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

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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Publication Details

Journal
Scientific Reports
Published
2025-03-20
DOI
https://doi.org/10.1038/s41598-025-93794-9
Citations
19
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
9.84
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article

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

Amy Wenxuan Ding, Shibo Li
19 citations
Scientific Reports
Machine Learning in Materials Science
9.84
article

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

Amy Wenxuan Ding, Shibo Li
article en
19 citations

Abstract

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.

Scientific ReportsVol. 15(1)
Indiana University Bloomington (US), École de management de Lyon (FR)
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Machine Learning in Materials Science
9.84
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