Consequentialism, Cluelessness, Clumsiness, and Counterfactuals

Alan Hájek (Australian National University)

GPI Working Paper No. 4-2024

According to a standard statement of objective consequentialism, a morally right action is one that has the best consequences. More generally, given a choice between two actions, one is morally better than the other just in case the consequences of the former action are better than those of the latter. (These are not just the immediate consequences of the actions, but the long-term consequences, perhaps until the end of history.) This account glides easily off the tongue—so easily that one may not notice that on one understanding it makes no sense, and on another understanding, it has a startling metaphysical presupposition concerning counterfactuals. I will bring this presupposition into relief. Objective consequentialism has faced various objections, including the problem of “cluelessness”: we have no idea what most of the consequences of our actions will be. I think that objective consequentialism has a far worse problem: its very foundations are highly dubious. Even granting those foundations, a worse problem than cluelessness remains, which I call “clumsiness”. Moreover, I think that these problems quickly generalise to a number of other moral theories. But the points are most easily made for objective consequentialism, so I will focus largely on it.

Other working papers

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I explore the implications of time preference heterogeneity for the private funding of public goods. The assumption that players use a common discount rate is knife-edge: relaxing it yields substantially different equilibria, for two reasons. First, time preference heterogeneity motivates intertemporal polarization, analogous to the polarization seen in a static public good game. In the simplest settings, more patient players spend nothing early in time and less patient players spending nothing later. Second…

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A principal wants to deploy an artificial intelligence (AI) system to perform some task. But the AI may be misaligned and aim to pursue a conflicting objective. The principal cannot restrict its options or deliver punishments. Instead, the principal is endowed with the ability to impose imperfect recall on the agent. The principal can then simulate the task and obscure whether it is real or part of a test. This allows the principal to screen misaligned AIs during testing and discipline their behaviour in deployment. By increasing the…