William Agnew

According to our database, William Agnew authored at least 24 papers between 2016 and 2024.

Collaborative distances:

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

2024

What Can AI Ethics Learn from Anarchism?

William Agnew

XRDS, 2024

Data Defenses Against Large Language Models.

William Agnew, Harry H. Jiang, Cella Sum, Maarten Sap, Sauvik Das

CoRR, 2024

Sound Check: Auditing Audio Datasets.

William Agnew, Julia Barnett, Annie Chu, Rachel Hong, Michael Feffer, Robin Netzorg, Harry H. Jiang, Ezra Awumey, Sauvik Das

CoRR, 2024

'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants.

Shivani Kapania, William Agnew, Motahhare Eslami, Hoda Heidari, Sarah E. Fox

CoRR, 2024

Who's in and who's out? A case study of multimodal CLIP-filtering in DataComp.

Rachel Hong, William Agnew, Tadayoshi Kohno, Jamie Morgenstern

Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, 2024

The Illusion of Artificial Inclusion.

William Agnew, A. Stevie Bergman, Jennifer Chien, Mark Díaz, Seliem El-Sayed, Jaylen Pittman, Shakir Mohamed, Kevin R. McKee

Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

2023

AI Ethics and Critique for Robotics

William Agnew

PhD thesis, 2023

The Surveillance AI Pipeline.

Pratyusha Ria Kalluri, William Agnew, Myra Cheng, Kentrell Owens, Luca Soldaini, Abeba Birhane

CoRR, 2023

Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms.

Organizers Of QueerInAI, Nathaniel Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, Jess de Jesus de Pinho Pinhal

CoRR, 2023

Evaluating the Social Impact of Generative AI Systems in Systems and Society.

Irene Solaiman, Zeerak Talat, William Agnew, Lama Ahmad, Dylan K. Baker, Su Lin Blodgett, Hal Daumé III, Jesse Dodge, Ellie Evans, Sara Hooker, Yacine Jernite, Alexandra Sasha Luccioni, Alberto Lusoli, Margaret Mitchell, Jessica Newman, Marie-Therese Png, Andrew Strait, Apostol Vassilev

CoRR, 2023

Queer In AI: A Case Study in Community-Led Participatory AI.

Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark

CoRR, 2023

Queer In AI: A Case Study in Community-Led Participatory AI.

Organizers Of QueerInAI, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark

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

Representation in AI Evaluations.

A. Stevie Bergman, Lisa Anne Hendricks, Maribeth Rauh, Boxi Wu, William Agnew, Markus Kunesch, Isabella Duan, Iason Gabriel, William Isaac

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

Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms.

Nathan Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, Jessica de Jesus de Pinho Pinhal

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Queer in AI.

Hetvi Jethwani, Arjun Subramonian, William Agnew, MaryLena Bleile, Sarthak Arora, Maria Ryskina, Jeffrey Xiong

XRDS, 2022

Robots Enact Malignant Stereotypes.

Andrew Hundt, William Agnew, Vicky Zeng, Severin Kacianka, Matthew C. Gombolay

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

The Values Encoded in Machine Learning Research.

Abeba Birhane, Pratyusha Kalluri, Dallas Card, William Agnew, Ravit Dotan, Michelle Bao

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

2021

Documenting the English Colossal Clean Crawled Corpus.

Jesse Dodge, Maarten Sap, Ana Marasovic, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Matt Gardner

CoRR, 2021

Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus.

Jesse Dodge, Maarten Sap, Ana Marasovic, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Margaret Mitchell, Matt Gardner

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity.

William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Caelen Wang, Pedro Domingos, Siddhartha S. Srinivasa

CoRR, 2020

Self-Supervised Object-Level Deep Reinforcement Learning.

William Agnew, Pedro Domingos

CoRR, 2020

Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity.

William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Yubo Wang, Pedro Domingos, Siddhartha S. Srinivasa

Proceedings of the 4th Conference on Robot Learning, 2020

2016

Drawing Insights from "Big Data" Machine Learning Literature using Textual Features Why are some novels considered to be literature? A. predictive model of literary judgments shows that textual features are important. Andreas van Cranenburgh: Reducing Mobile Throttling from Temperature by Offloading Apps.

William Agnew, Hyunjong Lee, Minsung Jang, Ada Gavrilovska, Karsten Schwan

Adv. Math. Commun., 2016

An Ensemble-Based Recommendation Engine for Scientific Data Transfers.

William Agnew, Michael Fischer, Ian T. Foster, Kyle Chard

Proceedings of the Seventh International Workshop on Data-Intensive Computing in the Clouds, 2016