  Transparency regarding the processing of personal data in online services is
a necessary precondition for informed decisions on whether or not to share
personal data. In this paper, we argue that privacy interfaces shall
incorporate the context of display, personal preferences, and individual
competences of data subjects following the principles of universal design and
usable privacy. Doing so requires -- among others -- to consciously decouple
the provision of transparency information from their ultimate presentation. To
this end, we provide a general model of how transparency information can be
provided from a data controller to data subjects, effectively leveraging
machine-readable transparency information and facilitating versatile
presentation interfaces. We contribute two actual implementations of said
model: 1) a GDPR-aligned privacy dashboard and 2) a chatbot and virtual voice
assistant enabled by conversational AI. We evaluate our model and
implementations with a user study and find that these approaches provide
effective and time-efficient transparency. Consequently, we illustrate how
transparency can be enhanced using machine-readable transparency information
and how data controllers can meet respective regulatory obligations.
