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将社交媒体用作数字表型分析所用人工智能模型训练数据的伦理问题。

Ethics of the Use of Social Media as Training Data for AI Models Used for Digital Phenotyping.

作者信息

Jaiswal Aditi, Shah Aekta, Harjadi Christopher, Windgassen Erik, Washington Peter

机构信息

Department of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, HI, United States.

Salesforce, San Francisco, CA, United States.

出版信息

JMIR Form Res. 2024 Jul 17;8:e59794. doi: 10.2196/59794.

Abstract

Digital phenotyping, or personal sensing, is a field of research that seeks to quantify traits and characteristics of people using digital technologies, usually for health care purposes. In this commentary, we discuss emerging ethical issues regarding the use of social media as training data for artificial intelligence (AI) models used for digital phenotyping. In particular, we describe the ethical need for explicit consent from social media users, particularly in cases where sensitive information such as labels related to neurodiversity are scraped. We also advocate for the use of community-based participatory design principles when developing health care AI models using social media data.

摘要

数字表型分析,或个人感知,是一个研究领域,旨在利用数字技术量化人们的特征和特性,通常用于医疗保健目的。在这篇评论中,我们讨论了将社交媒体用作数字表型分析所使用的人工智能(AI)模型的训练数据时出现的新伦理问题。特别是,我们描述了获得社交媒体用户明确同意的伦理必要性,尤其是在诸如与神经多样性相关的标签等敏感信息被抓取的情况下。我们还主张在使用社交媒体数据开发医疗保健AI模型时采用基于社区的参与式设计原则。

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