AI-builds-AI race heats up—with mental health in the crosshairs
Anthropic and peers are automating AI development itself: using LLMs to design, train, and optimize new models. It cuts iteration time and cost—but raises stakes on error propagation and bias.
Mental health AI is the canary. When synthetic models train on synthetic outputs, hallucination and drift compound fast. A single misaligned therapeutic recommendation, amplified through generations of AI-to-AI training, could harm millions.
Forbes analysis: the race for efficiency is outpacing safeguards.