This article provides a new typology for understanding human labour integrated into the production of artificial intelligence systems through data preparation and model evaluation. We call these forms of labour ‘AI data work’ and show how they are an important and necessary element of the artificial intelligence production process. We draw on fieldwork with an artificial intelligence data business process outsourcing centre specialising in computer vision data, alongside a decade of fieldwork with microwork platforms, business process outsourcing, and artificial intelligence companies to help dispel confusion around the multiple concepts and frames that encompass artificial intelligence data work including ‘ghost work’, ‘microwork’, ‘crowdwork’ and ‘cloudwork’. We argue that these different frames of reference obscure important differences between how this labour is organised in different contexts. The article provides a conceptual division between the different types of artificial intelligence data work institutions and the different stages of what we call the artificial intelligence data pipeline. This article thus contributes to our understanding of how the practices of workers become a valuable commodity integrated into global artificial intelligence production networks.

中文翻译：

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人工智能数据工作的类型学

本文提供了一种新的类型学，用于通过数据准备和模型评估来理解人工智能系统生产中融入的人类劳动。我们将这些劳动形式称为“人工智能数据工作”，并展示它们如何成为人工智能生产过程的重要且必要的元素。我们利用专门从事计算机视觉数据的人工智能数据业务流程外包中心的实地调查，以及十年来对微工作平台、业务流程外包和人工智能公司的实地调查，帮助消除围绕人工智能的多个概念和框架的混乱数据工作包括“幽灵工作”、“微工作”、“众包工作”和“云工作”。我们认为，这些不同的参考框架掩盖了不同背景下劳动组织方式之间的重要差异。文章对不同类型的人工智能数据工作机构以及我们所说的人工智能数据管道的不同阶段进行了概念划分。因此，本文有助于我们理解工人的实践如何成为融入全球人工智能生产网络的有价值的商品。