Iran and the Liar’s Dividend
Candice Bryant Consulting
Strategic Intelligence & Public Affairs
In late December, protests broke out across Iran amid a deepening economic crisis. As demonstrations spread and authorities moved to suppress them, the Iranian regime imposed a near-total internet blackout beginning January 8. Amnesty International warned the shutdown was being used to conceal killings and prevent evidence from reaching the outside world.
The tactic is familiar. Internet shutdowns have long been part of Iran's playbook, designed to create doubt "and for us to be confused with who is telling the truth," experts say.
Starlink, owned by Elon Musk, has emerged as one of the few ways to pierce the blackout. Access, however, does not solve the authentication problem. The information vacuum has created space for AI-generated content to spread as real and for old footage to recirculate as new. Iranian state media has also shared images from pro-regime rallies that are “technically” authentic but staged.
The result is what researchers call the Liar's Dividend: when the information space is saturated with questionable or incomplete material, trust erodes broadly, allowing legitimate evidence to be dismissed alongside false claims.
Appearing on Special Report with Bret Baier on January 14, Iranian Foreign Minister Abbas Araghchi denied allegations that the death toll in Iran has reached 2,500 to 12,000 or more, claiming the number is in the hundreds and that calm has been restored. These statements contrast sharply with New York Times reporting of sniper fire directed at unarmed protesters.
Media manipulation is not new; what has changed is the speed, scale, and accessibility of the tools involved. As barriers to entry continue to fall, preserving trust will require wider adoption of common standards such as C2PA content credentials, which use cryptographic metadata to help establish provenance, alongside sustained cross-sector collaboration. The crisis in Iran illustrates the dual-use nature of emerging technologies like AI and the growing imperative to pursue innovation and risk mitigation in parallel.
