监管社交媒体上的算法过滤
Regulating algorithmic filtering on social media
摘要：
通过过滤用户看到的内容，社交媒体平台有能力影响用户的看法和决定，从他们的餐饮选择到他们的投票偏好。这种影响已经引起了人们的关注，许多人呼吁对过滤算法进行监管，但设计和执行法规仍然具有挑战性。在这项工作中，我们研究三个问题。首先，给定一项法规，如何设计审计来执行它？第二，审核是否会给平台带来绩效成本？第三，审核对平台被激励过滤的内容有何影响？作为回应，我们提出了一种方法，这样，给定一个规定，审计师可以测试是否符合该规定，只有黑盒访问过滤算法。然后，我们转向平台的视角。该平台的目标是在满足监管的同时最大化目标函数。我们发现，在某些情况下，监管不会对平台造成高性能成本，特别是，内容多样性可以在协调平台和监管机构的利益方面发挥关键作用。
英文摘要：
By filtering the content that users see, social media platforms have the ability to influence users' perceptions and decisions, from their dining choices to their voting preferences. This influence has drawn scrutiny, with many calling for regulations on filtering algorithms, but designing and enforcing regulations remains challenging. In this work, we examine three questions. First, given a regulation, how would one design an audit to enforce it? Second, does the audit impose a performance cost on the platform? Third, how does the audit affect the content that the platform is incentivized to filter? In response, we propose a method such that, given a regulation, an auditor can test whether that regulation is met with only black-box access to the filtering algorithm. We then turn to the platform's perspective. The platform's goal is to maximize an objective function while meeting regulation. We find that there are conditions under which the regulation does not place a high performance cost on the platform and, notably, that content diversity can play a key role in aligning the interests of the platform and regulators.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
