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.

The C2PA standard's effectiveness depends on a complete ecosystem of participation, from capture (cameras) to distribution (platforms). The refusal of major players like Apple and X to join creates fatal gaps, rendering the entire system ineffective and preventing a network effect.

A critical failure point for C2PA is that social media platforms themselves can inadvertently strip the crucial metadata during their standard image and video processing pipelines. This technical flaw breaks the chain of provenance before the content is even displayed to users.

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.

While camera brands like Sony and Nikon support C2PA on new models, the standard's adoption is crippled by the inability to update firmware on millions of existing professional cameras. This means the vast majority of photos taken will lack provenance data for years, undermining the entire system.

The shift from "Copyright" to "Content Detection" in YouTube Studio is a strategic response to AI. The platform is moving beyond protecting just video assets to safeguarding a creator's entire digital identity—their face and voice. This preemptively addresses the rising threat of deepfakes and unauthorized AI-generated content.

There is a significant gap between how companies talk about using AI and their actual implementation. While many leaders claim to be "AI-driven," real-world application is often limited to superficial tasks like social media content, not deep, transformative integration into core business processes.

Advocating for a single national AI policy is often a strategic move by tech lobbyists and friendly politicians to preempt and invalidate stricter regulations emerging at the state level. Under the guise of creating a unified standard, this approach effectively ensures the actual policy is weak or non-existent, allowing the industry to operate with minimal oversight.

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.