作者:Besford, Quinn A.
Generative AI has made it trivial to generate fake microscopy images that are indistinguishable from real images, even for experts. As researchers in nanoscience, it is time for us to face this reality and discuss strategies to conserve the integrity of our discipline.
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The authors sincerely thank V. Foliush for initially shocking us with AI replication of experimental images, P. Formanek, K. Werner Stöckelhuber and E. Bittrich for discussions, and all anonymous participants in our online survey. Q.A.B., A.F., G.K.A., L.M.L.-M, and N.A.K. acknowledge support from the Deutsche Forschungsgemeinschaft (DFG) with project IDs 496201730 (Q.A.B), 451785257 (A.F.), 391977956-SFB 1357 (G.K.A), and RTG 451785257 (L.M.L.-M. and N.A.K.). W.J.P. was supported by the Cluster of Excellence 'Advanced Imaging of Matter' of the DFG - EXC 2056 - project ID 390715994. S.B., N.A.K., and L.M.L.-M. acknowledge funding from the European Research Council through ERC Synergy Grant Chiral-Pro (project ID 101166855). E.K. acknowledges funding by the Federal Ministry of Education and Research of Germany (BMBF) in the programme NanoMatFutur (grant no. 13XP5098).
The authors declare no competing interests.
Davydiuk, N., Krieg, E., Gaitzsch, J. et al. The rising danger of AI-generated images in nanomaterials science and what we can do about it. Nat. Nanotechnol. (2025). https://doi.org/10.1038/s41565-025-02009-9
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DOI: https://doi.org/10.1038/s41565-025-02009-9