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arXiv · 2609.30388

The Interviewer's Perspective: Unpacking the Impact of Real-Time AI Interviewing Assistance on Social Dynamics

Zhe Liu·Jiamin Dai·Joanna McGrenere
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Abstract

Eliciting rich data in semi-structured interviews is cognitively demanding, prompting recent work to explore real-time AI assistance for interviewers. However, introducing AI into the interviewer-interviewee interaction creates a triadic context whose social dynamics remain underexplored. We investigated how interviewers experience AI assistance for probing during semi-structured interviews. To elicit rich participant reflections, we implemented two variants of AI assistance differing in initiation and granularity in a high-fidelity prototype, ProbeAssist. We conducted a qualitative-first comparative structured observation study where 18 participants each completed three simulated interviews: one without AI and two with different AI variants. Findings showed that participants leveraged AI as a supportive tool but resisted it as an assessor or competitor. As they navigated AI's benefits and interaction costs, tensions emerged around agency, ownership, creativity, and interpersonal communication. We propose three implications for AI-assisted human-to-human interaction: managing social pressure, balancing idea alignment with inspiration, and preserving interpersonal presence.

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Zhe Liu, Jiamin Dai, Joanna McGrenere. 2026-09-24. The Interviewer's Perspective: Unpacking the Impact of Real-Time AI Interviewing Assistance on Social Dynamics. https://arxiv.org/abs/2609.30388

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