The debate on Open Data and Data Protection focuses on individual privacy. How can the latter be protected while taking advantage of the enormous potentialities offered by ever-bigger Open Data and ever-smarter algorithms and applications? The tension is sometimes presented as being asymmetric: between the ethics of privacy and the politics of security. In fact, it is ultimately ethical. Two moral duties need to be reconciled: fostering human rights and improving human welfare. The tension is obvious if one considers medical contexts and biomedical Big Data, for example, where protection of patients’ records and cure or prevention of diseases need to go hand in hand (Howe et al. 2008; Groves et al. 2013). Currently, the balance between these two moral duties is implicitly understood within a classic ontological framework. The beneficiaries of the exercise of the two moral duties are the individual vs. the society to which the individual belongs. At first sight, this may seem unproblematic. We work on the assumption that these are the only two “weights” on the two sides of the scale. Such a framework is not mistaken, but it is dangerously reductive, and it should be expanded urgently. For there is a third “weight” that must be taken into account by Data Protection, that of groups and their privacy. Privacy as a group right is a right held by a group as a group rather than by its members severally. It is the group, not its members, that is correctly identified as the right-holder. A typical example is the right of self-determination, which is held by a nation as a whole. The idea that groups may have a right to privacy is not new (see for example Bloustein (1978, 2003)) and it is open to debate (Bisaz 2012). But it has not received the attention it deserves, although it is becoming increasingly important. This because, by far, most people are not targeted by ICTs as individuals but as members of specific groups, where the groups are the really interesting focus, as carriers of rights, values, and potential risks. Think of owners of such and such kind of car, shoppers of such and such kind of food, people who like this kind of music, or people who go to that kind of restaurant, cats owners, dogs owners, people who live at that kind of postal code address, carriers of a specific gene, people affected by a certain disease, ... Open Data is more likely to treat types (of customers, users, citizens, demographic population, etc.) Philos. Technol. (2014) 27:1–3 DOI 10.1007/s13347-014-0157-8