Simulation expectation
Teruji Thomas (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 16-2021, published at Erkenntnis
I present a new argument that we are much more likely to be living in a computer simulation than in the ground-level of reality. (Similar arguments can be marshalled for the view that we are more likely to be Boltzmann brains than ordinary people, but I focus on the case of simulations.) I explain how this argument overcomes some objections to Bostrom’s classic argument for the same conclusion. I also consider to what extent the argument depends upon an internalist conception of evidence, and I refute the common line of thought that finding many simulations being run—or running them ourselves—must increase the odds that we are in a simulation.
Other working papers
Is In-kind Kinder than Cash? The Impact of Money vs Food Aid on Social Emotions and Aid Take-up – Samantha Kassirer, Ata Jami, & Maryam Kouchaki (Northwestern University)
There has been widespread endorsement from the academic and philanthropic communities on the new model of giving cash to those in need. Yet the recipient’s perspective has mostly been ignored. The present research explores how food-insecure individuals feel and respond when offered either monetary or food aid from a charity. Our results reveal that individuals are less likely to accept money than food aid from charity because receiving money feels relatively more shameful and relatively less socially positive. Since many…
Prediction: The long and the short of it – Antony Millner (University of California, Santa Barbara) and Daniel Heyen (ETH Zurich)
Commentators often lament forecasters’ inability to provide precise predictions of the long-run behaviour of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. …
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. …