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The Impact of Generative Artificial Intelligence on Market Equilibrium: Evidence from a Natural Experiment

Authors :
Zhang, Kaichen
Yuan, Zixuan
Xiong, Hui
Publication Year :
2023

Abstract

Generative artificial intelligence (AI) exhibits the capability to generate creative content akin to human output with greater efficiency and reduced costs. This groundbreaking capability, however, has ignited a debate regarding its potential to displace human creators. In light of these discussions, this paper empirically investigates the impact of generative AI on market equilibrium, in the context of China's leading art outsourcing platform. We overcome the challenge of causal inference by identifying an unanticipated and sudden leak of an advanced image-generative AI as a natural experiment. This leak precipitated a notable reduction in the production costs of anime-style images compared to other genres, thereby providing a unique opportunity for difference-in-differences comparisons. Our analysis shows that the advent of generative AI led to a 64% reduction in average prices, yet it simultaneously spurred a 121% increase in order volume and a 56% increase in overall revenue. This growth is primarily driven by the rising demand for "low-end" personal orders, rather than commercial orders. Moreover, incumbent creators retain the majority of the market share and reap the most benefits of generative AI. Our research highlights the potential of generative AI to benefit all stakeholders across the platform economy, yielding both scholarly contributions and practical implications.<br />Comment: Accepted by WINE 2024 - The 20th Conference on Web and Internet Economics

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2311.07071
Document Type :
Working Paper