Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews
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摘要
This paper reports a large natural field experiment (70,884 applications) showing that AI voice agents interviewing applicants can reduce variance in information collection and improve hiring outcomes: offers rise by 12% (9.73% vs 8.70%), job starts rise by 18%, and one-month retention rises by 18%, with no observed decline in the productivity of hired workers [page::2][page::15][page::18]. The mechanism—controlled variance—stems from AI enforcing structured interviews while remaining responsive to applicants, yielding richer, more comparable hiring-relevant information [page::3][page::4]. Transcript analyses show that AI-led interviews standardize topic coverage and guideline adherence, and correlate with linguistic features linked to higher offer probabilities [page::3][page::20]. Applicants generally respond well to AI interviewing, with most in the Choice condition preferring AI, though some backlashes (e.g., AI aversion, technical failures) exist; cost analyses indicate AI becomes cost-effective in higher-wage or high-volume settings under favorable pricing, though break-even depends on price tiers and wage environments [page::28][page::38][page::103]. Overall, AI can improve screening efficiency in high-volume, routine tasks, while human evaluators continue to play a role in signal weighting and complex assessments [page::40].
