Abstract
The use of Large Language Models (LLM) could have a profound impact on the labor market. There is already extensive research on the impact of AI automation on existing jobs, but little is known about the use of LLMs and AI tools on the selection process leading to new hires. For entry level positions, applicants are usually required to submit a CV and a cover letter in order to send a signal to the new employer about their skills. Writing a good cover letter that impresses an employer requires time and effort, and was traditionally interpreted as an effective way to send a signal about applicants’ relevant skills and motivation for the job. However, with the emergence of LLMs, writing a good quality cover letter has become much easier, and hence cover letters are a less reliable signal of an applicant’s quality. This is further confounded by the insights from the academic literature on the productivity effects of LLMs, which find that LLMs help everyone, however help the low-performers disproportionately more (Noy and Zhang, 2023; Dell’Acqua et al., 2023). Therefore, the difference in quality of cover letters between good and less good applicants is likely to decrease as a result of the use of LLMs – making cover letters a less reliable signal of the applicant’s quality.