What do we mean when we talk about transparency? Towards meaningful transparency in commercial content moderation

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Explainable machine learning in deployment (2019, background): “Though there are aspects of these use cases that are clearly in users’ interest, there are others where that is much less clear, with potential for adverse effects both when these systems work correctly and when they err [25, 38, 60].”
Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020, background): “…in the Global South); democratic legitimacy concerns (about global speech rules being set by a relatively homogenous group of Silicon Valley elites); and process concerns about the overall lack of transparency and accountability (see Gillespie, 2018; Kaye, 2019; Roberts, 2018; Suzor et al., 2019).”
Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator (2019, background): “In recent years, researchers have begun asking questions about the democratic accountability of platform companies and their role in the realization of important public values like freedom of expression, transparency, diversity, and socio-economic equality [39, 43, 46, 52, 103, 109].”
Towards Transparency by Design for Artificial Intelligence (2020, background): “On an individual level, transparency means that users who have been affected by a content moderation decision receive sufficient and contextualized explanations of how and why a decision was made (Suzor et al. 2019).”