Episode 264 - Fingerprints Proven by AI to Not Be Unique!

Double Loop Podcast

Eric and Glenn respond to the recent allegations that a computer science undergraduate at Columbia University, using Artificial Intelligence, has “proven that fingerprints aren’t unique” or at least…that’s how the media is mischaracterizing a new published paper by Guo, et al. The guys dissect the actual publication (“Unveiling intra-person fingerprint similarity via deep contrastive learning” in Science Advances, 2024 by Gabe Guo, et al.). They state very clearly what the paper actually does show, which is a far cry from the headlines and even public dissemination originating from Columbia University and the author. The guys talk about some of the important limitations of the study and how limited the application is to real forensic investigations. They then explore some of the media and social media outlets that have clearly misunderstood this paper and seem to have little understanding of forensic science. Finally, Eric and Glenn look at some quotes and comments from knowledgeable sources who also have recognized the flaws in the paper, the authors’ exaggerations, and lack of understanding of the value of their findings. Gabe Guo et al. ,Unveiling intra-person fingerprint similarity via deep contrastive learning.Sci. Adv.10, eadi0329(2024). DOI:10.1126/sciadv.adi0329 https://www.science.org/doi/10.1126/sciadv.adi0329 https://www.engineering.columbia.edu/news/ai-discovers-not-every-fingerprint-unique https://for-sci-law.blogspot.com/ https://www.cnn.com/2024/01/12/world/fingerprints-ai-based-study-scn/index.html