TY  - RPRT
        AU  - Askitas, Nikos
        TI  - Notes on a World with Generative AI
        PY  - 2025/Aug/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 18070
        UR  - https://www.iza.org/index.php/publications/dp18070
        AB  - Generative AI (GenAI) and Large Language Models (LLMs) are moving into domains once seen as uniquely human: reasoning, synthesis, abstraction, and rhetoric. Addressed to labor economists and informed readers, this paper clarifies what is truly new about LLMs, what is not, and why it matters. Using an analogy to auto-regressive models from economics, we explain their stochastic nature, whose fluency is often mistaken for agency. We place LLMs in the longer history of human–machine outsourcing, from digestion to cognition, and examine disruptive effects on white-collar labor, institutions, and epistemic norms. Risks emerge when synthetic content becomes both product and input, creating feedback loops that erode originality and reliability. Grounding the discussion in conceptual clarity over hype, we argue that while GenAI may substitute for some labor, statistical limits will, probably but not without major disruption, preserve a key role for human judgment. The question is not only how these tools are used, but which tasks we relinquish and how we reallocate expertise in a new division of cognitive labor.
        KW  - automation and outsourcing
KW  - technological change
KW  - labor economics
KW  - autoregressive models
KW  - Large Language Models
KW  - Generative Artificial Intelligence
KW  - human-machine collaboration knowledge work
KW  - epistemic norms
KW  - digital transformation
        ER  -