人工智能在系统文献评论中:社会工作道德,应用和可行性
Robert Lucio1, Amy Harris2, Johanna Creswell Báez3
1College of Social Work, University of Tennessee, Knoxville.
Journal of evidence-based social work (2019)
|August 20, 2025
概括
生成型人工智能 (AI) 工具在研究中显示了主题分析的潜力,但需要人类专家对其准确性进行审查. 将人工智能与专家监督相结合的混合方法可以提高研究效率和方法.
科学领域:
- 医学研究方法
- 研究中的人工智能
- 社会工作研究
背景情况:
- 范围审查对于综合证据至关重要,但需要大量时间.
- 创造性人工智能有助于简化研究过程.
- 在管理阿片类药物使用障碍 (OUD) 方面,同行支持专家起着至关重要的作用.
研究的目的:
- 将人工智能工具的专题发现与手动范围审查结果进行比较.
- 评估生成性人工智能在医学研究中识别主题的有效性.
- 评估人工智能在简化耗时的研究过程中的作用.
主要方法:
- 对OUD的同行支持专家进行了人为驱动的范围审查.
- 专题发现与人工智能工具 (NotebookLM,UTVERSE,Gemini) 的结果进行了比较.
- 人工智能工具只能从上传的15篇同行评审文章中识别主题.
主要成果:
- 人工智能模型从手动分析中确定了53%至80%的主题.
- 人工智能工具发现了新的主题,
- 在主题分析的生成人工智能性能中存在显著的变化.
结论:
- 人类专家审查对于验证人工智能生成的主题的准确性和相关性至关重要.
- 将人工智能与专家审查相结合的混合方法可以增强研究方法.
- 建立人类-人工智能合作的最佳实践对于社会工作研究至关重要.
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