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AI systems play an increasingly important role in shaping and regulating the lives of millions of human beings across the world. Calls for greater transparency from such systems have been widespread. However, there is considerable ambiguity concerning what "transparency" actually means, and therefore, what greater transparency might entail. While, according to some debates, transparency requires seeing through the artefact or device, widespread calls for transparency imply seeing into different aspects of AI systems. These two notions are in apparent tension with each other, and they are present in two lively but largely disconnected debates. In this paper, we aim to further analyse what these calls for transparency entail, and in so doing, clarify the sorts of transparency that we should want from AI systems. We do so by offering a taxonomy that classifies different notions of transparency. After a careful exploration of the different varieties of transparency, we show how this taxonomy can help us to navigate various domains of human-technology interactions, and more usefully discuss the relationship between technological transparency and human agency. We conclude by arguing that all of these different notions of transparency should be taken into account when designing more ethically adequate AI systems.
Andrada et al. (Sat,) studied this question.