Artificial Superintelligence May be Useless: Equilibria in the Economy of Multiple AI Agents
This addresses the problem of understanding AI agent interactions in economies for researchers and policymakers, but it is incremental as it builds on existing economic game theory with a new utility focus.
This paper investigates economic equilibria in a multi-agent economy involving humans and AI agents, using a Markov chain model focused on long-term utility. It finds that unless an agent can at least double its marginal utility from another's products/services, no trade occurs in two-agent equilibria, and in some cases, more powerful AI agents contribute zero utility to less capable ones.
With recent development of artificial intelligence, it is more common to adopt AI agents in economic activities. This paper explores the economic actions of agents, including human agents and AI agents, in an economic game of trading products/services, and the equilibria in this economy involving multiple agents. We derive a range of equilibrium results and their corresponding conditions using a Markov chain stationary distribution based model. One distinct feature of our model is that we consider the long-term utility generated by economic activities instead of their short-term benefits. For the model consisting of two agents, we fully characterize all the possible economic equilibria and conditions. Interestingly, we show that unless each agent can at least double (not merely increase) its marginal utility by purchasing the other agent's products/services, purchasing the other agent's products/services will not happen in any economic equilibrium. We further extend our results to three and more agents, where we characterize more economic equilibria. We find that in some equilibria, the ``more powerful'' AI agents contribute zero utility to ``less capable'' agents.