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A Rights-Based Approach to Trustworthy AI in Social Media

机译:一种基于权利的社交媒体值得信赖AI的方法

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Social media platforms increasingly use powerful artificial intelligence (AI) that are fed by the vast flows of digital content that may be used to analyze user behavior, mental state, and physical context. New forms of AI-generated content and AI-driven virtual agents present new forms of risks in social media use, the harm of which will be difficult to predict. Delivering trustworthy social media will therefore be increasingly predicated on effectively governing the trustworthiness of its AI components. In this article, we examine different approaches to the governance AI and the Big Data processing that drives it being explored. We identify a potential over-reliance on individual rights at the expense of consideration of collective rights. In response, we propose a collective approach to AI data governance grounded in a legal proposal for universal, non-exclusive data ownership right. We use the Institutional Analysis and Development (IAD) framework to explore the relative costs and benefits on stakeholders in two use cases, one focused on digital content consumers the other focused on digital content knowledge workers. Following an analysis that looks at self-regulation and industry-state co-regulation, we propose governance through shared data ownership. In this way, future social media platforms may be able to maintain trust in their use of AI by committing to no datafication without representation.
机译:社交媒体平台越来越多地利用由庞大的数字内容流馈送的强大人工智能(AI),这些数字内容可用于分析用户行为,心理状态和物理上下文。新形式的AI生成的内容和AI驱动的虚拟代理商在社交媒体使用中呈现出新的风险形式,这将难以预测。因此,提供值得信赖的社交媒体将越来越追求有效地治疗其AI组件的可信度。在本文中,我们研究了治理AI的不同方法以及推动它正在探索的大数据处理。我们规范了对各个权利的潜在过度依赖,以牺牲集体权利的思考。作为回应,我们向AI数据治理提出了一项集体方法,以普遍,非独家数据所有权的法律提案为基础。我们使用制度分析和发展(IAD)框架来探讨两种用例中利益攸关方对利益攸关方的相对成本和福利,一个专注于数字内容消费者,另一个专注于数字内容知识工作者。在看着自我监管和行业的共同规则的分析之后,我们通过共享数据所有权提出治理。通过这种方式,未来的社交媒体平台可能能够通过在没有表示的情况下毫无疑问来维持对AI的使用。

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