心理健康应用中的黑子算法:一个伦理反思
Tania Manríquez Roa1,2, Nikola Biller-Andorno1,2
1Institute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland.
Bioethics
|July 28, 2023
概括
心理健康应用中的黑子算法为分析提供了好处,但在提供建议时存在风险. 了解它们的功能对于在医疗保健和研究中安全有效地使用它们至关重要.
科学领域:
- 数字心理健康数字心理健康
- 医疗信息学 医疗信息学
- 算法透明度 算法的透明度
背景情况:
- 心理健康应用程序提供了显著的好处,但也有风险.
- 对这些应用程序的评估往往忽略了它们的底层算法和功能.
- 这些应用程序中常见的黑子算法,由于其不透明性,存在独特的挑战.
研究的目的:
- 探索心理健康应用中的黑子算法的不透明性.
- 讨论这种不透明对用户和医疗保健的影响.
- 提出指导方针,用于利用这些算法的结果在心理健康护理,自我护理和研究.
主要方法:
- 专注于使用黑子算法的心理健康应用程序.
- 对算法函数的分析,特别是区分分析和建议生成.
- 探索算法不透明性的影响.
主要成果:
- 黑子算法擅长分析功能,有助于早期复发检测,诊断和研究见解.
- 在生成建议时,黑子算法可能会产生有害的,意想不到的建议.
- 从分析函数的结果可以信任作为补充信息.
结论:
- 在心理健康应用程序中的算法分析和咨询功能之间存在关键区别.
- 建议对直接向用户提供建议的黑子算法保持谨慎.
- 确定算法是否提供建议对于减轻风险和最大化心理健康应用程序的好处至关重要.
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