HF

Hany Farid

Things Hany Says on Podcasts

Where to Find Them

Hany Farid has been a guest on Particles of Thought (5 times) , NOVA Presents (5 times) , After the Fact (3 times) , The Lawfare Podcast (2 times) , Terms of Service with Clare Duffy (2 times) , Harvard Data Science Review Podcast (2 times) , On with Kara Swisher (2 times) , FT Tech Tonic (2 times) , Click Here , The Lawfare Podcast: Patreon Edition , The 404 Media Podcast , Digital Disruption with Geoff Nielson , Settle In with PBS News , Marketplace All-in-One , Scaling Laws , TechStuff , TRM Talks and Bold Names .

Recently: “If deepfakes are getting better, can we trust our lying eyes?” on Click Here (October 2026); “AI Has Made Everything Worse | Hany Farid on the Internet's Truth Problem” on Digital Disruption with Geoff Nielson (August 2026); “The Future of Deepfakes and the Decline of Reality with Hany Farid” on The 404 Media Podcast (August 2026); “Why audio deepfakes are so hard to spot” on Marketplace All-in-One (May 2026); “AI Is Coming for Blue Collar Jobs | Hany Farid” on Particles of Thought (March 2026); “AI Is Coming for Blue Collar Jobs | Hany Farid” on NOVA Presents (March 2026).

What They Said

“You are in a lab setting. We've set you up for success. It is not politically charged. It is not emotionally charged. Now, imagine you are in social media, doom scrolling, politically charged, emotionally charged. You're way worse at it in that situation, but they don't know it. … I don't mind you being bad at something as long as you know you're bad at it, but they're bad at it and they're confident in the wrong assessment.” — Hany Farid, Click Here

Farid's research found that people are only slightly better than chance at spotting AI-generated fakes, even though most believe they are good at it. Here he explains why real-world conditions make people worse still.

Click Here · 2026-10-20 Permalink → Listen →
Click Here Around 14:52 into the episode
Speaker 4

…stealing somebody's voice and their likeness. And it's really, these are nasty and people aren't ready for it. Like we've gotten, maybe we've gotten ready for the spams and the malwares and the go out and buy me, you know, music gift card. But this one, I don't think people are fully prepared for.

Dina Temple-Raston

And here's the wildest part. If you ask someone if they think they're good at spotting fakes, most people will tell you they are. Hani has actually tested that. And it turns out, humans are actually pretty bad at it. His research shows our ability to spot a fake is just slightly better than chance.

Hany Farid

And here's the thing. You are in a lab setting. We've set you up for success. It is not politically charged. It is not emotionally charged. Now, imagine you are in social media, doom scrolling, politically charged, emotionally charged, things that you ideologically feel strongly about. You're way worse at it in that situation, but they don't know it. And that's really interesting. I don't mind you being bad at something as long as you know you're bad at it, but they're bad at it and they're confident in the wrong assessment.

Dina Temple-Raston

And apparently, we have evolution to thank for some of this.

Hany Farid

Our visual system didn't evolve to think, is this thing real or not? We are out in the world. And if we saw a tiger, run. There was no question of, well, is that really a tiger? You just ran and that's how you survived. But in this modern world, in this modern AI world, we have to really figure out…

Dina Temple-Raston

So what does a guy who knows just how easy it is to impersonate someone do to protect himself? Well, for starters, he and his wife have a secret code word, something they can ask each other if they ever get a suspicious phone call. But Hani has a less secret spy recommendation for the rest of us.…

Speaker names from our own diarization · position estimated from where the line sits in the episode
“When we do an analysis and we find an inconsistent shadow or lighting or reflection or geometry, we usually get to the other end and say, okay, we found something that is evidence of manipulation or AI generation. … But when you don't, when you run the battery of tests, you get to the end and you say, well, we found no evidence of manipulation. And that's not the same as saying something is real or authentic. It's subtly but really importantly different.” — Hany Farid, Click Here

Farid, a digital forensics expert, explains why proving an image is fake is easier than proving it is real. The host then points out the loophole this opens: anyone can dismiss genuine footage as a fake.

Click Here · 2026-10-20 Permalink → Listen →
Click Here Around 08:25 into the episode
Hany Farid

…views. So by the time the fact check goes out there, this content is everywhere. And setting the record straight is exceedingly difficult. I'm far more worried about that aspect of lies than I am about figuring out the truth. Time is not on our side because of the speed at which social media moves.

Dina Temple-Raston

There's also this strange imbalance. Hani can usually prove something is fake, but proving it's real is a lot harder.

Speaker 4

When we do an analysis and we find an inconsistent shadow or lighting or reflection or geometry or some pattern, we usually get to the other end and say, okay, we found something that is evidence of manipulation or AI generation. And you can hang your hand on that. But when you don't, when you run the battery of tests, you sort of get to the end and you say, well, we found no evidence of manipulation. And that's not the same as saying something is real or authentic. It's subtly but really importantly different.

Dina Temple-Raston

And that distinction has created a rather convenient loophole. Because now, even when there's no evidence that something is fake, you can just say it is. Consider Donald Trump. Back in 2016, a recording surfaced of him talking about women with an access Hollywood host.

Speaker 4

I just start kissing them. It's like a magnet. I don't even know what. And when you're a star, they let you do it. You can do anything. Whatever

Speaker 3

you want.

Speaker names from our own diarization · position estimated from where the line sits in the episode

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