How to neglect the long term

Hayden Wilkinson (Global Priorities Institute, University of Oxford)

GPI Working Paper No. 11-2023

Consider longtermism: the view that, at least in some of the most important decisions facing agents today, which options are morally best is determined by which are best for the long-term future. Various critics have argued that longtermism is false—indeed, that it is obviously false, and that we can reject it on normative grounds without close consideration of certain descriptive facts. In effect, it is argued, longtermism would be false even if real-world agents had promising means of benefiting vast numbers of future people. In this paper, I develop a series of troubling impossibility results for those who wish to reject longtermism so robustly. It turns out that, to do so, we must incur severe theoretical costs. I suspect that these costs are greater than simply accepting longtermism. If so, the more promising route to denying longtermism would be by appeal to descriptive facts.

Other working papers

Maximal cluelessness – Andreas Mogensen (Global Priorities Institute, Oxford University)

I argue that many of the priority rankings that have been proposed by effective altruists seem to be in tension with apparently reasonable assumptions about the rational pursuit of our aims in the face of uncertainty. The particular issue on which I focus arises from recognition of the overwhelming importance…

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…

Crying wolf: Warning about societal risks can be reputationally risky – Lucius Caviola (Global Priorities Institute, University of Oxford) et al.

Society relies on expert warnings about large-scale risks like pandemics and natural disasters. Across ten studies (N = 5,342), we demonstrate people’s reluctance to warn about unlikely but large-scale risks because they are concerned about being blamed for being wrong. In particular, warners anticipate that if the risk doesn’t occur, they will be perceived as overly alarmist and responsible for wasting societal resources. This phenomenon appears in the context of natural, technological, and financial risks…