Data dashboards are designed to help users manage data collected about them. However, prior work showed that exposure to some dashboards, notably Google's My Activity dashboard, results in significant decreases in perceived concern and increases in perceived benefit from data collection, contrary to expectations. We theorize that this result is due to the fact that data dashboards currently do not sufficiently "connect the dots" of the data food chain, that is, by connecting data collection with the use of that data. To evaluate this, we designed a study where participants assigned advertising interest labels to their own real activities, effectively acting as a behavioral advertising engine to "connect the dots." When comparing pre- and post-labeling task responses, we find no significant difference in concern with Google's data collection practices, which indicates that participants' priors are maintained after more exposure to the data food chain (differing from prior work), suggesting that data dashboards that offer deeper perspectives of how data collection is used have potential. However, these gains are offset when participants are exposed to their true interest labels inferred by Google. Concern for data collection dropped significantly as participants viewed Google's labeling as generic compared to their own more specific labeling. This presents a possible new paradox that must be overcome when designing data dashboards, the generic paradox, which occurs when users misalign individual, generic inferences from collected data as benign compared to the totality and specificity of many generic inferences made about them.

翻译：数据仪表盘旨在帮助用户管理自身被收集的数据。然而，先前研究表明，接触某些仪表盘（特别是谷歌的“我的活动”仪表盘）反而会导致用户对数据收集的感知担忧显著下降、感知收益显著上升，这与预期相悖。我们推测这一结果源于当前数据仪表盘未能充分“串联”数据食物链——即未能将数据收集行为与数据实际用途有效关联。为验证此假设，我们设计了一项实验：要求参与者为自己的真实活动标注广告兴趣标签，实质上模拟行为广告引擎来“串联因果”。对比标注任务前后的反馈发现，参与者对谷歌数据收集行为的担忧无显著差异，这表明在更深入接触数据食物链后（与先前研究不同），参与者的原有认知得以维持，暗示能揭示数据收集深层用途的仪表盘具有潜在价值。然而，当参与者知晓谷歌为其推断的真实兴趣标签后，这些正面效果随即消失。由于参与者认为谷歌的标签分类较自己标注更为笼统，其对数据收集的担忧显著降低。这揭示了数据仪表盘设计中须克服的新型悖论——“笼统化悖论”：当用户将泛化的个体推断与针对自身的大量具体推断相比时，误认为前者危害较小。