How many lives does the future hold?
Toby Newberry (Future of Humanity Institute, University of Oxford)
GPI Technical Report No. T2-2021
The total number of people who have ever lived, across the entire human past, has been estimated at around 100 billion.2 The total number of people who will ever live, across the entire human future, is unknown - but not immune to the tools of rational inquiry. This report estimates the expected size of the future, as measured in units of ‘human-life-equivalents’ (henceforth: ‘lives’). The task is a daunting one, and the aim here is not to be the final word on this subject. Instead, this report aspires to two more modest aims...
Other working papers
Time discounting, consistency and special obligations: a defence of Robust Temporalism – Harry R. Lloyd (Yale University)
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…
Are we living at the hinge of history? – William MacAskill (Global Priorities Institute, Oxford University)
In the final pages of On What Matters, Volume II, Derek Parfit comments: ‘We live during the hinge of history… If we act wisely in the next few centuries, humanity will survive its most dangerous and decisive period… What now matters most is that we avoid ending human history.’ This passage echoes Parfit’s comment, in Reasons and Persons, that ‘the next few centuries will be the most important in human history’. …
Exceeding expectations: stochastic dominance as a general decision theory – Christian Tarsney (Global Priorities Institute, Oxford University)
The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk (like Pascal’s Mugging), and intolerably paradoxical in cases like the St. Petersburg and Pasadena games. In this paper I show that, under certain conditions, stochastic dominance reasoning can capture most of the plausible implications of expectational reasoning while avoiding most of its pitfalls…