Cynthia L. Bennett

Cynthia L. Bennett is a human-computer interaction researcher who studies how sociotechnical systems, including novel AI-powered experiences, affect people with disabilities. Her work informs inclusive and ethically designed processes and experiences, with a focus on accessibility, disability studies, AI bias and disability representation, and responsible AI for disabled communities. She works in Google Research’s Responsible AI and Human-Centered Technology organization; previously, she was a postdoctoral researcher at Carnegie Mellon University’s Human-Computer Interaction Institute and a researcher at Apple.

• September 2022–Present·Google Research·Research Scientist, Responsible AI and Human-Centered Technology
  • Researches generative AI, accessible experiences, disability representation, and the effects of AI on disabled communities.
• Previously | Carnegie Mellon University, Human-Computer Interaction Institute | Postdoctoral Researcher
  • Studied sociotechnical questions involving algorithmic bias, automation, accessibility, agency, and equity.
• Previously | Apple | Researcher
• Previously | Microsoft Research | Internship / research experience

• 2020·University of Washington, Human Centered Design and Engineering·Ph.D.
  • Dissertation: Toward Centering Access in Professional Design.
• Undergraduate study | University of North Carolina Wilmington | B.A. in Psychology
  • Minors in African American Studies and Women’s Studies.

• Microsoft Research Dissertation Grant
• National Science Foundation Graduate Research Fellowship
• University of Washington Dennis Lang Student Award (2018)
• HCDE Award for Student Research (2019)
• Co-authored papers have received awards at ACM ASSETS, CHI, and DIS; this profile does not convert that aggregate statement into an unverified specific Best Paper Award.

• Beyond Safety: Toward a Value-Sensitive Approach to the Design of AI Systems (2022): examines tensions between AI safety and other stakeholder values in AI-supported accessibility technologies.
• “They only care to show us the wheelchair”: disability representation in text-to-image AI models (CHI 2024): examines disability representation and stereotypes in text-to-image models.
• Understanding Use Cases for AI-Powered Visual Interpretation Services (CHI 2024): studies blind and low-vision users’ use cases and trust in AI-generated visual descriptions.

• Personal website (verified 2026-09-23)
• Google Research profile (verified 2026-09-23)
• CMU Beneficial Intelligence Group (verified 2026-09-23)
• UW HCDE news (verified 2026-09-23)
• UW Disability Studies event page (verified 2026-09-23)
• UC Irvine research bio (verified 2026-09-23)