从录音中推断个人信息:用户意识和隐私问题

Jacob Leon Kröger, L. Gellrich, Sebastian Pape, S.R. Brause, Stefan Ullrich
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引用次数: 14

摘要

摘要通过声音特征和表达方式,即使是看似温和的录音也可以揭示被录音者的敏感属性(如地理出身、健康状况、性格)。我们在英国(n=683,18-69岁)进行了一项具有全国代表性的调查,以调查人们对声音和言语分析的推理能力的认识。我们的研究结果表明,尽管不同类别的推断信息的意识水平各不相同,但所有参与者的意识普遍较低,即使是在具有计算机科学、数据挖掘和IT安全专业经验的参与者中也是如此。例如,只有18.7%的参与者至少在一定程度上意识到,可以从录音中推断出身体和心理健康信息。许多参与者很少(28.4%)或从未(42.5%)想过从语音数据推断个人信息的可能性。在关于这个话题的简短教育视频之后,参与者只表达了适度的隐私问题。然而,基于对开放文本反应的分析,不关心的反应似乎在很大程度上是由关于可能的数据滥用的知识差距所解释的。观看教育视频降低了参与者使用语音设备的意愿。在讨论我们的研究结果的监管影响时,我们对数据处理的“知情同意”概念提出了质疑。我们还认为,关于个人的推断需要被法律承认为个人数据,并得到相应的保护。
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Personal information inference from voice recordings: User awareness and privacy concerns
Abstract Through voice characteristics and manner of expression, even seemingly benign voice recordings can reveal sensitive attributes about a recorded speaker (e. g., geographical origin, health status, personality). We conducted a nationally representative survey in the UK (n = 683, 18–69 years) to investigate people’s awareness about the inferential power of voice and speech analysis. Our results show that – while awareness levels vary between different categories of inferred information – there is generally low awareness across all participant demographics, even among participants with professional experience in computer science, data mining, and IT security. For instance, only 18.7% of participants are at least somewhat aware that physical and mental health information can be inferred from voice recordings. Many participants have rarely (28.4%) or never (42.5%) even thought about the possibility of personal information being inferred from speech data. After a short educational video on the topic, participants express only moderate privacy concern. However, based on an analysis of open text responses, unconcerned reactions seem to be largely explained by knowledge gaps about possible data misuses. Watching the educational video lowered participants’ intention to use voice-enabled devices. In discussing the regulatory implications of our findings, we challenge the notion of “informed consent” to data processing. We also argue that inferences about individuals need to be legally recognized as personal data and protected accordingly.
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