Does Explainability Require Transparency?

Dealing with opaque algorithms, the frequent overlap between transparency and explainability produces seemingly unsolvable dilemmas, as the much-discussed trade-off between model performance and model transparency. Referring to Niklas Luhmann's notion of communication, the paper argues that explainability does not necessarily require transparency and proposes an alternative approach. Explanations as communicative processes do not imply any disclosure of thoughts or neural processes, but only reformulations that provide the partners with additional elements and enable them to understand (from their perspective) what has been done and why. Recent computational approaches aiming at post-hoc explainability reproduce what happens in communication, producing explanations of the working of algorithms that can be different from the processes of the algorithms.