Speech production under uncertainty: how do job applicants experience and communicate with an AI interviewer?

Abstract Theories and research in human–machine communication (HMC) suggest that machines, when replacing humans as partners, change the processes outcomes of communication. With artificial intelligence (AI) increasingly used to interview evaluate job applicants, employers should consider effects AI on applicants’ psychology performance during AI-based interviews. This study examined experience speech fluency evaluated by AI. In a three-condition between-subjects experiment (N = 134), college students had an online mock under impression their would be human recruiter, system, or system with humanlike interface. Participants reported higher uncertainty lower social presence articulation rate AI-evaluation condition than human-evaluation condition. Through lowering presence, evaluation increased reduced silent pauses. Findings inform theories HMC practices automated recruitment professional training.