AI-generated media is rapidly eroding the public’s ability to distinguish reality from fabrication, according to Hany Farid, a prominent digital forensics expert and co-founder of cybersecurity firm GetReal. Farid, a former University of California, Berkeley professor who pioneered the field in 1999, warns that generative artificial intelligence has fundamentally dismantled the perceptual safeguards that once separated authentic content from manipulation. When Farid began studying digital evidence in the late 1990s, the internet and social media were nascent, and the concept of pervasive media forgery was not considered a societal threat. Early digital manipulation required significant technical skill, leaving behind detectable artifacts such as misaligned shadows, geometric inconsistencies, and editing metadata. While computational tools could reliably identify these flaws, the average internet user lacked the expertise to spot them, though the volume of content was manageable. That dynamic has shifted dramatically. Modern generative AI requires only a text prompt and an internet connection to produce photorealistic images, synthetic voice recordings, and increasingly coherent video clips within seconds. Farid notes that while AI still struggles to fully replicate three-dimensional physics and lighting, the visual and auditory output has crossed the threshold of human detectability, particularly in the short-form videos that dominate social platforms. The technological leap presents a critical structural problem for verification. Computational forensics can still detect subtle physical implausibilities in AI-generated content, but authenticating or debunking a piece of media typically requires about an hour of rigorous analysis. In an environment where content can amass millions of views and shape public discourse in minutes, this delay is functionally catastrophic. Fact-checking has effectively become a postmortem exercise, arriving after misinformation has already entrenched itself in the public consciousness. Farid emphasizes that while the average social media user cannot rely on human perception to filter synthetic media, specialized tools can isolate fakes, yet the velocity of the internet consistently outpaces institutional response times. Beyond the technical arms race between generation and detection, Farid identifies a deeper societal consequence: the gradual dissolution of a shared factual reality. He argues that democratic societies depend on a common baseline of observable truth to facilitate productive debate on policy, governance, and international relations. When synthetic media makes it impossible to agree on basic events, discourse devolves into fundamental epistemological conflict. The inability to distinguish verified reporting from AI fabrication threatens the informational infrastructure required for stable governance and informed citizenship. As generative models continue to improve, become cheaper, and achieve near-universal accessibility, the challenge will no longer be solely about identifying individual fakes, but about rebuilding trust in digital evidence at scale.