite No. 161. 2025.
ASAP/15: The Association for the Study of the Arts of the Present
New York, NY. October 2024.
Tamara Kneese, Briana Vecchione
Algorithms and the Occult, or Chatbots are the New Psychic Friends Network
University of Pennsylvania: CIS7000 Algorithmic Justice
[Remote]. March 2024.
Guest Lecture: Algorithmic Auditing: Challenges and Considerations
University of California Berkeley: MBA295T/EWMBA 295T
[Remote]. January 2024.
Guest Lecture: Discrimination and Bias in Online Marketplaces
Columbia University: Computer Programming for Beginners: Coding in Python
New York, NY. July 2023.
Guest Lecture: An Introduction to AI Bias, Auditing, & Accountability
Notre Dame-IBM Technology Ethics Lab: Auditing AI Workshop
Notre Dame, IN. June 2023.
CSCW 2022: Who Has an Interest in “Public Interest Technology”? Critical Questions for Working with Local Governments & Impacted Communities
[Remote]. November 2022.
Mozilla All Hands. Trustworthy AI "Big Ideas": Navigating the Algorithm Audit Tooling Landscape.
Waikiki, HI. September 2022.
Arize: Observe Summit. Breaking Down Barriers: How Women In AI Creates a More Equitable Technological Future.
[Remote] March 2022.
2021 ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO)
[Remote] October 2021.
Algorithmic Auditing for Social Justice
Aspen Digital Data Stewardship for Good 2021 Roundtable
[Remote] April 2021.
Cornell University AI, Policy, and Practice Seminar
Ithaca, NY. November 2020.
Algorithmic Auditing for Social Justice
FATES 2020: 2nd Workshop on Fairness, Accountability, Transparency, Ethics and Society on the Web
[Remote]. April 2020.
Cornell University Women's Network: Digital Lives: Perspectives on Ethics and AI
New York, NY. October 2019.
Partnership on AI: ABOUT Machine Learning Workshop
New York, NY. April 2019.
AI, Policy, and Practice Seminar
Ithaca, NY. September 2018.
Datasheets for Datasets
AI Now: Data Genesis Working Group
New York, NY. January 2018.
Data for Good Exchange
New York, NY. September 2017.
Building Open Data Dashboards for Hyper Local Government
ACM Richard Tapia Celebration of Diversity in Computing
Boston, MA. February 2015.
Self Balancing CitiBikes
Knowledge Discovery and Data Mining at Bloomberg (KDD)
New York, NY. August 2014.
Self Balancing CitiBikes
Microsoft Research Data Science Summer School
New York, NY. August 2014.
Self Balancing CitiBikes