UCR researchers retrain AI models to keep safety intact when trimmed for smaller devices

Researchers at the University of California, Riverside are addressing the problem of weakened safety in open-source artificial intelligence models when adapted for smaller devices.

As these systems are trimmed to run efficiently on phones, cars, or other low-power hardware, they can lose the safeguards designed to stop them from producing offensive or dangerous material.

The UCR team examined what happens when a model’s exit layer is changed from its default position.

Weakened safety guardrails

Their results, presented at the International Conference on Machine Learning in Vancouver, Canada, showed that safety guardrails weaken once the exit ...