The Hinge of History Hypothesis: Reply to MacAskill
Andreas Mogensen (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 9 - 2022, published in Analysis
Some believe that the current era is uniquely important with respect to how well the rest of human history goes. Following Parfit, call this the Hinge of History Hypothesis. Recently, MacAskill has argued that our era is actually very unlikely to be especially influential in the way asserted by the Hinge of History Hypothesis. I respond to MacAskill, pointing to important unresolved ambiguities in his proposed definition of what it means for a time to be influential and criticizing the two arguments used to cast doubt on the claim that the current era is a uniquely important moment in human history.
Other working papers
Measuring AI-Driven Risk with Stock Prices – Susana Campos-Martins (Global Priorities Institute, University of Oxford)
We propose an empirical approach to identify and measure AI-driven shocks based on the co-movements of relevant financial asset prices. For that purpose, we first calculate the common volatility of the share prices of major US AI-relevant companies. Then we isolate the events that shake this industry only from those that shake all sectors of economic activity at the same time. For the sample analysed, AI shocks are identified when there are announcements about (mergers and) acquisitions in the AI industry, launching of…
Against the singularity hypothesis – David Thorstad (Global Priorities Institute, University of Oxford)
The singularity hypothesis is a radical hypothesis about the future of artificial intelligence on which self-improving artificial agents will quickly become orders of magnitude more intelligent than the average human. Despite the ambitiousness of its claims, the singularity hypothesis has been defended at length by leading philosophers and artificial intelligence researchers. In this paper, I argue that the singularity hypothesis rests on scientifically implausible growth assumptions. …
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…