Deepfake

A deepfake is AI-generated synthetic media (video, audio, or image) realistically mimicking a real person. Using deep learning (a special type of artificial intelligence), it looks genuine with minimal manipulation evidence. The term comes from “deep learning” + “fake”.

How is deepfake made? The algorithm is trained on hundreds or thousands of photos/videos of a real person. Then, AI can generate new videos where that person appears speaking, walking, or doing things they never did. Technically possible through technologies like GANs (Generative Adversarial Networks).

Practical deepfake examples: (1) Video of famous politician saying something never said; (2) “Pornographic deepfake”—video seeming to show known person in pornographic content (without consent); (3) Audio deepfake—sound sounding like someone but isn’t.

Deepfake dangers: (1) Misinformation—false news spreads quickly; (2) Abuse—sexual blackmail, fake video for humiliation; (3) Identity theft—using deepfake to pretend being someone; (4) Democratic problems—fake videos of candidates during elections can alter results; (5) Reputational damage—even after proving it’s fake, damage is done.

How to protect against deepfakes? (1) Be skeptical—if video looks odd or unnatural (eyes not blinking naturally), might be deepfake; (2) Check sources—if hearing first from suspicious source, likely deepfake; (3) Deepfake detectors—AI tools attempting deepfake detection; (4) Legislation—more countries passing laws prohibiting malicious deepfakes.

For startups: If developing AI technology, responsibility is not enabling deepfake misuse.