A Forensic Expert Examined the Eric Swalwell Videos. Here’s What He Found.
By Hugh Cameron
Videos appearing to show Eric Swalwell kissing a woman in a hotel bed were verified as authentic and do feature the now-resigned California Democratic representative, according to a forensic report of the footage obtained by Newsweek.
Commissioned and prepared in early January, a digital forensics expert employed several methods to determine that the video was an authentic recording—not AI-generated or -manipulated—and said that his “biometric analysis” was “consistent with the conclusion that the appearance of the adult male in the videos matches Representative Eric Swalwell.”
Newsweek has contacted the author of the report for further information. Newsweek has also contacted Swalwell’s attorney via email for comment.
Swalwell suspended his campaign for California governor days after reports from the San Francisco Chronicle and CNN detailed allegations from multiple women against him, ranging from sexual harassment to rape. Swalwell has denied those allegations against him, with his legal representative calling them “a calculated and transparent political hit job.”
On Tuesday he resigned from Congress amid growing calls to do so as lawmakers from both parties pushed for his expulsion, just hours before a fifth woman came forward with new allegations...
The author, Hany Farid, is a computer scientist and leading digital forensics expert, and was tasked with assessing whether the videos were AI-generated, digitally altered, authentic, and whether these depicted Swalwell.
His analysis of the metadata reveals that the videos were shot on an Apple device in Las Vegas, Nevada at around 5 a.m. PT on July 13, 2021. The report said that the video resolution was “consistent with a video recorded through the Snapchat application on an iPhone.”
“There are no obvious visual anomalies in either video that would suggest that the videos are AI generated or otherwise manipulated,” the report reads...
Hany Farid is a professor in the Department of Electrical Engineering & Computer Sciences and the School of Information at UC Berkeley
