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大型语言模型人工智能与人类生成的辅导信息进行比较,用于行为减肥.
Zhuoran Huang1, Michael P Berry2, Christina Chwyl3
1Khoury College of Computer Sciences, Northeastern University, 440 Huntington Ave, Boston, MA 02115 USA.
Journal of technology in behavioral science
|January 22, 2026
概括
大型语言模型 (LLM) 人工智能聊天机器人显示为个性化体重控制教练的承诺. 在修订后,人工智能消息与人类教练相匹配,并且经常被误认为是人类撰写的内容.
科学领域:
- 行为科学 行为科学
- 人工智能的人工智能
- 卫生教练健康教练
背景情况:
- 自动化体重控制辅导信息可能会比人类辅导更重复和不那么有效.
- 大型语言模型 (LLM) 人工智能聊天机器人为个性化和新的辅导信息提供了潜力.
- 基于LLM的体重管理指导的可行性和可接受性仍未得到充分研究.
研究的目的:
- 评估LLM AI (ChatGPT) 的可行性和可接受性,以生成体重控制辅导信息.
- 为了比较人类编写的辅导信息与人工智能生成的辅导信息的有用性.
- 在减肥试验中探索用户对人工智能生成消息的看法.
主要方法:
- 87名BMI≥27kg/m2的成年人参加了一项减肥试验.
- 参与者在5分利克特级别上评价了人写和ChatGPT生成的辅导信息的有用性.
- 质量反和人工智能信息识别在两个阶段收集,并进行信息修订.
主要成果:
- 最初的AI消息被评为不那么有帮助,但修订后的AI消息与人类消息相匹配 (82%的评分≥3).
- 50%的AI信息被误认为是人类写的,这表明复杂的模仿.
- 参与者发现人工智能信息具有同情心和个性化,但有时是公式和数据重点.
结论:
- LLM AI 显示了创建有效的体重控制辅导信息的初步可行性.
- 人工智能生成的信息可以被认为是有帮助和个性化的,在改进后与人类撰写的内容竞争.
- 需要进一步改进,以解决人工智能指导的感知形式和数据中心方面的问题.
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