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Exploring Interpretations of Data from the Internet of Things in the Home

机译:探索家庭物联网数据解读

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摘要

The ‘Internet of Things’ (IoT) can be expected to radically increase the amount of potentially sensitive data gathered in our homes. This study explores the social implications of the presentation of data that could be collected within the household. In particular, it focuses on how ambiguities in these data, combined with existing interpersonal relationships, could influence social dynamics. Thirty-five participants were each presented with three separate household scenarios, involving ambiguous data that were collected and presented via near-future IoT technologies. Each participant was asked to respond to a series of open and closed questions about how they would interpret the data, how they would react to it and their general opinions of the technologies presented. Through qualitative and quantitative analysis of their responses, we contribute an understanding of how people interpret information about those around them. We find a common willingness to make inferences based on ambiguities within the data, even when participants are aware of the limitations of their understanding. We also find that sharing data produced via tagging of everyday objects raises a high level of privacy concern, and that, in a somewhat incoherent stance, users are more comfortable in sharing data publicly than in a targeted fashion with commercial organizations. Our findings also suggest that the age of the target user group has a greater effect on ease of use judgements than the nature of the technology, and we find some evidence that user’s interpretations can be biased by an individual’s age.
机译:物联网(IoT)有望从根本上增加在家中收集的潜在敏感数据的数量。这项研究探讨了可以在家庭中收集的数据的呈现的社会意义。特别是,它着眼于这些数据中的歧义性以及现有的人际关系如何影响社会动态。分别向35名参与者展示了三种独立的家庭场景,其中包括通过不久的物联网技术收集和呈现的模棱两可的数据。要求每个参与者回答一系列有关他们如何解释数据,如何对数据做出反应以及对所展示技术的一般看法的公开和封闭式问题。通过对他们的回答进行定性和定量分析,我们有助于人们理解他们周围的人的信息。我们发现,即使参与者意识到自己理解的局限性,我们仍然愿意根据数据中的歧义做出推断。我们还发现,共享通过标记日常物品产生的数据引起了高度的隐私关注,并且,在某种程度不连贯的立场下,与公开地与商业组织进行共享相比,用户更愿意公开共享数据。我们的发现还表明,目标用户群体的年龄对易用性判断的影响要大于技术的本质,并且我们发现一些证据表明,用户的理解可能会因个人的年龄而产生偏差。

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