Existential Risk and Growth
Philip Trammell (Global Priorities Institute and Department of Economics, University of Oxford) and Leopold Aschenbrenner
GPI Working Paper No. 13-2024
Technologies may pose existential risks to civilization. Though accelerating technological development may increase the risk of anthropogenic existential catastrophe per period in the short run, two considerations suggest that a sector-neutral acceleration decreases the risk that such a catastrophe ever occurs. First, acceleration decreases the time spent at each technology level. Second, since a richer society is willing to sacrifice more for safety, optimal policy can yield an “existential risk Kuznets curve”; acceleration then pulls forward a future in which risk is low. Acceleration typically increases risk only given sufficiently extreme policy failures or direct contributions of acceleration to risk.
An earlier version of the paper was published as GPI Working Paper No. 6-2020, and is available here.
Other working papers
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…
Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Rethink Priorities), Jojo Lee and Victor Yaneng Wang (Global Priorities Institute, University of Oxford)
The surrogate index method allows policymakers to estimate long-run treatment effects before long-run outcomes are observable. We meta-analyse this approach over nine long-run RCTs in development economics, comparing surrogate estimates to estimates from actual long-run RCT outcomes. We introduce the M-lasso algorithm for constructing the surrogate approach’s first-stage predictive model and compare its performance with other surrogate estimation methods. …
In search of a biological crux for AI consciousness – Bradford Saad (Global Priorities Institute, University of Oxford)
Whether AI systems could be conscious is often thought to turn on whether consciousness is closely linked to biology. The rough thought is that if consciousness is closely linked to biology, then AI consciousness is impossible, and if consciousness is not closely linked to biology, then AI consciousness is possible—or, at any rate, it’s more likely to be possible. A clearer specification of the kind of link between consciousness and biology that is crucial for the possibility of AI consciousness would help organize inquiry into…