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ORCIDInioluwa Deborah Raji
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- affiliation: Mozilla Foundation, USA
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2020 – today
- 2024
[c13]Hellina Hailu Nigatu
, Inioluwa Deborah Raji:
"I Searched for a Religious Song in Amharic and Got Sexual Content Instead'': Investigating Online Harm in Low-Resourced Languages on YouTube. FAccT 2024: 141-160- [c12]Abeba Birhane, Ryan Steed, Victor Ojewale, Briana Vecchione, Inioluwa Deborah Raji:
AI auditing: The Broken Bus on the Road to AI Accountability. SaTML 2024: 612-643 - [i18]Inioluwa Deborah Raji, Roel Dobbe:
Concrete Problems in AI Safety, Revisited. CoRR abs/2401.10899 (2024) - [i17]Abeba Birhane, Ryan Steed, Victor Ojewale, Briana Vecchione, Inioluwa Deborah Raji:
AI auditing: The Broken Bus on the Road to AI Accountability. CoRR abs/2401.14462 (2024) - [i16]Victor Ojewale, Ryan Steed, Briana Vecchione, Abeba Birhane, Inioluwa Deborah Raji:
Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling. CoRR abs/2402.17861 (2024) - [i15]Hellina Hailu Nigatu, Inioluwa Deborah Raji:
"I Searched for a Religious Song in Amharic and Got Sexual Content Instead": Investigating Online Harm in Low-Resourced Languages on YouTube. CoRR abs/2405.16656 (2024) - [i14]Judy Hanwen Shen, Inioluwa Deborah Raji, Irene Y. Chen:
The Data Addition Dilemma. CoRR abs/2408.04154 (2024) - 2023
- [j4]Inioluwa Deborah Raji, Joy Buolamwini:
Actionable Auditing Revisited: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. Commun. ACM 66(1): 101-108 (2023) - [c11]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:
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. FAccT 2023: 1396-1417 - [i13]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:
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. CoRR abs/2304.13081 (2023) - [i12]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:
REFORMS: Reporting Standards for Machine Learning Based Science. CoRR abs/2308.07832 (2023) - [i11]Sasha Costanza-Chock, Emma Harvey, Inioluwa Deborah Raji, Martha Czernuszenko, Joy Buolamwini:
Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem. CoRR abs/2310.02521 (2023) - 2022
- [c10]Inioluwa Deborah Raji:
From Algorithmic Audits to Actual Accountability: Overcoming Practical Roadblocks on the Path to Meaningful Audit Interventions for AI Governance. AIES 2022: 5 - [c9]Inioluwa Deborah Raji, Peggy Xu, Colleen Honigsberg, Daniel E. Ho:
Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance. AIES 2022: 557-571 - [c8]Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz, Andrew D. Selbst:
The Fallacy of AI Functionality. FAccT 2022: 959-972 - [c7]Sasha Costanza-Chock, Inioluwa Deborah Raji, Joy Buolamwini:
Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem. FAccT 2022: 1571-1583 - [i10]Inioluwa Deborah Raji, Peggy Xu, Colleen Honigsberg, Daniel E. Ho:
Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance. CoRR abs/2206.04737 (2022) - [i9]Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz, Andrew D. Selbst:
The Fallacy of AI Functionality. CoRR abs/2206.09511 (2022) - 2021
- [j3]Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, Alex Hanna:
Data and its (dis)contents: A survey of dataset development and use in machine learning research. Patterns 2(11): 100336 (2021) - [c6]Inioluwa Deborah Raji, Morgan Klaus Scheuerman, Razvan Amironesei:
You Can't Sit With Us: Exclusionary Pedagogy in AI Ethics Education. FAccT 2021: 515-525 - [c5]Inioluwa Deborah Raji, Emily Denton, Emily M. Bender, Alex Hanna, Amandalynne Paullada:
AI and the Everything in the Whole Wide World Benchmark. NeurIPS Datasets and Benchmarks 2021 - [i8]Inioluwa Deborah Raji, Genevieve Fried:
About Face: A Survey of Facial Recognition Evaluation. CoRR abs/2102.00813 (2021) - [i7]Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada, Emily Denton, Alex Hanna:
AI and the Everything in the Whole Wide World Benchmark. CoRR abs/2111.15366 (2021) - 2020
- [j2]Inioluwa Deborah Raji:
The Discomfort of Death Counts: Mourning through the Distorted Lens of Reported COVID-19 Death Data. Patterns 1(4): 100066 (2020) - [j1]Inioluwa Deborah Raji:
Handle with Care: Lessons for Data Science from Black Female Scholars. Patterns 1(8): 100150 (2020) - [c4]Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton:
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing. AIES 2020: 145-151 - [c3]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes:
Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing. FAT* 2020: 33-44 - [i6]Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton:
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing. CoRR abs/2001.00964 (2020) - [i5]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes:
Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing. CoRR abs/2001.00973 (2020) - [i4]Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, Alex Hanna:
Data and its (dis)contents: A survey of dataset development and use in machine learning research. CoRR abs/2012.05345 (2020)
2010 – 2019
- 2019
- [c2]Inioluwa Deborah Raji, Joy Buolamwini:
Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. AIES 2019: 429-435 - [c1]Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru:
Model Cards for Model Reporting. FAT 2019: 220-229 - [i3]Alice Xiang, Inioluwa Deborah Raji:
On the Legal Compatibility of Fairness Definitions. CoRR abs/1912.00761 (2019) - [i2]Inioluwa Deborah Raji, Jingying Yang:
ABOUT ML: Annotation and Benchmarking on Understanding and Transparency of Machine Learning Lifecycles. CoRR abs/1912.06166 (2019) - 2018
- [i1]Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru:
Model Cards for Model Reporting. CoRR abs/1810.03993 (2018)
Coauthor Index
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last updated on 2024-10-07 21:17 CEST by the dblp team
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