Fleming Megan N
Department of Psychological Sciences, University of Missouri - Columbia.
Ethics Behav. 2021;31(3):181-192. doi: 10.1080/10508422.2020.1817026. Epub 2020 Sep 9.
The ubiquity of social media usage has led to exciting new technologies such as machine learning. Machine learning is poised to change many fields of health, including psychology. The wealth of information provided by each social media user in combination with machine learning technologies may pave the way for automated psychological assessment and diagnosis. Assessment of individuals' social media profiles using machine learning technologies for diagnosis and screening confers many benefits (i.e., time and cost efficiency, reduced recall bias, information about an individual's emotions and functioning spanning months or years, etc.); however the implementation of these technologies will pose unique challenges to the professional ethics of psychology. Namely, psychologists must understand the impact of these assessment technologies on privacy and confidentiality, informed consent, recordkeeping, bases for assessments, and diversity and justice. This paper offers a brief review of the current applications of machine learning technologies in psychology and public health, provides an overview of potential implementations in clinical settings, and introduces ethical considerations for professional psychologists. This paper presents considerations which may aid in the extension of the current Ethical Principles of Psychologists and Code of Conduct to address these important technological advancements in the field of clinical psychology.
社交媒体使用的普遍性催生了机器学习等令人兴奋的新技术。机器学习有望改变包括心理学在内的许多健康领域。每个社交媒体用户提供的大量信息与机器学习技术相结合，可能为自动化心理评估和诊断铺平道路。利用机器学习技术评估个人的社交媒体资料以进行诊断和筛查有诸多益处（如时间和成本效率、减少回忆偏差、获取有关个人数月或数年的情绪和功能的信息等）；然而，这些技术的实施将给心理学的职业道德带来独特挑战。具体而言，心理学家必须了解这些评估技术对隐私和保密、知情同意、记录保存、评估依据以及多样性和公正性的影响。本文简要回顾了机器学习技术在心理学和公共卫生领域的当前应用，概述了在临床环境中的潜在应用，并介绍了专业心理学家的伦理考量。本文提出了一些考量因素，可能有助于扩展当前的《心理学家伦理原则与行为准则》，以应对临床心理学领域的这些重要技术进步。
