The freedom of future people
Andreas T Schmidt (University of Groningen)
GPI Working Paper No. 10-2023
What happens to liberal political philosophy, if we consider not only the freedom of present but also future people? In this article, I explore the case for long-term liberalism: freedom should be a central goal, and we should often be particularly concerned with effects on long-term future distributions of freedom. I provide three arguments. First, liberals should be long-term liberals: liberal arguments to value freedom give us reason to be (particularly) concerned with future freedom, including freedom in the far future. Second, longtermists should be liberals, particularly under conditions of empirical and moral uncertainty. Third, long-term liberalism plausibly justifies some restrictions on the freedom of existing people to secure the freedom of future people, for example when mitigating climate change. At the same time, it likely avoids excessive trade-offs: for both empirical and philosophical reasons, long-term and near-term freedom show significant convergence. Throughout I also highlight important practical implications, for example on longtermist institutional action, climate change, human extinction, and global catastrophic risks.
Other working papers
Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Rethink Priorities), Jojo Lee and Victor Yaneng Wang (Global Priorities Institute, University of Oxford)
The surrogate index method allows policymakers to estimate long-run treatment effects before long-run outcomes are observable. We meta-analyse this approach over nine long-run RCTs in development economics, comparing surrogate estimates to estimates from actual long-run RCT outcomes. We introduce the M-lasso algorithm for constructing the surrogate approach’s first-stage predictive model and compare its performance with other surrogate estimation methods. …
Imperfect Recall and AI Delegation – Eric Olav Chen (Global Priorities Institute, University of Oxford), Alexis Ghersengorin (Global Priorities Institute, University of Oxford) and Sami Petersen (Department of Economics, University of Oxford)
A principal wants to deploy an artificial intelligence (AI) system to perform some task. But the AI may be misaligned and aim to pursue a conflicting objective. The principal cannot restrict its options or deliver punishments. Instead, the principal is endowed with the ability to impose imperfect recall on the agent. The principal can then simulate the task and obscure whether it is real or part of a test. This allows the principal to screen misaligned AIs during testing and discipline their behaviour in deployment. By increasing the…
Economic inequality and the long-term future – Andreas T. Schmidt (University of Groningen) and Daan Juijn (CE Delft)
Why, if at all, should we object to economic inequality? Some central arguments – the argument from decreasing marginal utility for example – invoke instrumental reasons and object to inequality because of its effects…