Doomsday and objective chance
Teruji Thomas (Global Priorities Institute, Oxford University)
GPI Working Paper No. 8-2021
Lewis’s Principal Principle says that one should usually align one’s credences with the known chances. In this paper I develop a version of the Principal Principle that deals well with some exceptional cases related to the distinction between metaphysical and epistemic modality. I explain how this principle gives a unified account of the Sleeping Beauty problem and chance-based principles of anthropic reasoning. In doing so, I defuse the Doomsday Argument that the end of the world is likely to be nigh.
Other working papers
Against Willing Servitude: Autonomy in the Ethics of Advanced Artificial Intelligence – Adam Bales (Global Priorities Institute, University of Oxford)
Some people believe that advanced artificial intelligence systems (AIs) might, in the future, come to have moral status. Further, humans might be tempted to design such AIs that they serve us, carrying out tasks that make our lives better. This raises the question of whether designing AIs with moral status to be willing servants would problematically violate their autonomy. In this paper, I argue that it would in fact do so.
Longtermist political philosophy: An agenda for future research – Jacob Barrett (Global Priorities Institute, University of Oxford) and Andreas T. Schmidt (University of Groningen)
We set out longtermist political philosophy as a research field. First, we argue that the standard case for longtermism is more robust when applied to institutions than to individual action. This motivates “institutional longtermism”: when building or shaping institutions, positively affecting the value of the long-term future is a key moral priority. Second, we briefly distinguish approaches to pursuing longtermist institutional reform along two dimensions: such approaches may be more targeted or more broad, and more urgent or more patient.
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…