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Philosophical Foundations of Automated Scientific Discovery

Objective

"The Nobel Turing Challenge from 2021 calls for developing ``AI Scientists capable of autonomously carrying out research to make major scientific discoveries worthy of [a] Nobel Prize and beyond by 2050."" (https://www.nobelturingchallenge.org/(opens in new window)). A decade before, the Nobel Turing challenge would have seemed ridiculously optimistic: automated discovery was still mainly associated with rule-based systems like DENDRAL, EURISCO, or BACON, which had fallen short of delivering on any promise to enable more general approaches to scientific discovery. However, recent advancements in machine learning, particularly deep neural networks (DNNs) and large language models (LLMs), have significantly reignited work in automated scientific discovery. Symbolic regression has advanced significantly, AI systems are increasingly being presented as ``AI scientists"", and foundation models tailored for scientific applications are being developed.
The project will subject an innovative and potentially game-changing interdisciplinary field of science---that of automated scientific discovery---to a much needed philosophy of science investigation. The project has three major goals: The first goal is to assess the state-of-the-art of automated scientific discovery through the lens of the philosophy of science. The second goal is to design novel benchmarks of automated discovery systems based on so far neglected insights from the philosophy of science. The third goal is to integrate insights from the workings of automated discovery systems into our general understanding of how scientific discovery works. To keep the scope of the project under a controllable size, and to optimise synergy with the applicant’s background, the project deals with automated discovery in physics specifically.
The three goals will be addressed by the PI, a postdoc, and a PhD student by paying close attention to current scientific practice, supported by an international advisory board of experts."

Fields of science (EuroSciVoc)

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2026-STG

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Host institution

UNIVERSITE DE GENEVE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 457 528,00
Address
RUE DU GENERAL DUFOUR 24
1211 Geneve
Switzerland

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Region
Schweiz/Suisse/Svizzera Région lémanique Genève
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 457 528,00

Beneficiaries (1)