Trustworthy artificial intelligence (TAI) is trending high on the political agenda. However, what is actually implied when talking about TAI, and why it is so difficult to achieve, remains insufficiently understood by both academic discourse and current AI policy frameworks. This paper offers an analytical scheme with four different dimensions that constitute TAI: a) A user perspective of AI as a quasi-other; b) AI's embedding in a network of actors from programmers to platform gatekeepers; c) The regulatory role of governance in bridging trust insecurities and deciding on AI value trade-offs; and d) The role of narratives and rhetoric in mediating AI and its conflictual governance processes. It is through the analytical scheme that overlooked aspects and missed regulatory demands around TAI are revealed and can be tackled. Conceptually, this work is situated in disciplinary transgression, dictated by the complexity of the phenomenon of TAI. The paper borrows from multiple inspirations such as phenomenology to reveal AI as a quasi-other we (dis-)trust; Science & Technology Studies (STS) to deconstruct AI's social and rhetorical embedding; as well as political science for pinpointing hegemonial conflicts within regulatory bargaining.
