ArticleScientific reports2025
Generative AI lacks the human creativity to achieve scientific discovery from scratch.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- A Safety-Governed Architecture for Adaptive Sequential Evidence Selection from Pre-Recorded Gait Data.Sensors (Basel, Switzerland) · 2026Article
- Autonomous artificial intelligence, scientific research, and human values.AI and ethics · 2026Article
- Recalibrating academic expertise in the age of generative AI.Patterns (New York, N.Y.) · 2026Review
- Can AI be truly creative?Nature · 2025Article
- Generative artificial intelligence models outperform students on divergent and convergent thinking assessments.Scientific reports · 2025Article
- The chain mediating role of critical thinking and AI self-efficacy in GenAI usage competence and engineering students' creativity.Scientific reports · 2025Article
- Artificial intelligence fails to outperform orthopaedic surgeons: A systematic review.Journal of experimental orthopaedics · 2025Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.