用生成式AI做用户画像，81篇研究揭示了效率与风险并存的现状。
Creating and Evaluating Personas Using Generative AI: A Scoping Review of 81 Articles
- 分析81篇论文，梳理生成式AI在用户画像创建中的应用模式。
- 45%文章无评估，86%仅用GPT模型，存在自我循环评估风险。
- 建议制定规范指南，避免人为角色弱化和结果不可靠。
随着生成式AI（GenAI）在用户画像构建中日益广泛应用，理解其影响与局限对建立可靠实践至关重要。本综述分析了2022至2025年间81篇相关论文，探讨GenAI在画像创建、评估与应用中的使用情况。研究发现，61%的论文共享了资源（如画像、代码或数据集），具备较好可复现性；同时，对话式画像界面正逐步取代传统静态档案。然而，近半数（45%）论文未进行评估，且86%仅使用GPT类模型。部分研究存在循环性风险——同一GenAI模型既生成又评估结果。此外，研究显示GenAI可能削弱人类开发者在画像构建中的作用。为降低风险，本文提出可操作的负责任整合指南。
原文摘要 · Abstract (English)
As generative AI (GenAI) is increasingly applied in persona development to represent real users, understanding the implications and limitations of this technology is essential for establishing robust practices. This scoping review analyzes how 81 articles (2022-2025) use GenAI techniques for the creation, evaluation, and application of personas. The articles exhibited good level of reproducibility, with 61% of articles sharing resources (personas, code, or datasets). Furthermore, conversational persona interfaces are increasingly provided alongside traditional profiles. However, nearly half (45%) of the articles lack evaluation, and the majority (86%) use only GPT models. In some articles, GenAI use creates a risk of circularity, in which the same GenAI model both generates and evaluates outputs. Our findings also suggest that GenAI seems to reduce the role of human developers in the persona-creation process. To mitigate the associated risks, we propose actionable guidelines for the responsible integration of GenAI into persona development.
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