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Time

Wednesday 4 December 2024, at 14:15 - 15:45

Location

D3 (1531–215)

By Randi Mosegaard

Abstract

Machine learning (ML) systems play increasingly important roles in scientific discovery, e.g., to discover novel protein structures, recover unknown physics equations, or reconstruct broken historical artefacts. In the wake of these developments, significant conceptual disruptions (Löhr 2023) take place: central concepts we use to understand and structure scientific pursuits come under pressure, leaving unclear how to apply them and what follows from their application. This talk focuses on two disruptions of key concepts: ‘evidence’ and ‘researcher’. The concept of ‘evidence’ is disrupted by recent attempts to use generative AI systems in the historical sciences to restore partially destroyed manuscripts or artefacts. Such use-cases raise uncertainty around how to interpret their outputs: e.g. as mere hypotheses that provide reasons for considering what an artefact may have looked like, or as full-blown evidence that already entitles us to make new knowledge claims. Second, the concept of ‘researcher’ is disrupted by recent efforts to build ML systems that predict upcoming scientific discoveries and suggest hypotheses and experiments. Such systems go beyond automating execution-level tasks, such as efficiently searching a space for stable chemical compounds, and instead automate high-level agenda-setting roles, steering what to investigate and how. I argue that these novel roles played by ML systems press us to consider what it means to be a researcher, whether emerging ML systems possess abilities central to this role, and what are good divisions of labor between human researchers and machines. Together, both disruptions illustrate the need for a larger research program that examines and provides responses to these ongoing disruptions.

Bio

Donal Khosrowi is a postdoctoral researcher at Leibniz University Hannover. His work focuses on issues at the interface between the ethics of digital technology, the epistemology of artificial intelligence and machine learning, and philosophy of science.

Coffee, tea, cake and fruit will be served before the colloquium @ 2 pm.

CSS colloquium: Donal Khosrowi, University of Hannover

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