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 apply Parasuraman et al.’s (2000) framework of four cognitive automation stages to characterize this shift. GenAI automates all four stages simultaneously: information acquisition, information analysis, decision selection, and action specification. Classical automation effects (e.g., the “lumberjack effect”) were established exclusively in trained operators working within bounded domains. Whether these effects persist, intensify, or transform when GenAI violates all previous scope conditions simultaneously remains an open empirical question. Nearly a billion people now use this technology without the empirical foundation needed to predict human performance consequences. This commentary maps how GenAI’s deployment configuration exceeds automation theory’s empirical boundaries and identifies critical research questions to guide investigation of human performance and safety in this understudied area of automation design.