Calibration dilemmas in the ethics of distribution
Jacob M. Nebel (University of Southern California) and H. Orri Stefánsson (Stockholm University and Swedish Collegium for Advanced Study)
GPI Working Paper No. 10-2021, published in Economics & Philosophy
This paper was the basis for the Parfit Memorial Lecture 2021.
The recording of the Parfit Memorial Lecture is now available to view here.
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…
The Conservation Multiplier – Bård Harstad (University of Oslo)
Every government that controls an exhaustible resource must decide whether to exploit it or to conserve and thereby let the subsequent government decide whether to exploit or conserve. This paper develops a positive theory of this situation and shows when a small change in parameter values has a multiplier effect on exploitation. The multiplier strengthens the influence of a lobby paying for exploitation, and of a donor compensating for conservation. …
Towards shutdownable agents via stochastic choice – Elliott Thornley (Global Priorities Institute, University of Oxford), Alexander Roman (New College of Florida), Christos Ziakas (Independent), Leyton Ho (Brown University), and Louis Thomson (University of Oxford)
Some worry that advanced artificial agents may resist being shut down. The Incomplete Preferences Proposal (IPP) is an idea for ensuring that does not happen. A key part of the IPP is using a novel ‘Discounted Reward for Same-Length Trajectories (DReST)’ reward function to train agents to (1) pursue goals effectively conditional on each trajectory-length (be ‘USEFUL’), and (2) choose stochastically between different trajectory-lengths (be ‘NEUTRAL’ about trajectory-lengths). In this paper, we propose…