馃敩 Research Summary by Blair Attard-Frost, a PhD Candidate and SSHRC Joseph-Armand Bombardier Canada Graduate Scholar at the University of Toronto鈥檚
Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making
馃敩 Research Summary by Min Lee, an Assistant Professor in Computer Science at Singapore Management University, where he creates and evaluates
The Design Space of Generative Models
馃敩 Research Summary by Meredith Ringel Morris, Director of Human-AI Interaction Research at Google DeepMind; she is also an Affiliate Professor at the
Towards Healthy AI: Large Language Models Need Therapists Too
馃敩 Research Summary by Baihan Lin, PhD, a computational neuroscientist and AI researcher at Columbia University and IBM Thomas J Watson Research
Value-based Fast and Slow AI Nudging
馃敩 Research summary by Dr. Marianna Ganapini, our Faculty Director. [Original paper by Marianna B. Ganapini, Francesco Fabiano, Lior Horesh,
AI in the Gray: Exploring Moderation Policies in Dialogic Large Language Models vs. Human Answers in Controversial Topics
馃敩 Research Summary by Vahid Ghafouri, a Ph.D. student in Telematics at IMDEA Networks Institute working on the application of NLP to measure online
Benchmark Dataset Dynamics, Bias and Privacy Challenges in Voice Biometrics Research
馃敩 Research Summary by Anna Leschanowsky, a research associate at Fraunhofer IIS in Germany working at the intersection of voice technology,
Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare
馃敩 Research Summary by Eran Tal, Canada Research Chair in Data Ethics and Associate Professor of Philosophy at McGill University. He studies the
Tell me, what are you most afraid of? Exploring the Effects of Agent Representation on Information Disclosure in Human-Chatbot Interaction
馃敩 Research Summary by Stephan Schl枚gl, a professor of Human-Centered Computing at MCI - The Entrepreneurial School in Innsbruck (Austria), where his
People are not coins: Morally distinct types of predictions necessitate different fairness constraints
馃敩 Research Summary by Corinna Hertweck, a fourth-year PhD student at the University of Zurich and the Zurich University of Applied Sciences where she
From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models
馃敩 Research Summary by Shangbin Feng, Chan Young Park, and Yulia Tsvetkov. Shangbin Feng is a Ph.D. student at University of Washington.Chan
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
馃敩 Research Summary by Stephen Casper, an MIT PhD student working on AI interpretability, diagnostics, and safety. [Original paper by Stephen