The proliferation of AI-generated content has eroded consumer trust to a new low. People increasingly assume that what they see is not real, creating a significant hurdle for authentic brands that must now work harder than ever to prove their genuineness and cut through the skepticism.

Adam Mosseri’s public statement that we can no longer assume photos or videos are real marks a pivotal shift. He suggests moving from a default of trust to a default of skepticism, effectively admitting platforms have lost the war on deepfakes and placing the burden of verification on users.

A simple method to detect a common type of real-time deepfake is to ask the person to place their fingers in front of their face. While the AI can generate realistic hands held separately, the complexity of overlaying them on the face often causes the model to glitch and break the illusion, providing a practical, low-tech verification test.

Politician Alex Boris argues that expecting humans to spot increasingly sophisticated deepfakes is a losing battle. The real solution is a universal metadata standard (like C2PA) that cryptographically proves if content is real or AI-generated, making unverified content inherently suspect, much like an unsecure HTTP website today.

The rise of convincing AI-generated deepfakes will soon make video and audio evidence unreliable. The solution will be the blockchain, a decentralized, unalterable ledger. Content will be "minted" on-chain to provide a verifiable, timestamped record of authenticity that no single entity can control or manipulate.

The rapid advancement of AI-generated video will soon make it impossible to distinguish real footage from deepfakes. This will cause a societal shift, eroding the concept of 'video proof' which has been a cornerstone of trust for the past century.

As AI makes creating complex visuals trivial, audiences will become skeptical of content like surrealist photos or polished B-roll. They will increasingly assume it is AI-generated rather than the result of human skill, leading to lower trust and engagement.

Cryptographically signing media doesn't solve deepfakes because the vulnerability shifts to the user. Attackers use phishing tactics with nearly identical public keys or domains (a "Sybil problem") to trick human perception. The core issue is human error, not a lack of a technical solution.

C2PA was designed to track a file's provenance (creation, edits), not specifically to detect AI. This fundamental mismatch in purpose is why it's an ineffective solution for the current deepfake crisis, as it wasn't built to be a simple binary validator of reality.