AI needs to serve people, science, and society: a vision for ai@cam
Neil Lawrence and Jess Montgomery set out Cambridge’s vision for a flagship AI mission that serves science, citizens and society.
AI for Science — an emerging agenda
8 March 2023
AI for Science — an emerging agenda
8 March 2023
Philipp Berens, Kyle Cranmer, Neil D. Lawrence, Ulrike von Luxburg and Jessica Montgomery have published AI for Science: an emerging agenda, the report of Dagstuhl Seminar 22382, “Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling”.
The seminar treated AI for science as a meeting point: expertise from machine learning and from application domains, modelling knowledge alongside engineering practice, and collaboration across disciplines and between people and machines. The report argues that the next wave of progress will come from that community — machine learning researchers, domain experts, citizen scientists and engineers — designing and deploying tools together, not from technical advances alone.
The report is available on arXiv. It sits alongside the Accelerate Science programme’s work on interdisciplinary use of AI in research.
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