Labor Market Signals: The Role of Large Language Models

Abstract

Large Language Models (LLMs) are transforming the labor market, including hiring. This paper assesses their impact on signals that job-seekers send to potential employers and how this affects labor market matching. Through two field experiments, focusing on cover letters and involving job-seekers and recruiters, we document that LLMs enhance the quality of signals, particularly benefiting lower-quality applicants. However, these improvements do not translate into increased interview invitations because the improvements are concentrated in standardized, less influential sections of the cover letters. When recruiters are explicitly informed of candidates’ use of LLMs, they place greater value on high-quality cover letters crafted without AI assistance. Our findings indicate that LLMs reduce the informativeness of signals, potentially leading to increased inefficiencies in labor market matching.