Now, the rise of artificial intelligence deepfakes has left him doubting his abilities, according to a New York Times (NYT) profile published Sunday (June 14).
Farid, the report said, has spent years helping government, law enforcement, journalists and human rights groups determine the difference between deepfakes and legitimate material.
His research has found that most people could no longer distinguish real photos, videos, or voice recordings from AI creations, and has begun to fail his own tests, the report added.
“I feel like I’m going blind,” Farid said, expressing concern that AI was distorting reality and hurting democracies, while taking its own toll on him. Farid and his wife are planning to leave Silicon Valley for a rural Vermont farm.
The report also describes Farid lecturing at Berkeley, telling the class that while he remained confident in his abilities, each investigation takes time, while the half-life of an average social media post was under 90 seconds.
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“Within 20 minutes, the whole ballgame’s basically over,” Farid said, meaning that by the time he finishes an analysis, a fake can become fact in the minds of the public.
“So, the creation of deepfakes is easy, cheap, fast and reliable,” one student observed. “Detection is costly and difficult.”
In addition to spreading information, deepfakes are also helping criminals carry out financial fraud, as PYMNTS wrote last week.
“Across the lending industry, a new category of fraud is emerging that combines deepfake video, cloned voices, synthetic identity creation, fabricated employment histories and AI-generated financial behavior into a single engineered persona,” the report said.
“These synthetic borrowers are not merely fake identities in the traditional sense. They are algorithmically optimized consumers designed to survive onboarding checks, satisfy underwriting models and disappear once loans are funded.”
For banks, credit unions and FinTech lenders, the report continued, the implications are transforming the usual assumptions underpinning underwriting: that fraudsters will eventually trip themselves up through inconsistency. Digital finance was designed around the belief that more data creates more certainty.
“Synthetic borrowers invert that premise,” PYMNTS added. “The risk today is that, in an AI-saturated environment, more data may simply create more convincing illusions.”
Research from the PYMNTS Intelligence report “The AI MonitorEdge Report: COOs Leverage GenAI to Reduce Data Security Losses” found that 55% of companies are turning to AI-powered cybersecurity measures. However, a lender may spend millions to create an anti-fraud infrastructure, while open-source generative AI tools reduce the cost of attack for criminal organizations.
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