AI Challenges the Uniqueness of Fingerprints

Recent AI research challenges the belief that all fingerprints are unique, as undergrad researchers at Columbia Engineering found that the angles and curvature at the center of fingerprints could be the same across an individual. Using a deep contrastive network and a US government database of 60,000 fingerprints, the team discovered that the network could identify if prints were from the same person with 77 percent accuracy, potentially aiding in solving cold cases and prioritizing leads in ambiguous situations. The results are set to be published in Science Advances on January 12.