论文标题
“公共 - 循环”：有争议的公共政策领域中促进算法决定的审议
"Public(s)-in-the-Loop": Facilitating Deliberation of Algorithmic Decisions in Contentious Public Policy Domains
论文作者
论文摘要
该立场论文提供了一个框架，可以思考如何更好地涉及人类影响力参与有争议的公共政策问题的算法决策。从传播文献的见解中，我们介绍了一种“公共”方法，并列举了这种方法至关重要的三个特征：公众作为多元政治实体，通过审议和公众的建设进行集体决策。它探讨了这些功能如何提高我们对利益相关者参与AI设计的理解，例如累犯预测等有争议的公共政策领域。最后，它为HCI社区支持这项工作的一部分研究议程。
This position paper offers a framework to think about how to better involve human influence in algorithmic decision-making of contentious public policy issues. Drawing from insights in communication literature, we introduce a "public(s)-in-the-loop" approach and enumerates three features that are central to this approach: publics as plural political entities, collective decision-making through deliberation, and the construction of publics. It explores how these features might advance our understanding of stakeholder participation in AI design in contentious public policy domains such as recidivism prediction. Finally, it sketches out part of a research agenda for the HCI community to support this work.
