Imagine a courtroom where key evidence — a video of the defendant confessing to a crime — is so convincing that the judge and jury have little reason to doubt its authenticity.

The recording plays, showing the defendant detailing the crime in their own voice, with familiar gestures and expressions. The jury is moved, convinced by the video’s clarity and the confidence of what appears to be a genuine confession. A conviction is handed down, seemingly beyond doubt.

Months later, new information surfaces: The video was a deepfake, an AI-crafted fabrication made to resemble the defendant with stunning accuracy. The conviction is overturned, but the damage has been done. The defendant’s life and reputation have suffered irrevocably, public trust in the legal system is shaken, and significant court resources are spent untangling the deception.

This hypothetical is not far-fetched — it’s a near-term risk as deepfake technology advances. The term deepfake — a blend of “deep learning” and “fake” — refers to a sophisticated manipulation of audio, video or images using AI.

By training algorithms on extensive datasets, deepfake technology can create uncannily realistic yet entirely fabricated portrayals, making it increasingly difficult to distinguish fact from fiction.

The pervasive threat of deepfakes has already been shown in other high-stakes environments.

In 2021, cybercriminals deepfaked the voice of an unnamed company’s director, successfully authorizing the fraudulent transfer of $35 million.[1]

In 2022, a manipulated video of Ukrainian President Volodymyr Zelenskyy allegedly surrendering to Russian forces circulated widely online, briefly shaking public trust before it was debunked.[2]