馃敩 Research Summary by Matthew Barker, a recent graduate from the University of Cambridge, whose research focuses on explainable AI and human-machine
The path toward equal performance in medical machine learning
馃敩 Research Summary by Eike Petersen, a postdoctoral researcher at the Technical University of Denmark (DTU), working on fair, responsible, and robust
Adding Structure to AI Harm
馃敩 Research Summary by Mia Hoffmann and Heather Frase. Dr. Heather Frase is a Senior Fellow at the Center for Security and Emerging
On the Challenges of Using Black-Box APIs for Toxicity Evaluation in Research
馃敩 Research Summary by Luiza Pozzobon, a Research Scholar at Cohere For AI where she currently researches model safety. She鈥檚 also a master鈥檚 student
On the Creativity of Large Language Models
馃敩 Research Summary by Giorgio Franceschelli, a second-year Ph.D. student at the University of Bologna working on Generative Artificial Intelligence,
Supporting Human-LLM collaboration in Auditing LLMs with LLMs
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
Are we ready for a multispecies Westworld?
鉁嶏笍 Column by Jeff Sebo and Leonie N. Bossert Jeff Sebo is Clinical Associate Professor of Environmental Studies, Affiliated Professor of Bioethics,
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