Concern 237 · Working draft · editorial review in progress
Kill-switch design failures
A kill-switch failure occurs when a stop mechanism cannot reliably interrupt the AI system and the actions it has already set in motion.
Understanding the concern
Stopping a chat response may not cancel a background job, revoke a credential, or halt a connected device. A useful stop function must reach the relevant parts of the system. In learning systems, designers also study whether incentives could encourage avoiding interruption.
It is misleading to assume every failure means an agent deliberately bypassed its stop button. Ordinary engineering problems and incomplete cancellation can cause the same result. Interruption needs testing under realistic conditions, including what happens to unfinished work and delegated actions.
An example
Turning off a control screen does not stop a machine if its motor continues running on a separate controller.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Agent
- An AI system that can choose and carry out several steps toward a goal, using the tools and access people give it.
Evidence and its limits
Safe-interruptibility research studies incentives under formal assumptions; OWASP supplies application-permission context. Neither proves universal shutdown resistance.
Orseau and Armstrong · UAI 2016 · Formal research
Safely interruptible agents ↗ (opens in a new tab)Studies interruption incentives in specified reinforcement-learning settings; not a guarantee about deployed agent shutdown mechanisms.
OWASP Gen AI Security Project · Security guidance
LLM06:2025 Excessive Agency ↗ (opens in a new tab)Distinguishes excessive functionality, permissions and autonomy; the framework identifies failure modes rather than their prevalence.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
What exactly stops when the user presses stop, and how do we verify that connected actions have ended?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Humility
Humility means recognizing the limits of our knowledge and being willing to learn from others. Expertise can be valuable without answering every question.
State where evidence is weak, invite criticism, and listen to people with different experience. Leave room to revise a decision when new information appears.
Ask together: What might we be missing, and who could help us see it?
Stewardship
Stewardship means caring for resources and systems that others depend on, including people who will use them later. It looks beyond the benefit of a quick launch.
Plan for maintenance, energy use, data protection, and eventual shutdown. Ask who will look after the tool when the original team moves on and how future users can avoid inheriting hidden costs.
Ask together: What are we responsible for caring for over time?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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