Alexis Morin-Martel

Kingmaking occurs when a board game participant who can no longer win attempts to change the winner without improving their own position. This phenomenon often elicits strong negative reactions and is widely regarded as a breach of two normative expectations in gameplay: the Meritocratic Norm, which holds that the most skilled or deserving player ought to win, and the Striving Norm, which demands that all players continue to try to win even when victory is unattainable. While both norms are prominent in player discourse, we argue that they fail to capture what is morally significant about kingmaking. We contend that kingmaking is morally objectionable only when it constitutes a failure to abide by the Lusory Impartiality principle, according to which players must bracket extra-game allegiances and treat each other as equals qua individuals. This norm speaks in favor of a form of Moderate Moralism about games: while many in-game actions are not apt targets of moral evaluation, some—like kingmaking—can have genuine moral import when they express interpersonal disrespect. One upshot is that kingmaking that doesn’t express such disrespect isn’t wrong—and that its salience can even be valuable in some contexts. When motivated by in-game reciprocity, strategic deterrence, or aesthetic storytelling, kingmaking can be justified and may enhance the strategic and narrative value of play.

This paper’s central question is whether trust can have inherent moral value. While traditional views emphasize trust's instrumental value in extending our agential capacities, a new perspective suggests that trust is also a way to convey respect to those we trust. This paper defends the view that full-blooded trust—trust grounded in the belief that the trustee is trustworthy—always involves appraisal respect: a positive evaluative attitude toward the trustee’s moral character or conduct. I argue that this respect confers a distinctive moral value on full-blooded trust, one that is absent in forms of trust without belief, such as therapeutic or recalcitrant trust, even if they may still be instrumentally valuable. Full-blooded trust is the paradigm of trust because it uniquely affirms the trustee as worthy of moral regard and serves as a kind of mirror, helping individuals sustain self-respect by recognizing themselves as worthy of trust. Nonetheless, even full-blooded trust can lack recognition respect, the respect owed to others simply in virtue of their agency. It can thus still be morally flawed, all things considered.

As society grapples with a deluge of information, the role of experts in guiding public opinion and decision-making becomes both a conceptual and a normative puzzle. This paper examines the value of epistemic trust in the context of laypersons forming beliefs based on expert testimony. To do so, I first differentiate epistemic trust in experts from mere reliance. I contend that trust involves normative expectations and preemptive reasons in a way that mere reliance doesn’t. I then apply this conceptualization to the relationship between laypersons and experts who work within public institutions, whom I term ‘public experts.’ I suggest that laypersons are often warranted in forming the normative expectations central to trust towards such experts because of their social role. The central contribution of the paper is to argue that well-placed epistemic trust in public experts is more valuable than mere reliance because it offers greater resistance to sophisticated disinformation prevalent in our cognitive environments. This is because epistemic trust gives the trustor a reason to have strongly held beliefs that aren’t easily swayed by deceptive first-order evidence, while reliance on other agents can only foster strong beliefs more vulnerable to such evidence.

The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong desideratum of criminal trials, advocates of the relational theory of procedural justice give us good reason to think that fairness and perceived fairness of legal procedures have a value that is independent from the outcome. According to this literature, one key aspect of fairness is trustworthiness. In this paper, I argue that using certain algorithms to assist bail decisions could increase three different aspects of judges’ trustworthiness: (1) actual trustworthiness, (2) rich trustworthiness, and (3) perceived trustworthiness.

Over the last few years, various public, private, and NGO entities have adopted a staggering number of non-binding ethical codes to guide the development of artificial intelligence. However, this seemingly failed to drive better ethical practices within AI organizations. In light of this observation, this paper aims to reevaluate the roles the ethics of AI can play to have a meaningful impact on the development and implementation of AI systems. In doing so, we challenge the notion that AI ethics should focus primarily on instilling ethical principles in practitioners within AI organizations, as well as the claim that AI ethics can only lead to ethics washing. We propose a two-pronged institutionalist approach to AI ethics, focusing on shaping organizational decision-making processes and emphasizing the necessity of binding legal regulations. First, we argue that AI ethics should give priority to institutional design over the internalization of ethical principles by individual practitioners. We then contend that legally binding rules are needed to this end, both as a motivation for organizations and to contribute to the semantic determination of high-level ethical principles. We then show that promising proposals to operationalize ethical principles require the backing of binding legal norms to be effective. We conclude by highlighting the potential of AI ethics to contribute meaningfully to legislative innovation in AI governance.

In this paper, I raise a challenge to Gideon Rosen’s defence of moral contingentism against Jamie Dreier’s moral luck argument. Dreier argues that if moral contingentism is true, acting in a morally permissible way always depends on a form of moral luck, because we could be in a descriptively identical possible world where the moral laws are different. Rosen’s response is that such a world is too remote from ours for us to count it as lucky that we are not in it. I argue that, given Rosen’s method of assessing the remoteness of possible worlds, worlds like the one Dreier describes are close enough to ours to justify his worry, and consequently that Rosen’s counterargument fails. I take this strongly counterintuitive conclusion as a reason to be optimistic that Rosen’s argument for moral contingentism can be resisted.

The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong desideratum of criminal trials, advocates of the relational theory of procedural justice give us good reason to think that fairness and perceived fairness of legal procedures have a value that is independent from the outcome. According to this literature, one key aspect of fairness is trustworthiness. In this paper, I argue that using certain algorithms to assist bail decisions could increase three diferent aspects of judges’ trustworthiness: (1) actual trustworthiness, (2) rich trustworthiness, and (3) perceived trustworthiness.