Braess's Paradox of Generative AI

TL;DR

This paper explores the complex social and economic impacts of Generative AI, revealing potential drawbacks like reduced platform engagement and proposing regulatory conditions for societal benefit.

Contribution

It introduces a novel analysis of GenAI's revenue optimization, social impact, and regulatory conditions, highlighting a Braess's paradox-like effect in AI adoption.

Findings

GenAI's optimal revenue strategy has a non-cyclic structure.

GenAI can be socially harmful, akin to Braess's paradox.

Conditions for regulators to ensure GenAI's social benefits.

Abstract

ChatGPT has established Generative AI (GenAI) as a significant technological advancement. However, GenAI's intricate relationship with competing platforms and its downstream impact on users remains under-explored. This paper initiates the study of GenAI's long-term social impact resulting from the weakening network effect of human-based platforms like Stack Overflow. First, we study GenAI's revenue-maximization optimization problem. We develop an approximately optimal solution and show that the optimal solution has a non-cyclic structure. Then, we analyze the social impact, showing that GenAI could be socially harmful. Specifically, we present an analog to Braess's paradox in which all users would be better off without GenAI. Finally, we develop necessary and sufficient conditions for a regulator with incomplete information to ensure that GenAI is socially beneficial.