人与机器人交流中的沟通错误:一个关于ChatGPT阿拉伯语心理健康支持查询的案例研究
Ghuzayyil Mohammed Al-Otaibi1, Hind M Alotaibi1, Sami Sulaiman Alsalmi1
1Department of English, College of Language Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia.
Behavioral sciences (Basel, Switzerland)
|August 28, 2025
概括
这项研究分析了与ChatGPT-3.5互动的阿拉伯语沟通错误,发现大部分是语法错误和重复. 这些见解突显了对话性人工智能在心理健康支持等敏感领域的挑战.
科学领域:
- 自然语言处理
- 人工智能道德
- 人与计算机的交互
背景情况:
- 大型语言模型 (LLM) 越来越普遍,但它们的有效使用需要进一步探索.
- 了解沟通细微差别对于在心理健康等敏感领域部署人工智能至关重要.
研究的目的:
- 在阿拉伯语中识别和分类人类-ChatGPT-3.5交互中的通信错误.
- 分析错误的类型,包括语法,重复,矛盾,模糊性和缺乏社交性.
- 提供关于当前对话性AI在心理健康支持环境中的局限性的见解.
主要方法:
- 我从一个网络论坛收集了六个阿拉伯语的心理健康咨询.
- 从咨询中提交的用户查询到ChatGPT-3.5
- 分析了ChatGPT-3.5对通信错误的反应.
主要成果:
- 在ChatGPT-3.5的阿拉伯回复中发现了102个不同的通信错误.
- 大多数错误是语法和重复的.
- 其他重大错误包括矛盾,模两可的语言,被忽视的问题和缺乏社交性.
结论:
- 像ChatGPT-3.5这样的当前交谈人工智能系统在阿拉伯语中表现出明显的沟通错误.
- 这些错误, 特别是在心理健康等敏感领域, 表明人工智能在准确和同情地传达信息的能力受限.
- 需要进一步的研究来改善专业应用的LLM沟通.
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