Hidden humans: exploring perceptions of user-work and training artificial intelligence in Aotearoa New Zealand

Abstract

ABSTRACT Artificial intelligence systems require large amounts of data to allow them to learn and achieve high performance. That data is increasingly collected in extractive and exploitative ways, which transfer value and power from individuals to AI system owners. Our research focuses on data that is collected from users of digital platforms, through direct and indirect interaction with those platforms, in ways that are not communicated to users, without consent or compensation. This paper presents our findings from a series of interviews and workshops in the Aotearoa New Zealand context to identify common themes and concerns from a variety of perspectives. Reframing this type of interaction as work or labour brings into view an otherwise unrecognised harm of using this data for training AI systems, and illustrates a new class of exploitative data practices that have become normalised in the digital age. We found that participants particularly emphasised moral or ethical justifications for intervention over financial or economic reasons to act.