馃敩 Research Summary by Charvi Rastogi, a Ph.D. student in Machine Learning at Carnegie Mellon University. She is deeply passionate about addressing
A Systematic Review of Ethical Concerns with Voice Assistants
馃敩 Research Summary by William Seymour, a lecturer in computer science at King鈥檚 College London, specializing in AI privacy, security, and
Prompt Middleware: Helping Non-Experts Engage with Generative AI
馃敩 Research Summary by Dr. Stephen MacNeil, an Assistant Professor of Computer and Information Sciences at Temple University, where he directs the HCI
Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI
馃敩 Research Summary by Avijit Ghosh and Dhanya Lakshmi. Dr. Avijit Ghosh is a Research Data Scientist at AdeptID and a Lecturer in the Khoury
The Unequal Opportunities of Large Language Models: Revealing Demographic Bias through Job Recommendations
馃敩 Research Summary by Abel Salinas and Parth Vipul Shah. Abel is a second-year Ph.D. student at the University of Southern California.
Fair allocation of exposure in recommender systems
馃敩 Research Summary by Virginie Do and Nicolas Usunier Virginie Do is a former PhD student at Meta AI (Facebook AI Research) and PSL
Ghosting the Machine: Judicial Resistance to a Recidivism Risk Assessment Instrument
馃敩 Research Summary by Dasha Pruss, a postdoctoral fellow at the Berkman Klein Center for Internet & Society and the Embedded EthiCS program at
On the Perception of Difficulty: Differences between Humans and AI
馃敩 Research Summary by Philipp Spitzer and Joshua Holstein Philipp is a second-year PhD student at the Karlsruhe Institute of Technology, where
AI Consent Futures: A Case Study on Voice Data Collection with Clinicians
馃敩 Research Summary by Lauren Wilcox, Ph.D. (she/her) is a Senior Staff Research Scientist and Group Manager of the Technology, AI, Society, and
International Institutions for Advanced AI
馃敩 Research Summary by Lewis Ho, a researcher on Google DeepMind鈥檚 AGI Strategy and Governance Team. [Original paper by Lewis Ho, Joslyn
Participation and Division of Labor in User-Driven Algorithm Audits: How Do Everyday Users Work together to Surface Algorithmic Harms?
馃敩 Research Summary by Sara Kingsley, a researcher at Carnegie Mellon University, and an expert in A.I. system risk assessments, having built A.I.
“Customization is Key”: Four Characteristics of Textual Affordances for Accessible Data Visualization
馃敩 Research Summary by Shuli Jones, a recent MIT MEng in Computer Science and current software engineer at Google. [Original paper by Shuli