Inioluwa Deborah Raji

According to our database, Inioluwa Deborah Raji authored at least 33 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Bridging Prediction and Intervention Problems in Social Systems.

Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Hammaad Adam, Amanda Coston, Benjamin Laufer, Ezinne Nwankwo, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson

CoRR, July, 2025

Multi-lingual Functional Evaluation for Large Language Models.

Victor Ojewale, Inioluwa Deborah Raji, Suresh Venkatasubramanian

CoRR, June, 2025

Aggregated Individual Reporting for Post-Deployment Evaluation.

Jessica Dai, Inioluwa Deborah Raji, Benjamin Recht, Irene Y. Chen

CoRR, June, 2025

The California Report on Frontier AI Policy.

Rishi Bommasani, Scott R. Singer, Ruth E. Appel, Sarah Cen, A. Feder Cooper, Elena Cryst, Lindsey A. Gailmard, Ian Klaus, Meredith M. Lee, Inioluwa Deborah Raji, Anka Reuel, Drew Spence, Alexander Wan, Angelina Wang, Daniel Zhang, Daniel E. Ho, Percy Liang, Dawn Song, Joseph E. Gonzalez, Jonathan Zittrain, Jennifer Tour Chayes, Mariano-Florentino Cuellar, Li Fei-Fei

CoRR, June, 2025

Medical Large Language Model Benchmarks Should Prioritize Construct Validity.

Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini, Shiladitya Dutta, Frances Dean, Inioluwa Deborah Raji, Travis Zack

CoRR, March, 2025

Toward an Evaluation Science for Generative AI Systems.

Laura Weidinger, Inioluwa Deborah Raji, Hanna M. Wallach, Margaret Mitchell, Angelina Wang, Olawale Salaudeen, Rishi Bommasani, Deep Ganguli, Sanmi Koyejo, William Isaac

CoRR, March, 2025

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms.

Jessica Dai, Paula Gradu, Inioluwa Deborah Raji, Benjamin Recht

CoRR, February, 2025

Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling.

Victor Ojewale, Ryan Steed, Briana Vecchione, Abeba Birhane, Inioluwa Deborah Raji

Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025

Evaluating Prediction-based Interventions with Human Decision Makers In Mind.

Inioluwa Deborah Raji, Lydia T. Liu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Concrete Problems in AI Safety, Revisited.

Inioluwa Deborah Raji, Roel Dobbe

CoRR, 2024

AI auditing: The Broken Bus on the Road to AI Accountability.

Abeba Birhane, Ryan Steed, Victor Ojewale, Briana Vecchione, Inioluwa Deborah Raji

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

The Data Addition Dilemma.

Judy Hanwen Shen, Inioluwa Deborah Raji, Irene Y. Chen

Proceedings of the Machine Learning for Healthcare Conference, 2024

"I Searched for a Religious Song in Amharic and Got Sexual Content Instead'': Investigating Online Harm in Low-Resourced Languages on YouTube.

Hellina Hailu Nigatu, Inioluwa Deborah Raji

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023

Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem.

Sasha Costanza-Chock, Emma Harvey, Inioluwa Deborah Raji, Martha Czernuszenko, Joy Buolamwini

CoRR, 2023

REFORMS: Reporting Standards for Machine Learning Based Science.

Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan

CoRR, 2023

Actionable Auditing Revisited: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products.

Inioluwa Deborah Raji, Joy Buolamwini

Commun. ACM, 2023

Organizational Governance of Emerging Technologies: AI Adoption in Healthcare.

Jee Young Kim, William Boag, Freya Gulamali, Alifia Hasan, Henry David Jeffry Hogg, Mark Lifson, Deirdre K. Mulligan, Manesh Patel, Inioluwa Deborah Raji, Ajai Sehgal, Keo Shaw, Danny Tobey, Alexandra Valladares, David E. Vidal, Suresh Balu, Mark P. Sendak

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

The Fallacy of AI Functionality.

Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz, Andrew D. Selbst

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem.

Sasha Costanza-Chock, Inioluwa Deborah Raji, Joy Buolamwini

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance.

Inioluwa Deborah Raji, Peggy Xu, Colleen Honigsberg, Daniel E. Ho

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

From Algorithmic Audits to Actual Accountability: Overcoming Practical Roadblocks on the Path to Meaningful Audit Interventions for AI Governance.

Inioluwa Deborah Raji

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

Data and its (dis)contents: A survey of dataset development and use in machine learning research.

Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, Alex Hanna

Patterns, 2021

About Face: A Survey of Facial Recognition Evaluation.

Inioluwa Deborah Raji, Genevieve Fried

CoRR, 2021

AI and the Everything in the Whole Wide World Benchmark.

Inioluwa Deborah Raji, Emily Denton, Emily M. Bender, Alex Hanna, Amandalynne Paullada

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

You Can't Sit With Us: Exclusionary Pedagogy in AI Ethics Education.

Inioluwa Deborah Raji, Morgan Klaus Scheuerman, Razvan Amironesei

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020

Handle with Care: Lessons for Data Science from Black Female Scholars.

Inioluwa Deborah Raji

Patterns, 2020

The Discomfort of Death Counts: Mourning through the Distorted Lens of Reported COVID-19 Death Data.

Inioluwa Deborah Raji

Patterns, 2020

Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing.

Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes

Proceedings of the FAT* '20: Conference on Fairness, 2020

Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing.

Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2019

ABOUT ML: Annotation and Benchmarking on Understanding and Transparency of Machine Learning Lifecycles.

Inioluwa Deborah Raji, Jingying Yang

CoRR, 2019

On the Legal Compatibility of Fairness Definitions.

Alice Xiang, Inioluwa Deborah Raji

CoRR, 2019

Model Cards for Model Reporting.

Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products.

Inioluwa Deborah Raji, Joy Buolamwini

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019