在算法（AI）与直觉（人类）之间：在AI辅助的定性UX数据意义建构中保留设计师的能动性
Between Algorithm (AI) and Intuition (Human): Preserving Designer Agency in AI-Assisted Sensemaking of Qualitative UX Data
中文总结 AI 辅助
本文针对AI辅助定性UX数据意义建构中保留设计师能动性的问题，通过案例对比提出将AI作为放大人类判断工具的增强意义建构框架，为AI在设计研究中的应用提供了新方向。
中文摘要 AI 辅助
将AI整合到定性设计研究中存在一个根本矛盾：如何在利用AI的同时保留构成设计专业核心的主观、直觉判断？本文通过分析20份教育场景下视频会议平台的用户反馈案例来探讨这一问题。我们认为，AI意义建构工具可能会弱化丰富的数据模式，将用户反馈的矛盾性转化为枯燥的分类，从而将设计研究从一种解释性工艺转变为机械的分类工作（僵化且形式化）。通过对同一数据集的AI辅助意义建构与以人为中心的方法进行比较分析，我们明确了算法效率何时能增强理解、何时会削弱设计师的解释能动性（包括挖掘潜在需求、批判性探究、“如果”探究、决策、权衡取舍）。我们提出了一种增强意义建构的框架，将AI定位为放大人类判断的工具而非替代品。研究结果表明，AI在设计研究中最有价值的作用并非消除主观性，而是使其更具目的性、反思性和可问责性。
英文摘要
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.
