视觉数字数据,道德挑战和心理学科学
Mark Levine1, Richard Philpot1, Sophie J Nightingale1
1Department of Psychology, Lancaster University.
The American psychologist
|January 18, 2024
概括
心理学家可以使用数字视觉数据进行研究,但必须应对重大的伦理挑战. 隐私和数据保护影响评估为负责任的数据处理提供了一个实际的解决方案.
科学领域:
- 心理学 心理学 心理学
- 数字伦理数字伦理
- 数据科学数据科学数据科学
背景情况:
- 数字视觉数据为心理学中的实时行为分析提供了前所未有的机会.
- 视觉数据中面部和个人识别信息的固有敏感性存在重大伦理风险.
- 自动数据收集和处理放大了与数字视觉数据相关的敏感性和伦理挑战.
研究的目的:
- 探索心理学家在利用数字视觉数据进行研究时所面临的伦理挑战.
- 讨论整个数据生命周期的伦理考虑:获取,分析,存储和共享.
- 为解决这些复杂的伦理问题提供一个实际的框架.
主要方法:
- 探索从公共安全系统和社交媒体获取视觉数据的伦理挑战.
- 分析与自动数据处理相关的风险,包括偏见和歧视.
- 检查安全数据存储,功能爬行和数据撤回权的伦理要求.
主要成果:
- 在数据采集,处理 (偏见,歧视),存储和共享方面确定了重大伦理风险.
- 突出了数据敏感性和开放科学运动对透明度的强调之间的紧张关系.
- 提出隐私和数据保护影响评估 (PDPIA) 作为研究人员的实际路线图.
结论:
- 导航数字视觉数据的伦理格局需要仔细考虑隐私和保护.
- 该PDPIA模板提供了一个结构化的方法,以减轻风险并确保负责任的研究实践.
- 将研究潜力与道德义务相平衡,对于心理学科学的进步至关重要.
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