Post-AGI Economies: Autonomy and the First Fundamental Theorem of Welfare Economics
For economists and AI ethicists, this work provides a theoretical framework to evaluate welfare in economies with autonomous AI agents, though it is largely conceptual and incremental.
The paper extends the First Fundamental Theorem of Welfare Economics to post-AGI economies by incorporating varying degrees of autonomy in artificial systems, showing that an autonomy-complete competitive equilibrium is autonomy-Pareto efficient, with the classical theorem recovered as a low-autonomy limit.
The First Fundamental Theorem of Welfare Economics assumes that welfare-bearing agents are autonomous and implicitly relies on a binary distinction between autonomy and instrumentality. Welfare subjects are those who have autonomy and therefore the capacity to choose and enter into utility comparisons, while everything else does not. In post-AGI economies this presupposition becomes nontrivial because artificial systems may exhibit varying degrees of autonomy, functioning as tools, delegates, strategic market actors, manipulators of choice environments, or possible welfare subjects. We argue that the theorem ought to be subject to an autonomy qualification where the impact of these changes in autonomy assumptions is incorporated. Using a minimal general-equilibrium model with autonomy-conditioned welfare, welfare-status assignment, delegation accounting, and verification institutions, we set out conditions for which autonomy-complete competitive equilibrium is autonomy-Pareto efficient. The classical theorem is recovered as the low-autonomy limit.