No One Can Tell What’s Real Anymore
A few times a week, I get a comment or message from someone asking me to help verify whether an image or video is AI-generated. Sometimes the answer comes quickly, like when there’s a detectable watermark, known artifact, or disprovable location or timeline. In other cases, though, the verdict is murkier, leaving the content lingering in a gray zone where certainty is out of reach, but belief isn’t. It’s a perfect storm for disinformation.
Weaponized is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.
Here’s the uncomfortable reality facing us right now: there is currently no universally accepted way to determine whether an image or video is AI-generated. Not for the public, not for journalists, and not even for the engineers building the detection tools.
It’s not so much that nothing works, but that everything works only partially, and not all the time.
AI Verification: A Patchwork of Methods, With Some (Big) Holes
Today’s AI verification landscape is built from overlapping systems, with each one addressing a different piece of the problem.
Related Knowledge Center: Artificial intelligence
On top of a failing business model, newsrooms must navigate the powerful — and not fully reliable — new capabilities of artificial intelligence and the deployment of large language models.
State of the business model | Copyright and intellectual property
Related Knowledge Center: Information integrity
In an increasingly fractured media landscape, truth has been a casualty in the public discussion. Coverage has been warped by the business needs of struggling news organizations, and a significant segment of the public relies on bad-faith outlets that are little more than propagandists. While fact-checking has become routine, some organizations are exploring other ways to combat the trends. And misinformation spewed by AI-driven chatbots has become more of a feature than simply a bug.
Fact-checking and its detractors