Many real-world agents recognise that they impose harms by choosing to emit carbon, e.g., by flying. Yet many do so anyway, and then attempt to make things right by offsetting those harms. Such offsetters typically believe that, by offsetting, they change the deontic status of their behaviour, making an otherwise impermissible action permissible. Do they succeed in practice? Some philosophers have argued that they do, since their offsets appear to reverse the adverse effects of their emissions. But we show that (...) they do not. In practice, standard carbon offsetting does not reverse the harms of the original action, nor does it even benefit the same group as was harmed. Standard moral theories hence deny that such offsetting succeeds. Indeed, we show that any moral theory that allows offsetting in this setting faces a dilemma between allowing any wrong to be offset, no matter how grievous, and recognising an implausibly sharp discontinuity between offsettable actions and non-offsettable actions. The most plausible response is to accept that carbon offsetting fails to right our climate wrongs. (shrink)

ABSTRACT Offsetting is a very ineffective way to do good. Offsetting your lifetime emissions may increase aggregated life expectancy by at most seven years, while giving the amount it costs to offset your lifetime emissions to a malaria charity saves in expectation the life of at least one child. Is there any moral reason to offset rather than giving to some charity that does good so much more effectively? There might be such a reason if your offsetting compensated or somehow (...) benefitted the victims of your emission, since that could mean that you would satisfy the duty not to harm others by emitting and offsetting. But that is typically not true. If your emission harms some person and your offsetting benefits some person, then these are most likely different people. Hence, I conclude, we have a stronger reason to give to effective charities than we have to offset our emissions. (shrink)

Our universe is both chaotic and (most likely) infinite in space and time. But it is within this setting that we must make moral decisions. This presents problems. The first: due to our universe's chaotic nature, our actions often have long-lasting, unpredictable effects; and this means we typically cannot say which of two actions will turn out best in the long run. The second problem: due to the universe's infinite dimensions, and infinite population therein, we cannot compare outcomes by simply (...) adding up their total moral values - those totals will typically be infinite or undefined. Each of these problems poses a threat to aggregative moral theories. But, for each, we have solutions: a proposal from Greaves let us overcome the problem of chaos, and proposals from the infinite aggregation literature let us overcome the problem of infinite value. But a further problem emerges. If our universe is both chaotic and infinite, those solutions no longer work - outcomes that are infinite and differ by chaotic effects are incomparable, even by those proposals. In this paper, I show that we can overcome this further problem. But, to do so, we must accept some peculiar implications about how aggregation works. (shrink)

Autonomous systems are machines that can alter their behavior without direct human oversight or control. How ought we to program them to behave? A plausible starting point is given by the Reduction to Acts Thesis, according to which we ought to program autonomous systems to do whatever a human agent ought to do in the same circumstances. Although the Reduction to Acts Thesis is initially appealing, we argue that it is false: it is sometimes permissible to program a machine to (...) do something that it would be wrong for a human to do. We advance two main arguments for this claim. First, the way an autonomous system will behave can be known in advance. This knowledge can indirectly affect the behavior of other agents, while the same may not be true at the time the system actually executes its programming. Second, a lack of knowledge of the identities of the victims and beneficiaries can provide a justification during the programming phase that would be unavailable to an agent at the time the autonomous system executes its programming. (shrink)

Many people hold the constraint against doing harm, the view that the reason against doing harm is stronger than the reason against merely allowing harm, everything else being equal. Mogensen and MacAskill (2021) have recently argued that when considering indirect long-term consequences of our everyday behavior, the constraint against doing harm faces a problem: it has the absurd implication that we should do as little as possible in our lives. In this paper, I explore the view that, for behavior that (...) does not increase anyone’s ex ante risk of suffering harm, the reason against doing harm is not stronger than the reason against merely allowing harm, everything else being equal. I argue that this view is plausible, show how it solves the paralysis problem, and defend it against objections. (shrink)

Many people think that the moral reason against doing harm is stronger than the moral reason against allowing harm. What should these people think about doing and allowing good? I address this question by distinguishing two ways of understanding the doing/allowing distinction. The agency view implies that the moral reason for doing good is stronger than the moral reason for allowing good. The imposition view implies that the moral reason against preventing good is stronger than the moral reason against failing (...) to do good. I defend the imposition view and explore its implications for the comparative strength of harm-based and benefit-based reasons. (shrink)