Welcome to Youthquake, where we explore the tech trends shaping our world. Today, we’re tackling a critical issue: "When A.I.’s Output Becomes a Threat to A.I. Itself." As artificial intelligence generates more content, this data increasingly circulates back into future A.I. training. This feedback loop can lead to what researchers call "model collapse," where A.I. systems degrade over time, producing less accurate, diverse, and reliable outputs. Imagine a medical chatbot misdiagnosing symptoms because it’s trained on previous A.I.-generated content, or an educational A.I. spreading misinformation. The New York Times highlights this as a growing concern, with AI-generated content flooding the internet. Companies are racing to develop solutions, like filtering out A.I. outputs or curating high-quality human data. But the challenge is immense. As we continue to rely on A.I., we must be vigilant to ensure these systems don’t become a threat to themselves—and us.