Ned Cooper
I'm a postdoctoral researcher in the DesignAI lab at Cornell, working on human-AI interaction design and AI governance.
Before research, I spent eight years in large-scale technology infrastructure and human rights law. This background informs how I translate technical research into practical deployment, working across research, engineering, product, and policy teams.
I've collaborated with Google Research on building speech technologies for underserved languages, managed regulatory policy for Australia's national broadband rollout, and developed frameworks for responsible AI in high-stakes domains like mental health.
Email: ned [dot] cooper [at] cornell [dot] edu
RECENT PUBLICATIONS:
Evaluating AI
- Jared Moore, Ned Cooper*, Rasmus Overmark*, Beba Cibralic, Nick Haber, Cameron R. Jones. 2025. Do Large Language Models Have a Planning Theory of Mind? Evidence from MINDGAMES: a Multi-Step Persuasion Task. Second Conference on Language Modeling (COLM).
- Glen Berman, Ned Cooper, Wesley Hanwen Deng, Ben Hutchinson. 2024. Troubling Taxonomies in GenAI Evaluation. NeurIPS Workshop on Examining Best Practices for Measuring Broader Impacts of Generative AI.
- Skyler Wang*, Ned Cooper*, Margaret Eby. 2024. From human-centered to social-centered artificial intelligence: Assessing ChatGPT's impact through disruptive events. Big Data & Society.
Designing AI
- Ned Cooper, Jose A. Guridi, Angel Hsing-Chi Hwang, Beth Kolko, Emma Elizabeth McGinty, Qian Yang. 2026. Framing Responsible Design of AI Mental Well-Being Support: AI as Primary Care, Nutritional Supplement, or Yoga Instructor?. ACM Conference on Human Factors in Computing Systems (CHI).
- Ned Cooper and Alexandra Zafiroglu. 2025. Constraining Participation: Affordances of Feedback Features in Interfaces to Large Language Models. ACM Journal on Responsible Computing.
- Ben Hutchinson, Celeste Rodríguez Louro, Glenys Collard, and Ned Cooper. 2025. Designing Speech Technologies for Australian Aboriginal English: Opportunities, Risks and Participation. ACM Conference on Fairness, Accountability, and Transparency (FAccT).
- Ned Cooper and Alexandra Zafiroglu. 2024. From Fitting Participation to Forging Relationships: The Art of Participatory ML. ACM Conference on Human Factors in Computing Systems (CHI).
- Ned Cooper, Courtney Heldreth, Ben Hutchinson. 2024. "It’s how you do things that matters”: Attending to Process to Better Serve Indigenous Communities with Language Technologies. Conference of the EU Chapter of the Association for Computational Linguistics (EACL).
- Ned Cooper, Tiffanie Horne, Gillian R. Hayes, Courtney Heldreth, Michal Lahav, Jess Holbrook, Lauren Wilcox. 2022. A Systematic Review and Thematic Analysis of Community-Collaborative Approaches to Computing Research. ACM Conference on Human Factors in Computing Systems (CHI).
*Equal contribution