Lauritz Munch

Many seem to think that AI-induced responsibility gaps are morally bad and therefore ought to be avoided. We argue, by contrast, that there is at least a pro tanto reason to welcome responsibility gaps. The central reason is that it can be bad for people to be responsible for wrongdoing. This, we argue, gives us one reason to prefer automated decision-making over human decision-making, especially in contexts where the risks of wrongdoing are high. While we are not the first to suggest that responsibility gaps should sometimes be welcomed, our argument is novel. Others have argued that responsibility gaps should sometimes be welcomed because they can reduce or eliminate the psychological burdens caused by tragic moral choice-situations. By contrast, our argument explains why responsibility gaps should sometimes be welcomed even in the absence of tragic moral choice-situations, and even in the absence of psychological burdens.

In this paper, we defend what we call the ‘Hybrid View’ of privacy. According to this view, an individual has privacy if, and only if, no one else forms an epistemically warranted belief about the individual’s personal matters, nor perceives them. We contrast the Hybrid View with what seems to be the most common view of what it means to access someone’s personal matters, namely the Belief-Based View. We offer a range of examples that demonstrate why the Hybrid View is more plausible than the Belief-Based View. Finally, we show how the Hybrid View generates a more plausible fit between the concept of privacy, and a (morally objectionable) violation of privacy.

The stakes associated with an algorithmic decision are often said to play a role in determining whether the decision engenders a right to an explanation. More specifically, “high stakes” decisions are often said to engender such a right to explanation whereas “low stakes” or “non-high” stakes decisions do not. While the overall gist of these ideas is clear enough, the details are lacking. In this paper, we aim to provide these details through a detailed investigation of what we will call the “Simple Stakes Thesis”. The Simple Stakes Thesis, as it will turn out, is too simple. For even if the stakes associated with a specific one-off decision are low—and hence does not engender a right to an explanation—such decisions may nevertheless form part of a high stakes pattern or aggregate of decisions. In such cases, we argue, even a low stakes decision may engender a right to explanation. Not only does this show that the right to explanation is more demanding than so far recognized. It also shows that the stakes thesis is significantly harder to apply in practice.

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.

If I decide to disclose information about myself, this act can undermine other people’s ability to effectively conceal information about themselves. One case in point involves genetic information: if I share ‘my’ genetic information with others, I thereby also reveal genetic information about my biological relatives. Such dependencies are well-known in the privacy literature and are often referred to as ‘privacy dependencies’. Some take the existence of privacy dependencies to generate a moral duty to sometimes avoid sharing information about oneself. If true, we argue, then it is sometimes justified for others to impose harm on the person sharing the information to prevent them from doing so. This is a highly revisionary implication. Hence, one must either endorse a highly revisionary view on what one may do to protect one’s privacy, or one must reject the view that privacy dependencies can be used to justify a moral duty that constrains choices about sharing information about oneself.

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.

Often, when we share information about ourselves, we contribute to people learning personal things about others. This may happen because what we share about ourselves can be used to infer personal information about others. Such dependencies have become known as privacy dependencies in the literature. It is sometimes claimed that the scope of the right to privacy should be expanded in light of such dependencies. For example, some have argued that inferring information about others can violate their right to privacy. Others have argued that sharing personal information about yourself that license such inferences can by itself violate the right to privacy. In this paper, we argue that the latter view should be rejected.

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.

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.

In this paper, we defend what we call the ‘Hybrid View’ of privacy. According to this view, an individual has privacy if, and only if, no one else forms an epistemically warranted belief about the individual’s personal matters, nor perceives them. We contrast the Hybrid View with what seems to be the most common view of what it means to access someone’s personal matters, namely the Belief-Based View. We offer a range of examples that demonstrate why the Hybrid View is more plausible than the Belief-Based View. Finally, we show how the Hybrid View generates a more plausible fit between the concept of privacy, and the concept of a (morally objectionable) violation of privacy.