Name: Deepfakes flooding your feed: Why AI videos are dangerous — and how to spot them | DW News
Uploaded: 2026-01-02T13:39:24.000Z
Duration: 4 min 48 s
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Wild animal attacks, newborn babies running out of hospitals, celebrities committing crimes, all on our feeds and all AI generated.

They grab your attention, push your fear, or they make you believe things that never happened.

Adverbs of degree

AI video generators got so good that it's getting harder and harder to tell what's real and what's AI generated.

Let's have a look at why this is problematic, how they are produced and how to spot fake video.

A study found that participants were only about 50% accurate in spotting AI generated content, including audio and visual AI material.

Some of these clips, such as the running babies or cute rabbits on the trampoline, might be harmless and funny, but

social media amplifies the spread of political and emotional messages.

The broader thing here that you have to understand that's dangerous is that when we enter a world where half or more of what you see is fake, when you see the real thing, you're not necessarily going to believe it.

People are doing bad things with deepfakes and generative AI scams, frauds, non consensual imagery, child sexual abuse, disinformation campaigns.

But then when the real video of police misconduct, human rights violations, a politician saying something illegal or awful comes out, what's going to happen?

And so when you see this massive flood, everybody becomes suspicious of everything.

You've probably used chatbots like ChatGPT, Gemini, Copilot.

The technology behind them is called large language models.

Put simply, they work by using tokens, basically numbers that represent words, letters or punctuation marks.

Text to video tools are a little trickier.

They need to handle text inputs like your prompt and create videos or sound.

They are so called cross modal models, which is more or less a shared space for several AIs to work together and exchange information.

And this is how it works when you create a video with a prompt.

For example, with Google's VO3 video generator, the LLM breaks your input down into structured elements, for example, what the environment should look like, actions and emotions, and

Then a so called diffusion model creates realistic images frame by frame.

It starts with random noise and gradually refines it into a coherent image that matches the LLM's instructions.

Afterwards, a temporal model predicts how each frame should change over time, creating smooth motion and transitions.

Finally, all frames are stitched together into a complete video.

Please note, this is a very simplified explanation.

But it's also very easy to misuse Are there still ways to detect deepfakes?

Some have obvious watermarks, like this one from OpenAI's Sora 2.

Here are three tips how to detect an AI generated Video if you believe this CCTV footage, OpenAI founder Sam Altman stole GPUs in a store using an AI detection tool such as Hive.

This video is likely to contain AI generated or deepfake content 99%, even though it's clear here such AI detection tools cannot yet detect all AI fakes and are only an indication.

Zoom in and you'll see that this package moves as if by magic without the AI generated Sam Altman ever touching it.

Here you can see that the man's legs blend into the bench, even when it's hard to detect sometimes.

Often it's unnatural movements or blinding body parts that can still give it away.

When you have visuals like this, ask yourself, does any of this even make sense?

Or is this video just playing with your emotions?

But the father running through a bucket and the mother running the wrong way?

Because I would argue that if we have a society where we don't agree on basic facts of what is happening in the world, we are destabilizing societies, economies and democracies.

And that's what the combination of AI and social media are doing.

The AI generated viral hits follow a recipe as old as social media evoke strong emotions.

People that are triggered emotionally are more likely to comment or share, so check content before you share it.