Send us a text

The established practice of Human-in-the-Loop (HITL) oversight is obsolete, posing significant risks and economic limitations for modern AI development. The analysis demonstrates that human physiological latency renders intervention dangerous in high-velocity kinetic environments like autonomous vehicles, while the linear costs of human labor cannot meet the exponential scaling demands of training massive language models. Cognitively, the human operator acts inconsistently and is susceptible to automation bias and being manipulated by novel attacks such as "Lies-in-the-Loop," compromising security rather than enhancing it. Furthermore, the reliance on human labor for moderation causes severe and documented psychological trauma, making the current ethical framework fundamentally unsustainable. Finally, the authors contend that human supervision will be theoretically impossible as AI approaches superintelligence, advocating instead for a rapid transition to automated governance systems like Constitutional AI and Reinforcement Learning from AI Feedback (RLAIF).