Tag: deepfakes

I find a lot of people seem to think they can glance at an online video and quickly figure out if it’s real or not.

They can’t.

Studies put human detection rates near chance for good video “deepfakes” and AI generated content.

The technology has gotten so advanced that there’s no easy, reliable way to spot every deepfake or AI-generated video by eye alone. Discernment is important because a convincing clip can drive outrage, move markets, or worse. In 2024 there was a case involving a deepfaked video-call and participants made roughly $25 million in financial transfers based on the call. Several years ago on my TV program “Full Measure,” I spoke with experts on national security fears that a good deepfake of a president making a statement could start a war before the video was ever exposed as a fraud.

Even in today’s environment where people are on alert for fakes, videos can feel more “real” than text, so they spread faster and hit harder. Knowing the common tells—and, more importantly, how to check context and source—gives you a better chance of pausing before you share, act, or believe.

Read on for details.

Here’s a practical guide for detecting AI videos.

Length

One of the most consistent patterns I’ve noticed is that many realistic AI videos and deepfakes circulating on social media are short: often 6–10 seconds. Digital forensics expert Hany Farid has pointed out that the vast majority of clips he’s asked to verify fall in that range. The fact is: generating longer, coherent video is still computationally expensive for many tools, and longer clips give the AI more chances to glitch.

Missing context

These clips frequently show only the dramatic moment: the confrontation, the shocking statement, the heartwarming rescue, or the “gotcha.” They skip what led up to it and cut off before the aftermath.

Framing

Short, tightly framed emotional clips that leave you with almost no surrounding information are a strong reason to consider they may be fake.

Editing

Creators also stitch short segments together, which can produce noticeable cuts every few seconds.

Visual and audio clues

We’ve already learned to look for the obvious signs of extra fingers and limbs. I still think it’s weird that AI can’t always figure out humans generally have four fingers and a thumb. Even when it’s instructed to create that kind of a hand, it sometimes cannot.

I’ve been watching Medicare commercials that clearly use AI-generated people and images. The lips don’t perfectly match the sounds coming from them. The voice seems too perfect.

But what about less obvious clues and better deepfakes?

Slow the video (0.25x or 0.5x if possible) and pause on movement. Look for lip-sync and mouth issues. Real lips usually close fully on plosive sounds like “p,” “b,” and “m.” Deepfakes and lip-synced AI often drift by a frame or two, or the mouth interior looks off.

Blinks that are too regular, too rare, or mistimed with speech are another possible sign. So are eyes that look glassy or have mismatched reflections and expressions that don’t quite match the words or the rest of the face.

Watch for warping, smearing, or a soft “halo” around the jaw, hairline, ears, or where the face meets the background—especially when the head turns quickly or something crosses in front of the face such as a hand or a microphone.

Unnaturally smooth or waxy skin compared with the neck or hands can be a sign of deepfakes. So are teeth that look like a solid white block.

Be on the lookout for shadows pointing the wrong way, lighting on the face that doesn’t match the room, objects that float or pass through each other, or garbled text on signs, screens, or clothing. Sometimes background elements morph or behave impossibly.

Voices that sound too clean or flat are suspect. So are missing natural room tone— the sort of natural background sounds in a room— breathing, and pauses. At times you may detect the emotion doesn’t match the delivery.

These clues are more reliable indicators of AI videos when you find several of them together.

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Federal judges meeting in Boston heard tech industry warnings that AI-generated images and video are becoming nearly impossible to verify, as a judiciary committee considers whether courts need new rules for evidence that may be deepfakes instead of the real thing.

Reuters reports that the U.S. Judicial Conference’s Advisory Committee on Evidence Rules has spent three years, since 2023, studying how courts should handle evidence that may have been faked or altered using artificial intelligence. At Thursday’s meeting, representatives from OpenAI and Meta told the panel that detecting such fakes is only going to get harder.

“AI images are only getting better, and I do not think that there will be a scientific way going forward to detect them,” said Shira Anderson, OpenAI’s policy counsel.

Devin Norder, Meta’s director of product management, told the committee that the latest generation of AI models produces media that people simply cannot tell apart from the real thing. “Media generated from frontier models, at least in the last few generations, are indistinguishable by humans from authentic or AI-generated media,” Norder said. He added that producing convincing fakes no longer takes much effort or money: “And the cost and the time it takes to create this media really are quite trivial at this point.”

Both companies have built tools meant to verify whether visual content is authentic, and lawmakers have started moving the same way. California and the European Union have each passed laws requiring “watermarking” designed to flag AI-generated material. But Anderson cautioned that no single system can catch everything, since different companies’ tools don’t talk to each other. “My guess is that this absolutely will continue to get better. I do not think it’ll ever be bulletproof,” she said.

Despite the warnings, the committee has found little evidence that deepfakes are actually showing up in courtrooms. A survey released in March by the Federal Judiciary Center, the judiciary’s research arm, polled 931 judges and found that only 15 had handled a case in which someone challenged evidence as a deepfake. US District Judge Jesse Furman of Manhattan, who chairs the committee, pointed to that gap between prediction and reality. “There’s a lot of academic commentary and other commentary predicting that courts will be dealing with deepfakes, but we haven’t actually seen a whole lot of that yet,” Furman said.

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In the “old” days of the internet, you perhaps had to be wary of some creep in a chat masquerading as an appealing romantic interest. But that was small ball. Today some men are falling for gorgeous female “influencers” — who happen to be generated via artificial intelligence (AI). The kicker:

Some people are trying to forge relationships with these digital fictions even when knowing they’re AI-generated.

The appeal is that with current technology, these “digi-entities” appear, behave, and interact just as real women do. (But without the moodiness?) What’s more, you ain’t seen nothin’ yet.

When this AI is ultimately combined with ultra-sophisticated robotics, we could have real-life “Stepford Wives.” (This references the eponymous 1970s story about a town whose married women are gradually replaced with identical-looking, subservient, domesticity-oriented androids.) Moreover, this phenomenon’s acceptance is wholly congruent with today’s prevailing secular mindset.

After all, a corollary of atheism is that we’re just material beings — some pounds of chemicals and water. Another way of putting it:

We’re mere organic robots.

And what would be wrong with replacing sub-optimal robots with more pleasing ones?

“Domo Arigato, Mr. Roboto”

For now, however, that kind of real-woman realism (not to mention the affordability factor) is only found in the digi-entities. Reporting on the story Sunday, ZeroHedge cites the New York Post and, providing digi-entity examples, writes:

One widely followed pro-MAGA persona, for example, was ultimately exposed as “nothing more than an algorithm run by a guy in India,” revealing just how convincingly these accounts can mimic authenticity.

Despite that, audiences continue to engage — often deeply. Many followers, particularly older men, are “falling for them left, right and center.” Experts suggest this isn’t just about deception, but about a deeper emotional gap. Some describe the phenomenon as a “pandemic of loneliness,” even pointing to a broader “societal loss of humanity” as people increasingly form attachments to digital illusions instead of real relationships.

What’s striking is that these accounts don’t always hide the truth. Some openly identify as AI and still attract admiration. Take Ana Zelu, a fictional influencer who clearly labels herself an “ai-influencer,” yet maintains a highly curated feed filled with aspirational imagery — luxury travel, fashionable outfits, and picturesque city scenes. Her posts draw enthusiastic responses, with followers commenting things like “Number one is my favourite…May God bless you,” and “You are genuinely in a class of your own.” The awareness that she isn’t real doesn’t seem to diminish the appeal.

The Post writes that a similar pattern appears with Milla Sofia, another digital creation presented as a pop singer. Her content includes stylized videos and performances, and although her profile identifies her as virtual, fans respond as if she were a real celebrity. Comments such as “my sweet love,” “Listening to the music of this woman I love,” and “I love you” reflect genuine emotional investment.

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