临床社会工作者对实践中的大型语言模型的看法:抵抗自动化和整合前景
Johanna Creswell Báez1, Eunhye Ahn2, Aubrey Tamietti1
1Social Work Department, University of Colorado, Colorado Springs, Colorado, USA.
Journal of evidence-based social work (2019)
|August 2, 2025
概括
临床社会工作者发现生成人工智能 (AI) 对行政任务有用,但对保密性和同情心感到担忧. 他们更喜欢人工智能增强而不是自动化,以保持客户的福祉和治疗深度.
科学领域:
- 临床社会工作 临床社会工作
- 医疗保健中的人工智能
- 人与计算机的交互
背景情况:
- 生成型人工智能 (AI),特别是大型语言模型 (LLM),越来越容易获得.
- 了解AI在临床实践中的整合对于社会工作至关重要.
- 临床社会工作者对人工智能工具的看法对于负责任的采用至关重要.
研究的目的:
- 探索临床社会工作者对临床实践中生成性AI (AI) 和大型语言模型 (LLM) 的看法.
- 确定影响LLM在社会工作中感知的有用性的因素.
- 了解社会工作者在客户互动中对人工智能的经验和担忧.
主要方法:
- 对21名临床社会工作者采访的定性反思性专题分析.
- 探索参与者与LLMs的经验,包括ChatGPT,在一个案例咨询练习.
- 使用ChatGPT.使用客户展示后的感知分析.
主要成果:
- 两个关键主题出现了:增强感知有用性的因素 (行政支持,客户参与) 和减少它的因素 (保密性,细微差别的丧失,同情的局限性).
- 实践者使用LLM作为创意生成器,但对信息质量和以人为中心的方法的需求表示担忧.
- 收养决定受职业道德和关系价值观的影响,偏爱增强而不是完全自动化.
结论:
- 负责任的人工智能实施需要从业人员培训和明确的伦理准则LLM集成.
- 持续评估是必要的,以确保人工智能工具在不损害治疗关系或社会工作价值观的情况下增强临床实践.
- 在将人工智能整合到社会工作中时,以以人为中心的方法至关重要,优先考虑客户的福祉和治疗深度.
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