The Diminishing Returns to Human Recruiting in Online Labor Markets

Firms spend hundreds of billions of dollars annually on outside recruiting help, yet it is unclear whether human intermediaries add value when employers already have access to algorithmic screening tools. We study a randomized experiment in a large online labor market that assigned human recruiting assistance to job postings. Treated employers received 16% more applications and conducted 35% more interviews but were no more likely to hire than control employers with access only to algorithmic tools. Match quality declined: treated employers spent less on hires and their workers completed fewer hours. We develop a model of delegated recruiting in which recruiters and employers rely on a common noisy signal, which can generate these patterns when their assessments are highly correlated. Consistent with this mechanism, recruited applicants are positively selected on engagement-related characteristics yet do not improve hiring outcomes. These findings suggest that as algorithmic screening improves, the scope for intermediaries to add value shrinks because it becomes harder to access independent information.