Beyond the Prompt: The Social Costs of Generative Artificial Intelligence

The rapid commercialization of generative artificial intelligence has produced extraordinary value for technology companies while systematically externalizing costs onto society. Co-authored with J. Scott Christianson, this article provides a review of these externalities across three domains: environmental, human health, and digital infrastructure. The environmental burden includes massive energy and water consumption alongside ecologically destructive mining for rare earth elements and accelerating electronic waste.

The human toll encompasses a documented pattern of AI-induced mental health crises, including suicide and self-harm linked to anthropomorphic chatbot design, raising novel questions of product liability. The digital commons face degradation through industrialized data scraping that has effectively stripped platforms of their primary legal defenses. Our argument is straightforward: the AI industry’s business model is predicated on a fundamental market failure—the privatization of benefit and socialization of cost.

Read the full paper published in the Business, Entrepreneurship & Tax Law Review (Vol. 10, Iss. 1, 2026).