Transparency and ‘explainability’ have quickly become accepted as core features of ethical uses of data. A process or system is transparent or explainable if it is possible to discover and explain how and why a system made a particular decision. Such systems are to be contrasted with those that are essentially ‘black-boxes’, which process data in ways which cannot be understood or explained to those they effect. I will talk about why transparency and explainability have become central to data ethics, and suggest that there are reasons to question that centrality. We should be more concerned with reliability and with how automated systems compare, ethically, with alternative ways of doing the tasks which might be done by automated systems.