Stanford economists argue AI should focus on human collaboration over automation

The essay critiques the current AI paradigm for ignoring key challenges like low-latency interaction, transparent process traces, and continuous human-AI collaboration. It highlights how automation’s economic appeal—reducing labor costs—overshadows broader productivity gains. The authors also trace the intellectual roots of this bias to computer science’s historical emphasis on autonomous systems, dismissing human-machine collaboration as a secondary concern. They call for a shift in research priorities, policy nudges, and market-driven experimentation to steer AI toward more collaborative, complementary roles with humans.