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