https://macropaperwarehouse.com/authors/nils-h.-lehr/Nils H. LehrHugo -- gohugo.ioen-ushttps://macropaperwarehouse.com/papers/the-price-of-intelligence-how-should-socially-minded-firms-price-and-deploy-ai/https://macropaperwarehouse.com/papers/the-price-of-intelligence-how-should-socially-minded-firms-price-and-deploy-ai/<p>Leading AI firms such as OpenAI and Anthropic publicly claim dual mandates of profit and social welfare, raising the question of whether—and how—a social mandate should change their pricing and deployment decisions. This paper provides a framework to answer this question, deriving a Modified Lerner Rule for socially minded AI firms that extends the standard profit-maximizing Lerner Rule to incorporate incentives for aggregate efficiency, distributional concerns, and labor market stability. Using U.S. data on 525 detailed occupations, the paper evaluates optimal pricing and deployment paths for an AI capable of replacing human labor in each job at 50% of the cost. The main finding is that a welfarist firm (one that values profits and social welfare) should price closer to marginal cost because, for the jobs considered, efficiency gains outweigh distributional concerns—AI does not primarily displace low-income workers. A conservative firm focused on labor market stability should price above the profit-maximizing level in the short run, but not in the long run. The paper concludes that the most pro-social course of action for AI firms with market power is to refrain from exercising that power, and that proposals to tax AI to protect labor markets miss the counteracting role of market power.</p>