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Generative AI lacks the human creativity to achieve scientific discovery from scratch
Journal article   Open access   Peer reviewed

Generative AI lacks the human creativity to achieve scientific discovery from scratch

Amy Wenxuan Ding and Shibo Li
Scientific Reports
20/03/2025

Abstract

Scientific discovery Generative artificial intelligence Large Language models ChatGPT
Scientists are interested in whether generative artificial intelligence (GenAI) can make scientific discoveries similar to those of humans. However, the results are mixed. Here, we examine whether, how and what scientific discovery GenAI can make in terms of the origin of hypotheses and experimental design through the interpretation of results. With the help of a computer-supported molecular genetic laboratory, GenAI assumes the role of a scientist tasked with investigating a Nobel-worthy scientific discovery in the molecular genetics field. We find that current GenAI can make only incremental discoveries but cannot achieve fundamental discoveries from scratch as humans can. Regarding the origin of the hypothesis, it is unable to generate truly original hypotheses and is incapable of having an epiphany to detect anomalies in experimental results. Therefore, current GenAI is good only at discovery tasks involving either a known representation of the domain knowledge or access to the human scientists’ knowledge space. Furthermore, it has the illusion of making a completely successful discovery with overconfidence. We discuss approaches to address the limitations of current GenAI and its ethical concerns and biases in scientific discovery. This research provides insight into the role of GenAI in scientific discovery and general scientific innovation.
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s41598-025-93794-9DownloadView
Open Access CC BY-NC-ND V4.0
url
https://doi.org/10.1038/s41598-025-93794-9View
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Collaboration types
Domestic collaboration
International collaboration
Citation topics
6 Social Sciences
6.185 Communication
6.185.2797 AI Ethics
Web of Science research areas
Psychology, Experimental
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