Deepfakes aren’t a tech problem — they’re a policy problem. A real framework must cover the full lifecycle of media, from capture to distribution to claims of harm, balancing free expression with urgent protections against fraud, disinformation, and abuse.

Deepfakes can spark coups and fuel chaos — proving why media verification can’t rely on trust in any one company or nation. The answer lies in federated observations: independent, tamper-proof “proofs of life” that every party can verify for themselves.

Shared reality can’t survive if everyone plays by different rules. A global media verification system must work for everyday smartphone users and for those documenting war or sensitive intelligence. That means adaptable, modular verification — proof of truth that protects both credit and discretion.

Deepfakes aren’t just fake videos—they’re attacks on our senses. Every convincing fake erodes trust, and every denial of the truth exploits that doubt. Detection isn’t enough anymore; authenticity has to start at the moment of capture.

Signal, WhatsApp, and even FaceTime can’t tell you who you’re actually talking to. That’s the real risk. Today’s fraud doesn’t happen in the message—it happens in the identity of the person sending it.

Hiring fraud isn’t just a theoretical risk anymore—it’s a daily threat. With remote interviews becoming the norm, deepfakes and impersonators are slipping past even the most diligent recruiters.

A near-perfect replica of your voice can be produced with just 30 seconds of recorded audio. What is the right way to combat this threat?

As AI detection technologies evolve, they inadvertently serve as training modules for generating more deceptive deepfakes.

Phishing attacks have increased by 3,000% in the past year, and are a major driver in the increasing cybercrime losses reported globally.