Between Algorithm (AI) and Intuition (Human): Preserving Designer Agency in AI-Assisted Sensemaking of Qualitative UX Data
Human-Computer InteractionEmerging Technologies
Summary
The authors studied how AI tools affect qualitative design research, especially when analyzing user opinions about video conferencing for education. They found that AI can sometimes oversimplify complex, nuanced feedback into rigid categories, which may reduce designers' ability to interpret and understand subtle user needs. By comparing AI-assisted and human-driven analysis, the authors show that AI works best when used to support, not replace, human judgment. They propose a way to use AI to enhance thoughtful decision-making rather than taking over the creative aspects of design research.
Authors
Md Haseen Akhtar
Abstract
The integration of AI into qualitative design research presents a fundamental tension: how do we leverage AI while preserving the subjective, intuitive judgments that define design expertise? This paper examines this question through a case study of analyzing 20 user responses about video conferencing platforms for educational contexts. We argue that AI sensemaking tools risk flattening the rich data patterns, amplifying contradictory textures of user feedback into sterile categories thereby transforming design research from an interpretive craft into a mechanical sorting exercise (rigid and formal). Through comparative analysis of AI-assisted sensemaking versus human-centered approaches to the same dataset, we identify when algorithmic efficiency enhances understanding and when it diminishes the designer's interpretive agency (uncovering hidden needs, critical enquiry, what if enquiries, making decisions, having trade-offs). We present a framework for augmented sensemaking that positions AI as an instrument for amplifying human judgment rather than replacing it. Our findings suggest that the most valuable role for AI in design research is not to eliminate subjectivity, but to make it more intentional, reflective, and accountable.