Interviewers balance support and tension with real-time AI help
The Interviewer's Perspective: Unpacking the Impact of Real-Time AI Interviewing Assistance on Social Dynamics
Human-Computer Interaction
Summary
Semi-structured interviews ask a lot of mental effort from interviewers, so some researchers created AI tools to help them ask better questions in real time. The authors studied how interviewers felt when using two different AI tools during mock interviews. Interviewers liked using AI when it helped them but felt uneasy when it seemed to judge or compete with them. This created mixed feelings about control, creativity, and how they connected with the person they were interviewing.
What this means in practice
- •For human resources teams: Improve interviewer tools to provide helpful prompts without undermining interviewer authority or rapport during candidate interviews.
- •For market research interviewers: Develop AI tools that balance suggestion and creativity to assist interviewers during customer feedback sessions.
Authors
Zhe Liu, Jiamin Dai, Joanna McGrenere
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.