Recommendation algorithms play an increasingly central role in our societies. However, thus far, these algorithms are mostly designed and parameterized unilaterally by private groups or governmental authorities. In this paper, we present an end-to-end permissionless collaborative algorithmic governance method with security guarantees. Our proposed method is deployed as part of an open-source content recommendation platform https://tournesol.app, whose recommender is collaboratively parameterized by a community of (non-technical) contributors. This algorithmic governance is achieved through three main steps. First, the platform contains a mechanism to assign voting rights to the contributors. Second, the platform uses a comparison-based model to evaluate the individual preferences of contributors. Third, the platform aggregates the judgements of all contributors into collective scores for content recommendations. We stress that the first and third steps are vulnerable to attacks from malicious contributors. To guarantee the resilience against fake accounts, the first step combines email authentication, a vouching mechanism, a novel variant of the reputation-based EigenTrust algorithm and an adaptive voting rights assignment for alternatives that are scored by too many untrusted accounts. To provide resilience against malicious authenticated contributors, we adapt Mehestan, an algorithm previously proposed for robust sparse voting. We believe that these algorithms provide an appealing foundation for a collaborative, effective, scalable, fair, contributor-friendly, interpretable and secure governance. We conclude by highlighting key challenges to make our solution applicable to larger-scale settings.
翻译:然而,到目前为止,这些算法大多是由私人团体或政府当局单方面设计并参数化的。在本文中,我们提出了一个带有安全保障的终至终允许合作算法治理方法。我们建议的方法是作为开放源码内容建议平台https://tournesol.app的一部分部署的。这个建议者由一个(非技术)贡献者群体协作参数化。这种算法治理是通过三个主要步骤实现的。首先,该平台包含一个将表决权分配给捐款者的机制。第二,该平台使用一个基于比较的模型来评估捐款者的个人偏好。第三,该平台将所有捐款者的判断汇总为内容建议的集体分数。我们强调,第一和第二步骤很容易受到恶意捐款者的攻击。为了保证对虚假账户的复原力,第一个步骤是将电子邮件认证、一种担保机制、一种基于声誉的可信任性算法的一种新变式,以及一个适应性快速的投票权分配,用于选择被过多不可信的账户评级的替代方案。为了提供抵御恶意认证贡献者的能力,我们之前的可靠地将Mehestan演算法,我们为一个可靠的、一个可靠的、一个可靠的、一个可靠的、一个可靠的、一个可靠的审计式的、我们以前相信一个可靠的选举的、我们为可靠的、我们一个可靠的选举的、我们一个可靠的、我们一个可靠的、一个可靠的、一个可靠的投资的、我们一个可靠的、我们能够的投资者的、我们为一个有效的算法。