Project description
AI’s impact on scientific writing and the scientific enterprise
The rise of advanced AI capable of mastering natural language has sparked debates about its role in science. While AI-generated content is increasingly present in research papers and scientific tools, its impact on science remains uncertain. Concerns centre on AI’s ability to mimic the nuanced integration of knowledge and social dynamics inherent in human scientific work. The ERC-funded scAIence project aims to rigorously evaluate how generative AI influences scientific writing, as well as the measures, algorithms and perception that are based on scientific text. Specifically, it will investigate whether AI can replicate the intricate human social networks involved. By leveraging large-scale data and controlled experiments, scAIence seeks to develop new quantitative methods and metrics to understand AI’s effects on science.
Objective
The recent The recent public release of Artificial Intelligence (AI) that can master natural language has sparked a debate about the capabilities of AI and whether it can produce scientific content. Despite the ongoing debate, AI-generated written content has already entered the world of science: Papers co-written by AI are published, companies release models to assist scientists with producing scientific content, and a large fraction of scientists use AI-based tools to augment their writing. We will thus inevitably have AI-infused science in our future. The goal of scAIence is to quantify whether, how, and with which implications generative AI is changing how scientists write, communicate, perceive, and diffuse science, and to rigorously explore the opportunities, dangers, and implications of scientists augmenting their science with AI. The key hypothesis of scAIence is that current AI lacks the ability to combine knowledge entities (e.g. references) in the same manner as humans and is unable to replicate the social information (e.g. homophily or recency) present in human scientific output. Testing the implications of this hypothesis is crucial since the scientific enterprise relies heavily on social information present in scientific output data for a wide range of purposes, e.g. metrics definition, information retrieval, and predictions. The scAIence project will deploy a novel computational social science approach, based on a wide array of quantitative disciplines, leveraging large- scale databases of human-generated information and controlled experiments. scAIence will break new ground by (i) introducing the quantitative methods required to understand AI-infused science, (ii) redefining metrics and models to account for AI-generated content in science, and (iii) delivering quantitative scientific insights into how AI is changing the diffusion of science. Taken together, scAIence will lay the scientific foundation for the quantitative study of AI-infused science.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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.
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
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2023-COG
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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.
1165 KOBENHAVN
Denmark
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