# Interview AI-ssistant: Designing for Real-Time Human-AI Collaboration in Interview Preparation and Execution

arXiv: https://arxiv.org/abs/2504.13847 · HTML: https://mlsanity.com/paper/2504.13847/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 29 references that are in the map.
- First posted on arXiv 3 Mar 2025.

## Builds on (most cited first, 5 of 5)

- [Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding](https://mlsanity.com/paper/2304.10548/) (2023)
- [Ask Not What AI Can Do, But What AI Should Do: Towards a Framework of Task Delegability](https://mlsanity.com/paper/1902.03245/) (2019)
- [If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills](https://mlsanity.com/paper/2002.01862/) (2020)
- [Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys with Open-ended Questions](https://mlsanity.com/paper/1905.10700/) (2019)
- [Supporting Serendipity: Opportunities and Challenges for Human-AI Collaboration in Qualitative Analysis](https://mlsanity.com/paper/2102.03702/) (2021)

## Built on by (most cited first, 2 of 2)

- [Designing AI-Supported Focus Groups: A Role x Modality Playbook](https://mlsanity.com/paper/2606.11835/) (2026)
- [AI-assisted Script Management for Requirements Elicitation Interviews](https://mlsanity.com/paper/2608.01640/) (2026)

## Abstract (arXiv)

Recent advances in large language models (LLMs) offer unprecedented opportunities to enhance human-AI collaboration in qualitative research methods, including interviews. While interviews are highly valued for gathering deep, contextualized insights, interviewers often face significant cognitive challenges, such as real-time information processing, question adaptation, and rapport maintenance. My doctoral research introduces Interview AI-ssistant, a system designed for real-time interviewer-AI collaboration during both the preparation and execution phases. Through four interconnected studies, this research investigates the design of effective human-AI collaboration in interviewing contexts, beginning with a formative study of interviewers' needs, followed by a prototype development study focused on AI-assisted interview preparation, an experimental evaluation of real-time AI assistance during interviews, and a field study deploying the system in a real-world research setting. Beyond informing practical implementations of intelligent interview support systems, this work contributes to the Intelligent User Interfaces (IUI) community by advancing the understanding of human-AI collaborative interfaces in complex social tasks and establishing design guidelines for AI-enhanced qualitative research tools.