Presenter Dmitrii Usynin, Technical University of Munich I am a PhD student at the Joint Academy of Doctoral Studies (JADS) launched between Imperial College London and Technical University of Munich. My research interests lie on the intersection of collaborative machine learning (CML) and trustworthy artificial intelligence (TAI). In particular, I am interested in topics such… Continue reading Dmitrii Usynin | Meaningfully evaluating large-scale machine learning under privacy constraints
Presenter Greg Leppert, Harvard Greg Leppert is the Executive Director of the Institutional Data Initiative at Harvard, a research initiative working to refine and publish library, academic, and government collections as public datasets for AI training. He is also the Chief Technologist of Harvard’s Berkman Klein Center. Before academia, Greg built startups in NYC and… Continue reading Greg Leppert | The Most Boring Dataset in the World
Abstract: Internet users often neglect important security actions (e.g., installing security updates or changing pass-words) because they interrupt users’ main task at inopportune times. Commitment devices, such as reminders and promises, have been found to be effective at reducing procrastination in other domains. In a series of on-line experiments, we explored the effects of reminders… Continue reading Serge Egelman | 2024 Norm Hardy Prize Seminar
Presenter Roland Pihlakas Roland Pihlakas, MSc in psychology, is an experienced AI software engineer who has been working on multi-objective value problems for almost 20 years, and has followed discussions on AI Safety since 2006. His thesis topic was about modelling of innate learning and planning mechanisms, which eventually form a foundation for culturally acquired… Continue reading R. Pihlakas | Biologically and Economically Aligned Multi-objective Multi-agent AI Safety Benchmarks
