# Shutdownable Agents through POST-Agency

arXiv: https://arxiv.org/abs/2505.20203 · HTML: https://mlsanity.com/paper/2505.20203/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 May 2025.

## Built on by (most cited first, 2 of 2)

- [AI Alignment Strategies from a Risk Perspective: Independent Safety Mechanisms or Shared Failures?](https://mlsanity.com/paper/2510.11235/) (2025)
- [Towards Shutdownable Agents: Generalizing Stochastic Choice in RL Agents and LLMs](https://mlsanity.com/paper/2604.17502/) (2026)

## Abstract (arXiv)

Many fear that future artificial agents will resist shutdown. I present an idea - the POST-Agents Proposal - for ensuring that doesn't happen. I propose that we train agents to satisfy Preferences Only Between Same-Length Trajectories (POST). I then prove that POST - together with other conditions - implies Neutrality+: the agent maximizes expected utility, ignoring the probability distribution over trajectory-lengths. I argue that Neutrality+ keeps agents shutdownable and allows them to be useful.