🔬 Research Summary by Ahmad Faiz, Masters in Data Science student at Indiana University Bloomington. [Original paper by Ahmad Faiz, Sotaro Kaneda, Ruhan Wang, Rita Osi, Parteek Sharma, Fan Chen, and Lei … [Read more...] about LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models
Climate
The Moral Machine Experiment on Large Language Models
🔬 Research Summary by Kazuhiro Takemoto, Professor at Kyushu Institute of Technology. [Original paper by Kazuhiro Takemoto] Overview: Large Language Models (LLMs) are increasingly integrated into autonomous … [Read more...] about The Moral Machine Experiment on Large Language Models
Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making
🔬 Research Summary by Min Lee, an Assistant Professor in Computer Science at Singapore Management University, where he creates and evaluates interactive, human-centered AI systems for societal problems (e.g. … [Read more...] about Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making
Tell me, what are you most afraid of? Exploring the Effects of Agent Representation on Information Disclosure in Human-Chatbot Interaction
🔬 Research Summary by Stephan Schlögl, a professor of Human-Centered Computing at MCI - The Entrepreneurial School in Innsbruck (Austria), where his research and teaching particularly focuses on humans’ interactions with … [Read more...] about Tell me, what are you most afraid of? Exploring the Effects of Agent Representation on Information Disclosure in Human-Chatbot Interaction
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
🔬 Research Summary by Stephen Casper, an MIT PhD student working on AI interpretability, diagnostics, and safety. [Original paper by Stephen Casper,* Xander Davies,* Claudia Shi, Thomas Krendl Gilbert, Jérémy … [Read more...] about Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback