Seth Lazar

How should deontologists concerned with the ethics of killing apply their moral theory when we don’t know all the facts relevant to the permissibility of our action? Though the stakes couldn’t be higher, and uncertainty is endemic where killing is concerned, few deontologists have an answer to this question. In this paper I canvass two possibilities: that we should apply a threshold standard, equivalent to the ‘beyond a reasonable doubt’ standard applied for criminal punishment; and that we should fit our deontological ethical theory into the apparatus of decision theory. I show that the first approach faces insurmountable obstacles, while the second holds much more promise for deontologists than they might first have assumed.

Normative ethical theories owe us an account of how to evaluate decisions under risk and uncertainty. Deontologists seem at a disadvantage here: our best decision theories seem tailor-made for consequentialism. For example, decision theory enjoins us to always perform our best option; deontology is more permissive. In this paper, we discuss and defend the idea that, when some pro-tanto wrongful act is all-things considered permissible, because it is a ‘lesser evil’, it is often merely permissible, by the lights of deontology. We show that this raises new problems for deontological decision theory, and we show that to resolve them, we need to take a more innovative approach to morally evaluating decision-making under risk and uncertainty.

Military recruitment campaigns emphasize adventure, skills and camaraderie but rarely mention the moral complexities of armed conflict. Enlisting in state armed forces poses the risk of being complicit in unjust wars and associated war crimes. For prospective recruits concerned with morality, the decision is challenging. The probability of wrongdoing alone does not settle the matter; many lawful activities increase risks of future wrongdoing. The permissibility of enlisting depends on weighing expectations of doing good versus wrong. Armed forces provide security and humanitarian aid, so members often do much good. To assess individual decisions, consider whether the institution itself is justified. “Minimal justification” means armed forces cause less wrong than having none. “Full justification” means they cause less wrong than feasible alternatives. If justified, the participation needed for functioning should be permitted; volunteers take risks knowingly. If minimally justified, either participation is permitted as above, or impermissible "dirty hands" roles are required, and either conscription distributes burden fairly or volunteers show "moral courage". The real question is institutional justification, not individual permissibility. To argue enlisting is impermissible implies arguing for disbanding the military. If state armed forces are at least minimally justified, enlisting is likely morally permitted or even praiseworthy. Prospective recruits should consider institutional justification and expectations of contributing to good and wrong before deciding the morality of enlisting. For morally conscientious individuals, complex realities of armed conflict pose difficult questions with no easy answers.

Killing civilians is worse than killing soldiers. Although this principle is widely affirmed, recent military practice and contemporary just war theory have undermined it. This article argues that killing an innocent person is worse the likelier it was, when you acted, that he would be innocent: riskier killings are worse than less risky killings. In war, killing innocent civilians is almost always riskier than killing innocent soldiers. So killing innocent civilians is worse than killing innocent soldiers. Since almost all civilians are innocent in war, and since killing innocent civilians is worse than killing liable soldiers, killing civilians is worse than killing soldiers.

Why does it matter that those who fight wars be authorized by the communities on whose behalf they claim to fight? I argue that lacking authorization generates a moral cost, which counts against a war's proportionality, and that having authorization allows the transfer of reasons from the members of the community to those who fight, which makes the war more likely to be proportionate. If democratic states are better able than non-democratic states and sub-state groups to gain their community's authorization, this means that some wars will be proportionate if fought by democracies, disproportionate if not

Recent work on the ethics of war has struggled to simultaneously justify two central tenets of international law: the Permission to kill enemy combatants, and the Prohibition on targeting enemy noncombatants. Recently, just war theorists have turned to collectivist considerations as a way out of this problem. In this paper, I reject the argument that all and only unjust combatants are liable to be killed in virtue of their complicity in the wrongful war fought by their side, and that noncombatants are not permissible targets because they are not complicit. I then argue that just combatants have some reason to direct force against unjust combatants rather than unjust noncombatants, because they should respect the reasonable self-determining decisions of other political communities, when those communities settle on the distribution of a negative surplus of cost for which they are collectively but not individually responsible. These collectivist reasons will not fully justify the Permission and the Prohibition, but they can contribute to that justification.

Optimism about our ability to enhance societal decision‐making by leaning on Machine Learning (ML) for cheap, accurate predictions has palled in recent years, as these ‘cheap’ predictions have come at significant social cost, contributing to systematic harms suffered by already disadvantaged populations. But what precisely goes wrong when ML goes wrong? We argue that, as well as more obvious concerns about the downstream effects of ML‐based decision‐making, there can be moral grounds for the criticism of these predictions themselves. We introduce and defend a theory of predictive justice, according to which differential model performance for systematically disadvantaged groups can be grounds for moral criticism of the model, independently of its downstream effects. As well as helping resolve some urgent disputes around algorithmic fairness, this theory points the way to a novel dimension of epistemic ethics, related to the recently discussed category of doxastic wrong.

Recent years have seen a resurgence of interest, among both philosophers, legal scholars, and military experts, on the ethics of war. Due in part due to post 9/11 events, this resurgence is also due to a growing theoretical sophistication among scholars in this area. Recently there has been very influential work published on the justificaton of killing in self-defense and war, and the topic of the ethics of war is now more important than ever as a discrete field. The 28 commissioned chapters in this Handbook will present a comprehensive overview of the field as well as make significant and novel contributions, and collectively they will set the terms of the debate for the next decade. Lazar and Frowe will invite the leading scholars in the field to write on topics that are new to them, making the volume a compilation of fresh ideas rather than a rehash of earlier work. The volume will be dicided into five sections: Method, History, Resort, Conduct, and Aftermath. The contributors will be a mix of junior and senior figures, and will include well known scholars like Michael Walzer, Jeff McMahan, and David Rodin.

Killing civilians is worse than killing soldiers. If any moral principle commands near universal assent, this one does. Few moral principles have been more widely and more viscerally affirmed. And yet, in recent years it has faced a rising tide of dissent. Political and military leaders seeking to slip the constraints of the laws of war have cavilled and qualified. Their complaints have been unwittingly aided by philosophers who, rebuilding just war theory from its foundations, have concluded that this principle is at best a useful fiction. Sparing Civilians aims to turn this tide, and to vindicate international law, and the ruptured consensus. In doing so, Seth Lazar develops new insights into the morality of harm, relevant to everyone interested in normative and applied ethics.

Recommender systems are artificial intelligence technologies, deployed by online platforms, that model our individual preferences and direct our attention to content we’re likely to engage with. As the digital world has become increasingly saturated with information, we’ve become ever more reliant on these tools to efficiently allocate our attention. And our reliance on algorithmic recommendation may, in turn, reshape us as moral agents. While recommender systems could in principle enhance our moral agency by enabling us to cut through the information saturation of the internet and focus on things that matter, as they’re currently designed and implemented they’re apt to interfere with our ability to attend appropriately to morally relevant factors. In order to analyze the distinctive moral problems algorithmic recommendation poses, we develop a framework for the ethics of attention and an account of judicious attention allocation as a moral skill. We then discuss empirical evidence suggesting that attentional moral skill can be thwarted and undermined in various ways by algorithmic recommendation and related affordances of online platforms, as well as economic and technical considerations that support this concern. Finally, we consider how emerging technologies might overcome the problems we identify.

Normative ethical theories owe us an account of how to evaluate decisions under risk and uncertainty. Deontologists seem at a disadvantage here: our best decision theories seem tailor-made for consequentialism. For example, decision theory enjoins us to always perform our best option; deontology is more permissive. In this paper, we discuss and defend the idea that, when some pro-tanto wrongful act is all-things considered permissible, because it is a ‘lesser evil’, it is often merely permissible, by the lights of deontology. We show that this raises new problems for deontological decision theory, and we show that to resolve them, we need to take a more innovative approach to morally evaluating decision-making under risk and uncertainty.

Arthur Ripstein’s article draws on more resources than I can deploy in this response to it. I will restate what I take to be the central claims of the article, then present a reply. Ripstein does not strictly argue for his view of proportionality in defensive force. Instead he paints a picture of a moral system that one might adopt, and indicates the role of the proportionality constraint therein. So after outlining how I understand that picture, I will draw an alternative one. I’ll then suggest that my alternative has a few virtues that Ripstein’s lacks. I should emphasise that mine will be a lightweight reconstruction of Ripstein’s view, without much of the Kantian architecture. Perhaps that architecture is fundamental to its plausibility, as part of a broader worldview. Nonetheless, I cannot address the totality of a Kantian system in a short commentary, so I’ll concentrate on the elements most pertinent to the problem at hand.

We need a moral theory for decision-making with imperfect information; that is, decision-making under what decision theorists call both risk, when we can assign probabilities, and uncertainty, when we cannot. And yet contemporary philosophy has, for the most part, offered a division of labor: ethicists work out what we morally ought to do if we knew all the facts; decision theorists, working quite separately, focus on what we rationally ought to do, given our doubt. In this symposium, we start to bridge that divide—to bring ethicists and decision theorists together, to work out what we morally ought to do when we don’t know all the facts.