EAGER: Collaborative: Design, Perception, and Action - Engineering Information Give-Away

社交媒体界面的设计在很大程度上决定了人们决定在多大程度上以及何时透露私人信息。例如，设计师可以突出显示一个新的系统功能（例如，在地图上显示你的旅行历史），并显示哪些朋友正在使用这个新功能。通过让分享看起来像是一种常态——毕竟，你的朋友都在这么做——设计师向最终用户发出了这样的信号：他可以也应该参与并分享信息。这项研究集中在两个广泛的主题上：设计选择对改变用户认为适合与谁分享的内容有什么影响？规范是如何与设计相互作用来影响这些决策的？了解披露决策是如何制定和操纵的至关重要，因为公司和个人的利益可能大不相同。这是因为规范塑造可以用于善意的目的，例如引导最终用户通过不熟悉的界面，但也可以用于操纵最终用户，使他或她分享他或她宁愿保密的信息。事实上，这种设计模式可以两种方式使用，这使得它们特别有趣：用户无法推断设计师的意图，政策制定者和善意的设计师没有机制来评估他们的设计选择的规范塑造属性。这项研究有助于开发工具来研究用户界面作为社会规范的体现，并对隐私和在线分享的论述做出更广泛的贡献。具体的研究目标是(a)确定塑造披露规范的设计模式，(b)通过实验确定它们的工作机制（例如，模式如何改变对规范的看法，从而改变行为），以及(c)将这些观察结果整合到现有的理论框架中（例如，“隐私微积分”），该框架为披露决策如何做出建模。pi计划使用实验来确定设计对社会规范感知和随后的信息泄露行为的影响。这些实验结合了实验经济学和人机交互（HCI）方法。此外，pi将在计量经济学上测试隐私演算模型的扩展，该模型包括对规范遵守的偏好，估计个人在隐私保护行为和遵守共享规范之间权衡的意愿。本研究将展示如何使用来自不同学科的工具来增强对隐私和HCI设计的理解。研究结果将反馈给隐私、经济学和HCI社区。

The design of social media interfaces greatly shapes how much, and when, people decide to reveal private information. For example, a designer can highlight a new system feature (e.g., your travel history displayed on a map) and show which friends are using this new addition. By making it seem as if sharing is the norm -- after all, your friends are doing it -- the designer signals to the end-user that he can and should participate and share information. This research focuses on two broad themes: what are the effects of design choices on changing what users think is appropriate to share and with whom? and how do norms interact with design to impact these decisions? Understanding how disclosure decisions are made and manipulated is critical as corporate and individual interests can be quite different. This is because norm-shaping can be used for benevolent purposes, such as guiding the end-user through an unfamiliar interface, but can also be used to manipulate the end-user and cause him or her to share information he or she would have preferred to keep private. The fact that such design patterns can be used both ways makes them particularly interesting: the user has no way of inferring the designer's intent, and policy makers and well intentioned designers have no mechanism for assessing the norm-shaping properties of their design choices. This research contributes to the development of tools to study user interfaces as embodiments of social norms as well as contributing more broadly to the discourse of privacy and sharing online.The specific research goals are to (a) identify design patterns that shape disclosure norms, (b) experimentally determine the mechanisms by which they work (e.g., how patterns modify perception of norms and thus behavior), and (c) integrate these observations into existing theoretical frameworks (e.g., the "privacy calculus") that model how disclosure decisions are made. The PIs plan to use experiments to identify the impact of design on the perception of social norms and subsequent information divulging behavior. The experiments combine methodologies from experimental economics with Human Computer Interaction (HCI) methods. Additionally, the PIs will test econometrically an extension of the privacy calculus model that includes a preference for norm compliance, estimating an individual's willingness to trade-off between privacy preserving behavior and compliance with sharing norms. This research will demonstrate how tools from different disciplines can be used to enhance understanding of design in privacy and HCI. The results would feed back to the privacy, economics, and HCI communities.