The ability to label a deepfake as 'fake' doesn't solve the problem. The greater danger is 'frequency bias,' where repeated exposure to a false message forms a strong mental association, making the idea stick even when it's consciously rejected as untrue.

The rise of photorealistic, real-time deepfakes will make it impossible to trust who you're speaking with on video calls. This will necessitate a "proof of human" layer for platforms like Zoom, especially for high-value conversations like financial transactions where impersonation poses a significant threat.

AI-generated scams are now so convincing that even sophisticated users are fooled. The responsibility has shifted from teaching customers to spot fakes to brands proactively deploying technology to take down threats. Blaming the customer is irrelevant as the brand still loses trust and revenue.

The biggest political danger of deepfakes isn't that people will believe fake content. It's the "liar's dividend": politicians can now dismiss genuine, scandalous video evidence as a deepfake. This erodes video as a tool for accountability, a more subtle but profound threat to political discourse.

The most immediate cybersecurity threat from advanced AI isn't a sophisticated system breach. Instead, it's the ability to use AI to massively scale "old school" fraud like impersonation and phishing attacks, tricking individual people at an unprecedented rate and volume.

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.

Beyond generating fake content, AI exacerbates public skepticism towards all information, even from established sources. This erodes the common factual basis on which society operates, making it harder for democracies to function as people can't even agree on the basic building blocks of information.

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.