大型语言模型能解决博问题吗? 博治疗专业人员的专家见解
Kasra Ghaharian1, Marta Soligo2, Richard Young3
1International Gaming Institute, University of Nevada, Las Vegas, USA. kasra.ghaharian@unlv.edu.
Journal of gambling studies
|October 10, 2025
概括
专家们发现,大型语言模型 (LLM) 对博问题提供了不同的见解. 虽然Llama 3.1比GPT-4o略有优势,但这两种模型在提供安全和准确的博危害干预建议方面都表现出弱点.
科学领域:
- 人工智能的人工智能
- 行为科学 行为科学
- 公共卫生 公共卫生
背景情况:
- 大型语言模型 (LLM) 越来越多地用于信息检索,包括心理健康和成等敏感主题.
- 将LLM应用到问题博咨询中,由于潜在的风险,需要仔细评估.
研究的目的:
- 调查大型语言模型 (LLM) 如何响应有关问题博的提示.
- 评估专家对LLM产生的内容的解释,以评估博危害干预.
主要方法:
- 基于问题博严重性指数的9个提示被提交给GPT-4o和Llama 3.1.
- 23名经验丰富的博治疗专业人员通过在线调查评估了回复.
- 对专家反和首选的LLM响应选择进行了定性分析.
主要成果:
- 拉玛3.1在GPT-4o上获得了轻微的优势,在9次即时评估中获得了7次.
- 专家们确定了LLM响应的优点和弱点,包括可能鼓励博和误解语言.
- 人们对过于详细的信息和安全护表示担忧.
结论:
- 对问题博提示的LLM响应需要由人类专家进行仔细审查.
- 未来开发用于博伤害干预的LLM必须包含强有力的安全标准和专家知情的护.
- 需要进一步的研究来完善LLM输出,以提供敏感的与健康有关的建议.
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