Letter to a Young Person Worrying About AI (commoncog.com)

A Commoncog forum letter to a young person worried about AI-driven job loss argues the wrong move is trying to predict precisely what will happen. The author’s core advice: stop chasing narrow forecasts and instead design your career and organizations for “fast adaptation under uncertainty.” They caution against extrapolating from single papers (for example, debates about LLM hallucinations) — noting a technical point that aleatoric uncertainty in natural language makes perfect elimination of hallucination unlikely — and warn that hype cycles regularly overstate speed and scope of disruption. The letter points readers to historical evidence showing technological displacement usually unfolds slowly because technologies sit inside sociotechnical systems (maintenance, training, regulations, supply chains, unions), so replacement takes years. Recommended reads include The Shock of the Old, The Box, and diffusion-of-innovation literature to recalibrate expectations. Practical implications for the AI/ML community and workers: prioritize monitoring real-world signals, build adaptable workflows and safety nets, invest in transition skills and systems rather than betting on one forecast, and focus research and product strategy on robustness, observability and real-world integration instead of panic-driven predictions.