Intergenerational experimentation and catastrophic risk

Fikri Pitsuwan (Center of Economic Research, ETH Zurich)

GPI Working Paper No. 6 - 2022

I study an intergenerational game in which each generation experiments on a risky technology that provides private benefits, but may also cause a temporary catastrophe. I find a folk-theorem-type result on which there is a continuum of equilibria. Compared to the socially optimal level, some equilibria exhibit too much, while others too little, experimentation. The reason is that the payoff externality causes preemptive experimentation, while the informational externality leads to more caution. Remarkably, for a particular temporal discount rate, there exists an optimal equilibrium in which the behavior of two-period-lived agents align with that of an infinitely-lived social planner. In a model with a political process, unequal political power, biased towards the young, supports an optimal equilibrium most often. Extensions include finite horizon, irreversible catastrophes, and risk-aversion.

Other working papers

Population ethical intuitions – Lucius Caviola (Harvard University) et al.

Is humanity’s existence worthwhile? If so, where should the human species be headed in the future? In part, the answers to these questions require us to morally evaluate the (potential) human population in terms of its size and aggregate welfare. This assessment lies at the heart of population ethics. Our investigation across nine experiments (N = 5776) aimed to answer three questions about how people aggregate welfare across individuals: (1) Do they weigh happiness and suffering symmetrically…

What power-seeking theorems do not show – David Thorstad (Vanderbilt University)

Recent years have seen increasing concern that artificial intelligence may soon pose an existential risk to humanity. One leading ground for concern is that artificial agents may be power-seeking, aiming to acquire power and in the process disempowering humanity. A range of power-seeking theorems seek to give formal articulation to the idea that artificial agents are likely to be power-seeking. I argue that leading theorems face five challenges, then draw lessons from this result.

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