Max – A Thought Experiment: Could AI Run the Economy Better Than Markets?
48 Pages Posted: 4 Dec 2019 Last revised: 27 Feb 2020
Date Written: February 10, 2020
One of the fundamental critiques against 20th-century experiments in central economic planning, and the main reason for their failure, was the inability of human-directed planning systems to manage the data gathering, analysis, computation, and control necessary to direct the vast complexity of production, allocation, and exchange decisions that make up a modern economy. Rapid recent advances in AI, data, and related technological capabilities have re-opened that old question and provoked vigorous speculation about the feasibility, benefits, and threats of an AI-directed economy.
This paper presents a thought experiment about how this might work, based on assuming a powerful AI agent (whimsically named “Max”) with no binding computational or algorithmic limits on its (his) ability to do this. The paper’s novel contribution is to reason concretely through how such a system might work under explicit background conditions, what benefits it might offer relative to present market and mixed-market arrangements, what novel requirements or constraints it would present, what threats and challenges it would pose, and how it might inflect understanding of long-standing foundational questions about state, society, and human liberty.
As with smaller-scale regulatory interventions, the concrete implementation of comprehensive central planning can be abstracted as intervening via quantities or prices. The paper argues that quantity-based approaches would be fundamentally impaired by agency and incentive problems that would persist under arbitrary computational advances, while price-based approaches (as proposed by Lange) present no such fundamental disabilities. More promising than either, however, would be a variant in which Max manages a comprehensive system of price modifications added to emergent market outcomes, equivalent to a comprehensive economy-wide system of Pigovian taxes and subsidies. Such a system, “Pigovian Max,” could in principle realize the information efficiency benefits and liberty interests of decentralized market outcomes, while also comprehensively correcting externalities, suppressing tendencies to inefficient concentration of market power and associated rent-seeking behavior – and also, under additional assumptions, offer the prospect of taxation without deadweight losses by taking all taxes from inframarginal rents.
Having outlined the basic approach and these potential benefits, the paper discusses several challenges and potential risks presented by such a system. These include Max’s need for data and the potential costs of providing it; the granularity or aggregation of Max’s determinations; the problem of maintaining variety and innovation in an economy directed by Max; the implications of Max for the welfare of human workers, the meaning and extent of property rights, and associated liberty interests; the definition of social welfare that determines Max’s objective function, its compatibility with democratic control, and the resultant stability of the boundary between the state and the economy; and finally, the relationship of Max to AI-enabled trends already observable and implications for the strategic and political feasibility of something like Max appearing, along with the associated risks. In view of the depth and difficulty of these questions, the discussion of each is highly preliminary and tentative.
Keywords: artificial intelligence, economic planning, socialist calculation
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