The case for strong longtermism
Hilary Greaves and William MacAskill (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 5-2021
A striking fact about the history of civilisation is just how early we are in it. There are 5000 years of recorded history behind us, but how many years are still to come? If we merely last as long as the typical mammalian species, we still have over 200,000 years to go (Barnosky et al. 2011); there could be a further one billion years until the Earth is no longer habitable for humans (Wolf and Toon 2015); and trillions of years until the last conventional star formations (Adams and Laughlin 1999:34). Even on the most conservative of these timelines, we have progressed through a tiny fraction of history. If humanity’s saga were a novel, we would be on the very first page.
Other working papers
The paralysis argument – William MacAskill, Andreas Mogensen (Global Priorities Institute, Oxford University)
Given plausible assumptions about the long-run impact of our everyday actions, we show that standard non-consequentialist constraints on doing harm entail that we should try to do as little as possible in our lives. We call this the Paralysis Argument. After laying out the argument, we consider and respond to…
A Fission Problem for Person-Affecting Views – Elliott Thornley (Global Priorities Institute, University of Oxford)
On person-affecting views in population ethics, the moral import of a person’s welfare depends on that person’s temporal or modal status. These views typically imply that – all else equal – we’re never required to create extra people, or to act in ways that increase the probability of extra people coming into existence. In this paper, I use Parfit-style fission cases to construct a dilemma for person-affecting views: either they forfeit their seeming-advantages and face fission analogues…
Will AI Avoid Exploitation? – Adam Bales (Global Priorities Institute, University of Oxford)
A simple argument suggests that we can fruitfully model advanced AI systems using expected utility theory. According to this argument, an agent will need to act as if maximising expected utility if they’re to avoid exploitation. Insofar as we should expect advanced AI to avoid exploitation, it follows that we should expected advanced AI to act as if maximising expected utility. I spell out this argument more carefully and demonstrate that it fails, but show that the manner of its failure is instructive…