GenAI as complete cognitive automation for untrained users at population scale: implications for human factors and ergonomics

Generative AI (GenAI) systems provide complete cognitive task outputs to untrained users across unrestricted domains at population scale, creating an unprecedented form of automation. We use a foundational four-stage model of automation (information acquisition, information analysis, decision selection, and action specification) to characterise the shift: GenAI automates all four stages simultaneously. Yet the classical automation effects (such as the 'lumberjack effect') were established exclusively in trained operators working within bounded domains. Whether these effects persist, intensify, or transform when GenAI violates all of these scope conditions at once remains an open empirical question. Nearly a billion people now use this technology without the empirical foundation needed to predict its consequences for human performance. This commentary maps how GenAI's deployment configuration exceeds the empirical boundaries of automation theory and identifies the critical research questions needed to guide investigation of human performance and safety in this understudied area of automation design.