Agency-Driven Labor Theory of Human Value Creation in AI-Augmented Work
A theoretical framework in labor economics arguing that as AI performs more cognitive tasks, human labor value shifts away from task execution toward agency: the capacity to make informed judgments, set strategic direction, and design operational frameworks for AI systems. It formalizes labor value as a function of agency quality, direction effectiveness, and outcomes (LV = f(A, D, O)), and draws out consequences for job design, compensation, professional development, and labor-market dynamics. A student learns a way to reconceptualize and quantify human contribution in workplaces where humans orchestrate combined human-AI systems.
Agency-Driven Labor Theory: A Framework for Understanding Human Work in the AI Age Venkat Ram Reddy
This paper introduces Agency-Driven Labor Theory (ADLT), a theoretical framework for understanding human work in AI-augmented environments. Where traditional labor theories - from Smith's division of…