Abstract
Luciano Floridi was not the first to discuss the idea of group privacy, but he was perhaps the first to discuss it in relation to the insights derived from big data analytics. He has argued that it is important to investigate the possibility that groups have rights to privacy that are not reducible to the privacy of individuals forming such groups. In this paper, we introduce a distinction between two concepts of group privacy. The first, the “what happens in Vegas stays in Vegas” privacy (in the following: WHVSV privacy), deals with confidential information shared with the member of a group and inaccessible to (all or a specific group of) outsiders. The second, to which we shall refer as inferential privacy, deals with the inferences that can be made about a group of people defined by a feature, or combination thereof, shared by all individuals in the group. We show why we unreservedly agree with Floridi that groups can have a form of privacy that amounts to more than the mere fact of being sets of individuals each of whom has individual privacy; moreover, like Floridi, we find it plausible that at least some groups (those satisfying our definition of type-a groups) may have a right to a species of group privacy (that is, WHVSV privacy) as groups (and not just as individuals who belong to those groups). However, by turning our attention to the context of big data analytics, we show that the relevant, new notion of group privacy is one of inferential privacy. We argue that an absolute right (either of individuals or groups) to inferential privacy is implausible. We also show that many groups generated algorithmically (those satisfying our definition of type-b groups) cannot be right holders as groups (unless they become type-a groups).
Highlights
Luciano Floridi was not the first to discuss the idea of group privacy, but he was perhaps the first to discuss it in relation to the insights derived from big data analytics (Floridi 2014, 2016)
We maintain that the essential ethical problem is how to deal with generalizable knowledge (GK) and whether the production of new GK counts as an infringement of Bgroup privacy.^ We proceed to provide a definition of group privacy that is pertinent to the issue at stake, where groups are identified by any feature individuals have in common, which is represented as the result of applying an algorithm, or used in an algorithmic decision
We have distinguished two concepts of group privacy, namely Bwhat happens in Vegas stays in Vegas^ (WHVSV) privacy and inferential privacy
Summary
Luciano Floridi was not the first to discuss the idea of group privacy, but he was perhaps the first to discuss it in relation to the insights derived from big data analytics (Floridi 2014, 2016). It is perfectly natural to speak of group privacy in this sense, but it is easy to understand why individuals have an interest in it Both forms of WHVSV privacy protect: The desire and need of people to come together, to exchange information, share feelings, make plans and act in concert to attain their objectives (Bloustein 2003, 125). We maintain that the essential ethical problem is how to deal with GK and whether the production of new GK (through big data or other methods) counts as an infringement of Bgroup privacy.^ We proceed to provide a definition of group privacy that is pertinent to the issue at stake, where (type-b) groups are identified by any feature (or combination thereof) individuals have in common, which is represented as the result of applying an algorithm, or used in an algorithmic decision. We will analyze inferential privacy to determine whether a right to inferential privacy is morally plausible and whether the right holders should be considered individuals, or groups, or both
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