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
The Hinge of History Hypothesis: Reply to MacAskill – Andreas Mogensen (Global Priorities Institute, University of Oxford)
Some believe that the current era is uniquely important with respect to how well the rest of human history goes. Following Parfit, call this the Hinge of History Hypothesis. Recently, MacAskill has argued that our era is actually very unlikely to be especially influential in the way asserted by the Hinge of History Hypothesis. I respond to MacAskill, pointing to important unresolved ambiguities in his proposed definition of what it means for a time to be influential and criticizing the two arguments…
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…
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…