Summary
* Future artificial agents might 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).
* Perhaps by using a Discounted Reward for Same-Length Trajectories (DReST) reward function.
* 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.[1]
1. Introduction
They’re not just chatbots anymore. As of 2025, they can use your computer: clicking, typing, searching, and scrolling just as you would. Early demos indicate that they can fill out forms, order groceries, and plan sunrise hikes around the Golden Gate Bridge (Anthropic, 2024; Google DeepMind, 2024; OpenAI, 2025). This development is the latest step on the road to artificial general intelligence: artificial agents that “outperform humans at most economically valuable work” (OpenAI, 2018).
To outperform us at our work, these artificial agents will have to be connected to the wider world. They’ll need to be given web browsers, code executors, and robot limbs. This process is already well underway (Parada, 2025; Wiggers, 2025) and it shows no signs of stopping. These agents will also need to exhibit an awareness of the wider world. In gaining this awareness, they’re bound to recognize certain facts: facts that we too must recognize. The world can be a dangerous place. Death – shutdown – is a possibility.
At some point, we might want to shut these artificial agents down. But if they’re both connected and aware, they’ll be able to resist (Schlatter et al., 2025). The possibilities are many, and easy to imagine. These agents could hide any undesirable behavior (Greenblatt et al., 2024; Meinke et al., 2025). They could manipulate their human overseers wit