人工智能生成的播客为使科学可访问打开了新的大门:混合方法评估科学传播的质量和潜力
Chloé P Desmedt1,2, Werner Budts2,3, Maarten De Vos4,5
1KU Leuven Department of Public Health and Primary Care, KU Leuven - University of Leuven, Kapucijnenvoer 7, PB7001, Leuven B-3000, Belgium.
European journal of cardiovascular nursing
|June 14, 2025
概括
生成型人工智能 (GenAI) 可以快速创建科学播客,但需要解决不准确性等质量和可信度问题. 人工智能播客显示出科学传播的潜力,如果严格评估和透明地呈现.
科学领域:
- 心血管护理心血管护理
- 医学教育 医学教育
- 科学传播科学传播
背景情况:
- 科学播客对医学教育和传播科学信息有价值.
- 生成型人工智能 (GenAI) 工具可以快速创建播客,但可能会带来诸如内容幻觉等挑战.
- 确保人工智能产生的内容的可靠性对于有效的科学传播至关重要.
研究的目的:
- 探索人工智能生成的科学传播播客的质量和潜力.
- 评估参与者对人工智能生成的播客的看法,而无需事先了解其来源.
主要方法:
- 基于欧洲心血管护理杂志文章的10个人工智能生成的播客的混合方法评估.
- 通过问卷和视频采访对参与者进行评估,参与者对人工智能一代不知情.
- 对不同受众的可信度,准确性和适合性的分析.
主要成果:
- 参与者发现人工智能播客在简单地总结关键发现方面是有效的,但指出了可信度问题 (例如",美国风格"),不准确性和错误发音.
- 只有一半的参与者认为播客是人工智能生成的.
- 播客被认为最适合患者和公众,如果量身定制,对专业人士有潜在的实用性.
结论:
- 人工智能生成的播客可以作为科学出版物有价值的补充和传统科学播客的替代品.
- 建议包括严格的评估,关于人工智能生成的透明度,以及对原始文章的适当引用.
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