Can AI Be Transparent?

This chapter explores the multifaceted nature of AI transparency. First, a general introduction first presented by Haresamudram et al. is given on what transparency entails in AI, distinguishing between algorithmic, interaction, and social transparency. Algorithmic transparency concerns the technical dimension of AI, including explainability techniques and the disclosure of other technical aspects. Interaction transparency allows users to recognize their interactions with AI systems, while social transparency concerns organizational governance structures. In a second step, we outline challenges to transparency, such as technical complexity, proprietary constraints, and potential conflicts with privacy regulations. Subsequently, this chapter provides an overview of the practical application of transparency, followed by real-world examples of transparency initiatives, highlighting both successes and failures. The final section argues that effective transparency requires strong regulatory frameworks, international standards, and AI literacy among stakeholders to ensure meaningful transparency beyond superficial disclosure.