Timnit Gebru

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 31

Top Topics

General Intelligence

Subset Selection

Top Venues

Publications

Timnit Gebru, Émile P. Torres
The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence. First Monday 29 (4) (2024)
Suresh Venkatasubramanian, Timnit Gebru, Ufuk Topcu, Haley Griffin, Leah Namisa Rosenbloom, Nasim Sonboli
Community Driven Approaches to Research in Technology & Society CCC Workshop Report. CoRR (2024)
Harry H. Jiang, Lauren Brown, Jessica Cheng, Mehtab Khan, Abhishek Gupta, Deja Workman, Alex Hanna, Johnathan Flowers, Timnit Gebru
AI Art and its Impact on Artists. AIES (2023)
Vinodkumar Prabhakaran, Margaret Mitchell, Timnit Gebru, Iason Gabriel
A Human Rights-Based Approach to Responsible AI. CoRR (2022)
Raesetje Sefala, Timnit Gebru, Nyalleng Moorosi, Luzango Mfupe, Richard Klein
Constructing a Visual Dataset to Study the Effects of Spatial Apartheid in South Africa. NeurIPS Datasets and Benchmarks (2021)
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
Datasheets for datasets. Commun. ACM 64 (12) (2021)
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, Shmargaret Shmitchell
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? FAccT (2021)
Margaret Mitchell, Dylan Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern
Diversity and Inclusion Metrics in Subset Selection. AIES (2020)
Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing. CoRR (2020)
Margaret Mitchell, Dylan Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern
Diversity and Inclusion Metrics in Subset Selection. CoRR (2020)
Eun Seo Jo, Timnit Gebru
Lessons from archives: strategies for collecting sociocultural data in machine learning. FAT* (2020)
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 (2020)
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)
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)
Timnit Gebru
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning. KDD (2020)
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)
Timnit Gebru
Oxford Handbook on AI Ethics Book Chapter on Race and Gender. CoRR (2019)
Eun Seo Jo, Timnit Gebru
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning. CoRR (2019)
Ernest Mwebaze, Timnit Gebru, Andrea Frome, Solomon Nsumba, Jeremy Tusubira
iCassava 2019Fine-Grained Visual Categorization Challenge. CoRR (2019)
Emily Denton, Ben Hutchinson, Margaret Mitchell, Timnit Gebru
Detecting Bias with Generative Counterfactual Face Attribute Augmentation. CoRR (2019)
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
Datasheets for Datasets. CoRR (2018)
Joy Buolamwini, Timnit Gebru
Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. FAT (2018)
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 (2018)
Timnit Gebru, Judy Hoffman, Li Fei-Fei
Fine-Grained Recognition in the Wild: A Multi-task Domain Adaptation Approach. ICCV (2017)
Timnit Gebru, Jonathan Krause, Jia Deng, Li Fei-Fei
Scalable Annotation of Fine-Grained Categories Without Experts. CHI (2017)
Timnit Gebru, Jonathan Krause, Jia Deng, Li Fei-Fei
Scalable Annotation of Fine-Grained Categories Without Experts. CoRR (2017)
Timnit Gebru, Judy Hoffman, Li Fei-Fei
Fine-grained Recognition in the Wild: A Multi-Task Domain Adaptation Approach. CoRR (2017)
Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Erez Lieberman Aiden, Li Fei-Fei
Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States. Proc. Natl. Acad. Sci. USA 114 (50) (2017)
Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Erez Aiden Lieberman, Li Fei-Fei
Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US. CoRR (2017)
Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Li Fei-Fei
Fine-Grained Car Detection for Visual Census Estimation. CoRR (2017)
Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Li Fei-Fei
Fine-Grained Car Detection for Visual Census Estimation. AAAI (2017)
Jonathan Krause, Timnit Gebru, Jia Deng, Li-Jia Li, Li Fei-Fei
Learning Features and Parts for Fine-Grained Recognition. ICPR (2014)