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Reframing AI’s role in scientific discovery

3 September 2026

Reframing AI’s role in scientific discovery

3 September 2026

Kyle Cranmer, Neil Lawrence, Jessica Montgomery and Denis Thérien have published AI for Science: Reframing AI’s Role in Discovery in RSS: Data Science and Artificial Intelligence.

The paper asks how AI actually contributes to science, and warns that inflated claims hide both present limits and longer-term possibilities. It organises that contribution around task capabilities, integration into scientific workflows, and the constraints of particular domains. From there it opens questions the field has not settled: whether knowledge that people cannot inspect still counts as scientific understanding; what it would take to move systems from pattern matching toward causal reasoning; and which institutional changes responsible adoption requires.

The article marks the opening of a call for papers from RSS Data Science and AI. It continues a line of work that includes the 2023 Dagstuhl report and the 2024 Royal Society Open Science paper on accelerating AI for science.

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