Lauritz Munch

Most studies on the ethics of privacy focus on what others ought to do to accommodate our interest in privacy. I focus on a related but distinct question that has attracted less attention in the literature: When, if ever, does morality require us to safeguard our own privacy? While we often have prudential reasons for safeguarding our privacy, we are also, at least sometimes, morally required to do so. I argue that we, sometimes, ought to safeguard our privacy for the sake of the possible wrongdoer, in order to prevent the possible wrongdoer from committing a morally defiling act that renders them worse off. I illustrate the variety of cases in which this duty binds us and contrast my view to some other claims in the literature which also purport to show that we sometimes have a duty to safeguard our own privacy.

This paper concerns the double standard debate in the ethics of AI literature. This debate essentially revolves around the question of whether we should subject AI systems to different normative standards than humans. So far, the debate has centered around the desideratum of transparency. That is, the debate has focused on whether AI systems must be more transparent than humans in their decision-making processes in order for it to be morally permissible to use such systems. Some have argued that the same standards of transparency should be applied across the board, for AI systems and humans alike. Others have argued that we should hold AI systems to higher standards than humans in terms of transparency. In this paper, we first point out that there are structurally similar double standard debates to be had about other desiderata besides transparency, such as predictive accuracy. Second, we argue that when we focus on predictive accuracy, there are at least two reasons for holding AI systems to a lower standard than humans.

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.