“一个机器人在看着你”:人形机器人和对隐私的不同影响

Lucas Cardiell
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引用次数: 1

摘要

机器人,特别是那些属于一种特殊类型的机器人技术的机器人,设计和部署用于与人类交流和互动,它们进入了人类生活的越来越多的领域——从研究实验室和手术室到我们的厨房、卧室和办公室。它们可以通过面部表情、凝视方向和声音与人类互动,模仿人类关系的情感动态。因此,它们为人们的隐私创造了新的机会,但也带来了新的挑战和风险。关于社交伴侣机器人(SCR)背景下的隐私问题的文献很少,并且非常关注信息隐私和数据保护。然而,它很少关注隐私的其他方面,例如身体、情感或社交隐私。这篇文章主张隐私的概念是“不断发展的”或“可转换的”,而不是由Daniel J.Solove(2008)和Judith J.Thomson(1975)等著名隐私理论家阐述的“难以捉摸的”隐私概念。换言之,与其假设隐私有一个单一的核心或定义(如Warren和Brandeis在1890年的论文中所定义的),它认为重要的是将隐私概念化为可区分的各个方面,包括信息隐私、思想和行动的隐私以及社会隐私。这种归纳方法使识别隐私的新维度成为可能,从而有效应对人工智能技术的快速技术演变,人工智能技术不断引入新的隐私入侵领域。
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"A Robot Is Watching You”: Humanoid Robots And The Different Impacts On Privacy
Robots, particularly the ones that belong to a special type of robotic technologies designed and deployed for communicating and interacting with humans, slip into more and more domains of human life - from the research laboratories and operating rooms to our kitchens, bedrooms, and offices. They can interact with humans with facial expressions, gaze directions, and voices, mimicking the affective dynamics of human relationships. As a result, they create new opportunities, but also new challenges and risks to peoples’ privacy.  The literature on privacy issues in the context of Social Companion Robots (SCRs) is poor and has a strong focus on information privacy and data protection. It has given, however, less attention to other dimensions of privacy, e.g. physical, emotional, or social privacy. This article argues for an “evolving” or “transformable” notion of privacy, as opposed to the “elusive” concept of privacy elaborated by leading privacy theorists such as Daniel J. Solove (2008) and Judith J. Thomson (1975). In other words, rather than assuming that privacy has a single core or definition (as defined, e.g., in Warren and Brandeis' 1890 paper), it maintains that it is important to conceptualize privacy as distinguishable into various aspects, including informational privacy, the privacy of thoughts and actions, and social privacy. This inductive approach makes it possible to identify new dimensions of privacy and therefore effectively respond to the rapid technological evolution in AI technologies which is constantly introducing new spheres of privacy intrusions.
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