'The only ethical argument for positive 𝛿'?Â
Andreas Mogensen (Global Priorities Institute, Oxford University)
GPI Working Paper No. 5-2019, published in Philosophical Studies
I consider whether a positive rate of pure intergenerational time preference is justifiable in terms of agent-relative moral reasons relating to partiality between generations, an idea I call ​discounting for kinship​. I respond to Parfit's objections to discounting for kinship, but then highlight a number of apparent limitations of this approach. I show that these limitations largely fall away when we reflect on social discounting in the context of decisions that concern the global community as a whole.
Other working papers
Evolutionary debunking and value alignment – Michael T. Dale (Hampden-Sydney College) and Bradford Saad (Global Priorities Institute, University of Oxford)
This paper examines the bearing of evolutionary debunking arguments—which use the evolutionary origins of values to challenge their epistemic credentials—on the alignment problem, i.e. the problem of ensuring that highly capable AI systems are properly aligned with values. Since evolutionary debunking arguments are among the best empirically-motivated arguments that recommend changes in values, it is unsurprising that they are relevant to the alignment problem. However, how evolutionary debunking arguments…
Simulation expectation – Teruji Thomas (Global Priorities Institute, University of Oxford)
I present a new argument for the claim that I’m much more likely to be a person living in a computer simulation than a person living in the ground-level of reality. I consider whether this argument can be blocked by an externalist view of what my evidence supports, and I urge caution against the easy assumption that actually finding lots of simulations would increase the odds that I myself am in one.
The Shutdown Problem: An AI Engineering Puzzle for Decision Theorists – Elliott Thornley (Global Priorities Institute, University of Oxford)
I explain and motivate the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems suggest that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. I end by noting that…