Algorithmic discrimination has rapidly become a topic of intense public and academic interest. This article explores three issues raised by algorithmic discrimination: 1) the distinction between direct and indirect discrimination, 2) the notion of disadvantageous treatment, and 3) the moral badness of discriminatory automated decision-making. It argues that some conventional distinctions between direct and indirect discrimination appear not to apply to algorithmic discrimination, that algorithmic discrimination may often be discrimination between groups, as opposed to against groups, and that it is (...) not necessarily the case that morally bad algorithmic discrimination gives us reason to not use automated decision-making. For each of the three issues, the article explores implications for algorithmic discrimination, suggests some alternative answers, and clarifies how we may want to think of discrimination more broadly in light of lessons drawn from the context of algorithmic discrimination. (shrink)

Credentialism refers to the practice of hiring or promoting applicants on the basis of their educational qualifications. In this paper, we argue that this can amount to wrongful discrimination against the less qualified. A standard way to defend credentialism appeals to the fact that it minimizes the costs of production. We argue that this argument has unacceptable implications in some cases involving disability- and gender-based discrimination. We claim that, once we appropriately revise this argument, credentialism is revealed to be similarly (...) wrongfully discriminatory. We then consider two objections and draw some preliminary lessons for policymaking. (shrink)

The article explores one prominent account of what makes discrimination morally bad (when it is) – the disrespect-based account. The article first reviews and clarifies the account, arguing that it is most charitably understood as the claim that discrimination is morally bad when the discriminator gives lower weight to reasons grounded in the moral status of the discriminatee(s) in her decision-making. It then presents three challenges to the account, and reviews a recent argument in defense of it. The first challenge (...) is the fact that intuitions that might support the disrespect-based account can also be explained by reference to the fact that disrespect reflects poorly on the moral character of the discriminator. The second challenge is that there are cases where disrespectful discrimination is not intuitively worse than non-disrespectful discrimination. The third challenge is that the disrespect-based account has difficulties explaining our intuitions about cases of “doing right for the wrong reasons”. Finally, pace a recent argument in its defense, cases of harmless and apparently morally bad discrimination are plausibly best explained by other factors than disrespect. In the light of this analysis, the article concludes that the disrespect-based account should be abandoned. (shrink)

Should the input data of artificial intelligence (AI) systems include factors such as race or sex when these factors may be indicative of morally significant facts? More importantly, is it wrong to rely on the output of AI tools whose input includes factors such as race or sex? And is it wrong to rely on the output of AI systems when it is correlated with factors such as race or sex (whether or not its input includes such factors)? The answers (...) to these questions are controversial. In this paper, I argue for the following claims. First, since factors such as race or sex are not morally significant in themselves, including such factors in the input data, or relying on output that includes such factors or is correlated with them, is neither objectionable (for example, unfair) nor commendable in itself. Second, sometimes (but not always) there are derivative reasons against such actions due to the relationship between factors such as race or sex and facts that are morally significant (ultimately) in themselves. Finally, even if there are such derivative reasons, they are not necessarily decisive since there are sometimes also countervailing reasons. Accordingly, the moral status of the above actions is contingent. (shrink)

This article addresses the moral and legal difficulties sport governing bodies encounter as human rights promoters. The case presented here is the 2023 decision by the International Olympic Committee (IOC) to allow athletes from Russia and Belarus to compete in international sport under neutral colours, after recommending complete exclusion a year before due to the Russian invasion of Ukraine. While IOC’s change of mind was influenced by UN experts on human rights, claiming that the ban discriminated against Russian athletes, the (...) same experts fail to take into account competing human rights elements that could favour the ban. To that end, this article discusses the complexities of prioritizing human rights in an Olympic context and, deriving from that, demonstrates the existence of moral and legal support for upholding the exclusion of Russia. Finally, the analysis of how to prioritize morally and legally between competing human rights offers deliberative material to other sport governing bodies which could be used to carve out preventive measures prior to their next encounter with a similar situation. (shrink)