Harry R. Lloyd

Many philosophers have recently defended the Maximise Expected Choiceworthiness (MEC) approach to moral uncertainty. Perhaps the most important problem for MEC is the problem of intertheoretic choiceworthiness unit comparisons; and one extant response to this problem is a technique called ‘variance normalization.’ Although there has been some short, scattered commentary on variance normalization in the philosophical literature, nobody has yet offered a detailed critical discussion of this proposal. This paper fills that lacuna, arguing that there are serious problems which would need to be addressed before variance normalization could be invoked to rescue MEC from scepticism about intertheoretic comparisons.

In this paper, I propose and defend a new criterion for appropriate choice under conditions of moral uncertainty. According to this new criterion, it is appropriate to follow some moral theory T under conditions of moral uncertainty iff T maximises expected truthlikeness. This approach to moral uncertainty has several important advantages: (1) it does not require any intertheoretic choiceworthiness comparisons; (2) it respects agent-centred prerogatives and supererogation; (3) it does not suffer from any ‘individuation problems’; and (4) it has a prima facie plausible motivating idea.

New AI technologies have the potential to cause unintended harms in diverse domains including warfare, judicial sentencing, medicine and governance. One strategy for realising the benefits of AI whilst avoiding its potential dangers is to ensure that new AIs are properly ‘aligned’ with some form of ‘alignment target.’ One danger of this strategy is that–dependent on the alignment target chosen–our AIs might optimise for objectives that reflect the values only of a certain subset of society, and that do not take into account alternative views about what constitutes desirable and safe behaviour for AI agents. In response to this problem, several AI ethicists have suggested alignment targets that are designed to be sensitive to widespread normative disagreement amongst the relevant stakeholders. Authors inspired by voting theory have suggested that AIs should be aligned with the verdicts of actual or simulated ‘moral parliaments’ whose members represent the normative views of the relevant stakeholders. Other authors inspired by decision theory and the philosophical literature on moral uncertainty have suggested that AIs should maximise socially expected choiceworthiness. In this paper, I argue that both of these proposals face several important problems. In particular, they fail to select attractive ‘compromise options’ in cases where such options are available. I go on to propose and defend an alternative, bargaining-theoretic alignment target, which avoids the problems associated with the voting- and decision-theoretic approaches.

One of the disadvantages of redistributive taxation is that it reduces people’s financial incentives to increase national wealth and benefit others by engaging in productive activities. It is natural to suppose that the severity of this disadvantage will be proportional to the socially prevailing level of human selfishness. Thus several advocates of redistribution (G.A. Cohen, Ha-Joon Chang among others) have argued that this disadvantage of redistribution need not be as severe as critics often suggest, because human beings need not be so selfish. My aim in this paper is to argue that, even in a society entirely composed of unselfish and impartially beneficent individuals, redistributive taxation would still discourage activities that contribute to national wealth, because differing individuals have different views about what counts as benefiting themselves and others. I also relate my discussion to G.A. Cohen’s influential ‘camping trip’ argument for socialism (from Why Not Socialism?).

Moral latitude is only ever a matter of coincidence on the most popular decision procedure in the literature on moral uncertainty. In all possible choice situations other than those in which two or more options happen to be tied for maximal expected choiceworthiness, Maximize Expected Choiceworthiness implies that only one possible option is uniquely appropriate. A better theory of appropriateness would be more sensitive to the decision maker’s credence in theories that endorse agent-centred prerogatives. In this paper, we will develop and defend a modified version of this view that allows for agent-centred prerogatives and supererogation as part of its verdicts about appropriateness.

As well as disagreeing about how much one should donate to charity, moral theories also disagree about where one should donate. In light of this disagreement, how should the morally uncertain philanthropist allocate her donations? In many cases, one intuitively attractive option is for the philanthropist to split her donations across all of the charities that are recommended by moral views in which she has positive credence, with each charity’s share being proportional to her credence in the moral theories that recommend that particular charity. Despite the fact that something like this approach is already being used by real-world philanthropists to distribute billions of dollars of donations, it is not supported by any of the approaches to moral uncertainty that have been proposed thus-far in the philosophical literature. In this paper, we will develop a bargaining-based approach to moral uncertainty that honors the proportionality intuition in favor of splitting one’s donations. We also show how this bargaining-based approach has several further advantages over the best alternative proposals.

We discuss potential biorisks from large language models (LLMs). AI assistants based on LLMs such as ChatGPT have been shown to significantly reduce barriers to entry for actors wishing to synthesize dangerous, potentially novel pathogens and chemical weapons. The harms from deploying such bioagents could be further magnified by AI-assisted misinformation. We endorse several policy responses to these dangers, including prerelease evaluations of biomedical AIs by subject-matter experts, enhanced surveillance and lab screening procedures, restrictions on AI training data, and access controls on biomedical AI. We conclude with a suggestion about future research directions in bioethics.

Philosophical discussions of gentrification have tended to focus on residential displacement. However, the prevalence of residential displacement is fiercely contested, with many urban geographers regarding it as quite uncommon. This lends some urgency to the underexplored question of how one should evaluate other forms of gentrification. In this paper, I argue that one of the most important harms suffered by victims of displacement gentrification is loss of access to the goods conferred by membership in a thriving local community. Leveraging the social scientific literature, I go on to argue that non-displacement gentrification also often damages local communities. One can hence extend existing philosophical critiques of displacement gentrification to argue that non-displacement gentrification likewise poses a threat to relational equality, and often violates certain basic occupancy rights. Focusing on the value that inheres in thriving local communities also suggests some new possibilities for critiquing gentrification. For instance, existing occupancy rights critiques focus on incumbent land users’ interests in stability. However, one can also argue in a Lockean mode that incumbent land users’ occupancy rights are at least partially grounded in their community having laboured together to create objects of value. An extension of Michael Walzer’s theory of justice to incorporate community goods as a separate ‘sphere’ might also have widespread appeal. Taken together, these arguments constitute a sustained and theoretically ecumenical case for the pro tanto moral objectionability of gentrification.

This paper defends the claim that mere temporal proximity always and without exception strengthens certain moral duties, including the duty to save – call this view Robust Temporalism. Although almost all other moral philosophers dismiss Robust Temporalism out of hand, I argue that it is prima facie intuitively plausible, and that it is analogous to a view about special obligations that many philosophers already accept. I also defend Robust Temporalism against several common objections, and I highlight its relevance to a number of practical policy debates, including longtermism. My conclusion is that Robust Temporalism is a moral live option, that deserves to be taken much more seriously in the future.

Shelly Kagan has recently defended the view that it is morally worse for a human being to suffer some harm than it is for a lower animal (such as a dog or a cow) to suffer a harm that is equally severe (ceteris paribus). In this paper, I argue that this view receives rather less support from our intuitions than one might at first suppose. According to Kagan, moreover, an individual’s moral status depends partly upon her ‘modal capacities.’ In this paper, I argue that the most natural strategy for justifying Kagan’s theory faces some important challenges. More generally, I argue that philosophers who wish to defend the view that human beings have a higher moral status than that of the lower animals face a dilemma. Either their theory of moral status will imply (unacceptably) that some severely cognitively impaired human beings have a significantly lower moral status than that of typical human beings, or these philosophers will be forced to ground moral status in a set of properties so far removed from a subject’s actual capacities that it will become difficult to see why these kinds of properties should have such moral importance.