Lauritz Munch

Many believe that we ought to treat people as individuals and that this form of treatment is in some sense incompatible with treating people as members of groups. Yet, the relation between these two kinds of treatments is elusive. In this paper, we develop a novel account of the normative requirement to treat people as individuals. According to this account, treating people as individuals requires treating people as agents in the appropriate capacity. We call this the Agency Attunement Account. This view has the surprising implication that it's not only possible to fail in treating people as individuals but also possible to fail in treating people as members of groups, on the presumption that people's agency is sometimes nested in, and exercised via, agential groups.

Andrei Marmor has recently offered a narrow interpretation of the right to privacy as a right to having a reasonable amount of control over one's self‐presentation. He claims that the interest people have in preventing others from abusing their personal information to do harm is not directly protected by the right to privacy. This article rejects that claim and defends a view according to which concerns about abuse play a central role in fleshing out the appropriate scope of a general right to privacy.

Do privacy rights restrict what is permissible to infer about others based on statistical evidence? This paper replies affirmatively by defending the following symmetry: there is not necessarily a morally relevant difference between directly appropriating people’s private information—say, by using an X-ray device on their private safes—and using predictive technologies to infer the same content, at least in cases where the evidence has a roughly similar probative value. This conclusion is of theoretical interest because a comprehensive justification of the thought that statistical inferences can violate privacy rights is lacking in the current literature. Secondly, the conclusion is of practical interest due to the need for moral assessment of emerging predictive algorithms.