发表机构
Carnegie Mellon University（卡内基梅隆大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对社会技术干预措施缺乏比较依据的问题，提出含5项准则的多准则评估框架，以错误信息领域为例调查发现有效性与可行性、接受度存在矛盾，并为从业者提供决策框架。
AI 中文摘要
在内容审核、隐私界面、推荐系统等社会技术领域，设计者和政策制定者需从日益增多的拟议干预措施中做出选择，但通常缺乏比较它们的原则性依据。现有研究倾向于单独评估干预措施，且大多仅围绕有效性准则，而成本、工作量、可行性等实施约束往往被分开考虑。我们提出了一种用于评估社会技术干预措施的多准则框架，该框架通过错误信息这一拟议对策备受关注的领域实例化。我们针对5项评估准则（政治可行性、有效性、用户接受度、成本、实施工作量），对39名研究者调查了40项可操作的干预措施。研究发现，专家判定为最有效的干预措施，并不总是公众最能接受或最易实施的；我们还探讨了这种矛盾对错误信息之外的社会技术干预设计的影响，并为需权衡社会技术干预利弊的从业者提供了决策框架。
英文摘要
Designers and policymakers in sociotechnical domains like content moderation, privacy interfaces, recommender systems and beyond, must choose among a growing menu of proposed interventions, but typically lack a principled basis for comparing them. Prior work tends to evaluate interventions individually and mostly along the effectiveness criteria, while implementation constraints such as cost, effort and feasibility are often considered separately. We present a multi-criteria framework for evaluating sociotechnical interventions. This framework is instantiated through the case of misinformation, a domain of intense focus for proposed countermeasures. We survey $N=39$ researchers on 40 operationalized interventions across five evaluative criteria: political feasibility, effectiveness, user acceptance, cost, and implementation effort. We find that the interventions that experts judge to be the most effective are not always the most acceptable to the public or the most feasible to implement. We also discuss how this tension has implications for the design of sociotechnical interventions beyond misinformation, and offer a decision framework for practitioners navigating the trade-offs of sociotechnical interventions.
