An Unproven Theorem

RESEARCHERS FROM HUMAN LONGEVITY, INC. USE WHOLE GENOME SEQUENCE DATA AND MACHINE LEARNING TO IDENTIFY INDIVIDUALS THROUGH FACE AND OTHER PHYSICAL TRAIT PREDICTION (SAN DIEGO, CA)—September 5, 2017—Researchers from Human Longevity, Inc. (HLI) have published a study in which individual faces and other physical traits were predicted using whole genome sequencing data and machine learning. This work, from lead author Christoph Lippert, Ph.D. and senior author J. Craig Venter, Ph.D., was published in the journal  Proceedings from the National Academy of Sciences  (PNAS). The authors believe that, while the study offers novel approaches for forensics, the work has serious implications for data privacy, deidentification and adequately informed consent. The team concludes that much more public deliberation is needed as more and more genomes are generated and placed in public databases. For the IRB approved study, 1,061 ethnically diverse people ranging in age from 18 to 82...