Room SG1, Alison Richard Building
7 West Rd, Cambridge CB3 9DP, United Kingdom
University of Cambridge, Cambridge, UK
Google map: here.
8:00 - 8:50 Registration
8:50 - 9:00 Opening Remarks
9:00 - 9:40 Lena Kästner, “The Weal and Woe of Black Box Systems”
9:45 - 10:30 Emily Sullivan, “Machine learning in science: Just a toy?”
10:20 - 11:00 Stephan Guttinger, “Beyond opacity: the challenge of automated research”
11:00 - 11:30 Coffee break
11:30 - 12:10 Vlasta Sikimić, “Values and automated grant review: normative theories or vox populi?”
12:10 - 12:50 Konstantin Genin, “Performativity and Prospective Fairness”
12:50 - 13:30 Kathleen Creel, “Don't Use Machine Learning To Evaluate Grants”
13:30 - 15:00 Lunch
15:00 - 15:40 Florian Boge, “Understanding (and) Machine Learning's Black Box & Explanation Problems in Science”
15:40 - 16:20 Mel Andrews, “Machine Learning & Science’s Theory-Free Ideal”
16:20 - 17:00 Mario Krenn, “Towards an Artificial Muse for New Ideas in Physics”
9:00 - 9:40 Eamon Duede, “Considering the (Social) Epistemology of Mixed Agent Science”
9:45 - 10:30 Mike T. Stuart, “AI increases Scientific Understanding but does not Understand”
10:20 - 11:00 Atoosa Kasirzadeh, “On the Performativity of Machine Learning Prediction”
11:00 - 11:30 Coffee break
11:30 - 12:10 Andre Curtis-Trudel, “Does the No Miracles Argument Apply to AI?”
12:10 - 12:50 Daniel Andler, “AI in science today and tomorrow?”
12:50 - 13:00 Closing Remarks