Academic and policy proposals on algorithmic accountability often seek to understand algorithmic systems in their socio-technical context, recognising that they are produced by 'many hands'. Increasingly, however, algorithmic systems are also produced, deployed, and used within a supply chain comprising multiple actors tied together by flows of data between them. In such cases, it is the working together of an algorithmic supply chain of different actors who contribute to the production, deployment, use, and functionality that drives systems and produces particular outcomes. We argue that algorithmic accountability discussions must consider supply chains and the difficult implications they raise for the governance and accountability of algorithmic systems. In doing so, we explore algorithmic supply chains, locating them in their broader technical and political economic context and identifying some key features that should be understood in future work on algorithmic governance and accountability (particularly regarding general purpose AI services). To highlight ways forward and areas warranting attention, we further discuss some implications raised by supply chains: challenges for allocating accountability stemming from distributed responsibility for systems between actors, limited visibility due to the accountability horizon, service models of use and liability, and cross-border supply chains and regulatory arbitrage

翻译：关于算法问责的学术与政策探讨，常试图在技术社会语境中理解算法系统，认识到这些系统是由"多方之手"共同创造的。然而，算法系统正日益在由数据流联结多个行动者的供应链中被生产、部署和使用。在此类情境中，正是不同行动者组成的算法供应链——他们共同参与系统的生产、部署、使用与功能实现——协同运作，才驱动系统运行并产生特定结果。我们认为，算法问责讨论必须考虑供应链及其对算法系统治理与问责带来的复杂影响。为此，我们探讨算法供应链，将其置于更广阔的技术与政治经济语境中，并识别出未来算法治理与问责研究（特别是涉及通用人工智能服务领域）中需要理解的一些关键特征。为指明前进方向与需关注的领域，我们进一步讨论了供应链引发的若干问题：因系统责任在行动者间分散而导致的问责分配难题、因问责视域限制导致的可见性不足、服务使用模式与法律责任、跨境供应链与监管套利。