Featured Former Fellow - Samuel Schindler 11/21/25
Автор: Center for Philosophy of Science
Загружено: 2025-11-21
Просмотров: 91
Title: On the Limits of AI-driven Discovery in Science
Abstract: There has been much enthusiasm among the general public about recent developments in AI. The enthusiasm is echoed among scientists, culminating in the Nobel Prize for AlphaFold. In this paper, I want to dampen this enthusiasm slightly and articulate limits on attempts to make AI-driven scientific discoveries – understood as discoveries of new phenomena rather than ideas. To get a sense of the limitations of AI-driven discovery, I compare machine learning to standard scientific instrumentation and argue that the much-discussed opacity of machine learning restricts our ability to distinguish signal from noise. This constitutes a problem for both “target-specific” and “target-unspecific” learning regimes, but especially for the latter – arguably the more promising regime for the discovery of yet unknown phenomena – and gives rise to what I call the Aggravated Artifact Problem.
Speaker Information: https://samuelschindler.org/
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