Emerging discussions on the responsible government use of algorithmic technologies propose transparency and public participation as key mechanisms for preserving accountability and trust. But in practice, the adoption and use of any technology shifts the social, organizational, and political context in which it is embedded. Therefore translating transparency and participation efforts into meaningful, effective accountability must take into account these shifts. We adopt two theoretical frames, Mulligan and Nissenbaum's handoff model and Star and Griesemer's boundary objects, to reveal such shifts during the U.S. Census Bureau's adoption of differential privacy (DP) in its updated disclosure avoidance system (DAS) for the 2020 census. This update preserved (and arguably strengthened) the confidentiality protections that the Bureau is mandated to uphold, and the Bureau engaged in a range of activities to facilitate public understanding of and participation in the system design process. Using publicly available documents concerning the Census' implementation of DP, this case study seeks to expand our understanding of how technical shifts implicate values, how such shifts can afford (or fail to afford) greater transparency and participation in system design, and the importance of localized expertise throughout. We present three lessons from this case study toward grounding understandings of algorithmic transparency and participation: (1) efforts towards transparency and participation in algorithmic governance must center values and policy decisions, not just technical design decisions; (2) the handoff model is a useful tool for revealing how such values may be cloaked beneath technical decisions; and (3) boundary objects alone cannot bridge distant communities without trusted experts traveling alongside to broker their adoption.

翻译：关于政府负责任地使用算法技术的新兴讨论，将透明度与公众参与视为维护问责与信任的关键机制。然而在实践中，任何技术的采纳与应用都会改变其所处的社会、组织与政治环境。因此，要将透明度与参与性工作转化为有意义且有效的问责机制，必须考虑这些环境变化。本研究采用穆利根与尼森鲍姆的交接模型，以及斯塔与格里塞默的边界对象两个理论框架，揭示美国人口普查局在2020年人口普查中采用差分隐私更新其披露避免系统过程中发生的环境变迁。此次更新维护（甚至可以说强化了）该局依法必须履行的保密义务，同时该局开展了系列活动以促进公众对该系统设计过程的理解与参与。基于人口普查局实施差分隐私的公开文件，本案例研究旨在拓展我们对以下问题的理解：技术变迁如何牵涉价值观念，这种变迁如何促进（或未能促进）系统设计中更大的透明度与参与性，以及在地化专业知识的重要性。我们从案例研究中总结出三条经验，以深化对算法透明度与参与性的理解：（1）算法治理中的透明度与参与性工作必须以价值观念与政策决策为核心，而不仅仅是技术设计决策；（2）交接模型是揭示这些价值如何可能被技术决策所掩盖的有效工具；（3）若没有值得信赖的专家伴随引导以促成采纳，边界对象本身无法连接相距遥远的社群。