[在定性研究中使用人工智能的潜力和风险]
Christian Kempny1, Yüce Yilmaz-Aslan2, Patrick Brzoska1
1Universität Witten/Herdecke, Lehrstuhl für Versorgungsforschung, Witten, Deutschland.
Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen
|November 15, 2025
概括
人工智能 (AI) 为定性研究提供了补充工具,有助于反思和产生新的视角. 然而,人工智能不能自动化核心定性原则,需要对其使用采取批判性和严格的方法.
科学领域:
- 社会科学 社会科学 社会科学
- 计算机科学 计算机科学
- 研究方法研究方法研究方法学
背景情况:
- 强大的大型语言模型 (LLM) 的兴起正在增加对定性研究中的人工智能 (AI) 应用的兴趣.
- 现有的研究和实践经验强调了将AI整合到定性工作流中的潜在好处和重大挑战.
研究的目的:
- 在关键的定性研究过程中批判性地检查人工智能的潜力和局限性,特别是LLMs.
- 讨论在定性研究中与人工智能相关的功能优势以及方法,伦理和数据保护方面的问题.
主要方法:
- 对AI能力在类别开发,编码和解释方面的批判性检查.
- 综合来自作者经验和相关学术研究的见解.
- 分析人工智能的作用,作为一个补充工具,而不是一个自动化解决方案.
主要成果:
- 基于人工智能的系统可以作为有价值的辅助工具,为定性研究人员提供替代观点,并充当"第二意见".
- 存在重大挑战,包括必须解决的方法严谨性,伦理考虑和数据保护问题.
- 定性研究的基本原则,如深度解释和上下文理解,仍然超出了当前人工智能自动化的范围.
结论:
- 人工智能可以提高定性研究,当它被用作反思的帮助,但不是作为替代人类判断.
- 建议以研究为导向,批判性地反思人工智能的应用,强调方法论的健全性和道德责任.
- 持续的学术对话对于在定性研究中导航AI不断变化的景观至关重要.
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