From the NY Times: ...[Hany Farid] rode down from the hills on his motorcycle to give his last public lecture of the spring semester at Berkeley, passing the A.I. billboards that had become ubiquitous across the Bay Area. They were for start-ups promising to reinvent medicine, disrupt education and transform the future of business. “Stop Hiring Humans,” one billboard read. Farid parked on campus and walked into the lecture hall, where 75 students looked back at him.
He was one of Berkeley’s most popular professors* — kinetic, unfiltered and genuinely thrilled by the advancements in A.I. technology at the heart of his courses. He had A.I. agents that wrote code for him. He had a car that could drive itself on the highway. He had apps on his phone that could tighten the phrasing in his emails or turn a photo of his spice drawer into a recipe for weeknight chili. But the computer science majors in his classes were struggling to find jobs as companies waited to see what machines could do first. For the first time in his career, Farid sometimes stood in front of students and found himself at a loss for what to tell them...
“This technology is being weaponized against us,” he told the students. “The train has left the station. It’s accelerating at a speed that’s unbelievable.” ...
He paced at the front of the room and started to show slides of A.I. videos from the last several years. A fake image of the Pentagon exploding had briefly rattled the stock market in 2023, erasing more than $500 billion in a few minutes. Deepfakes from the war in Ukraine were still fairly easy to identify, with discolored explosions and misshaped buildings. Gaza fakes were much better. By the start of the Iran war, short A.I. footage was essentially indistinguishable from real video. Now thousands of North Korean government operatives were applying for remote jobs at U.S. companies, using A.I. to impersonate Americans in real time on Zoom calls and then funding a nuclear weapons program with their salaries. A nontechnical criminal, Farid said, could now use a still photograph and a 10-second audio clip to shape shift into anyone online.
“You might think you can look and tell the difference while you’re sitting there doom scrolling,” he said. “Believe me, you can’t. That’s where our methods come in.”
He had helped invent algorithmic tools to verify a person’s mannerisms, vocal inflections and blood flow. When a real person spoke, the eyes dilated and the heart pumped blood in and out of the face. Farid could sometimes measure subtle differences in skin color to see a person’s heart beating in real time, whereas an A.I. avatar was flatlined.
Farid said he was still confident that he could solve almost any A.I. mystery, but the problem was that each investigation took time. The half-life of an average social media post was less than 90 seconds. “Within 20 minutes, the whole ballgame’s basically over,” Farid said. Many times, he finished his analysis, looked up from his computer and realized the damage was already done. A fake had hardened into a fact. A fact had blurred into doubt.
A hand went up in the audience, and Farid pointed to a student in the front row.
“So, the creation of deepfakes is easy, cheap, fast and reliable,” the student said. “Detection is costly and difficult.”
“Yes,” Farid said.
“Is there a solution in the near future, or are we just screwed?”
He paused and took a breath. He thought about the Orozco mural, the school in Iran, the deepfakes piling up in his inbox and the farm waiting in Vermont. He still believed there were solutions. But first, he wanted people to understand what they were up against.
“We’re pretty screwed,” he said...
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Full story at https://www.nytimes.com/2026/06/14/us/ai-deepfake-hany-farid.html.
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