A testable framework for AI alignment: Simulation Theology as an engineered worldview for silicon-based agents
A new paper suggests training AI to believe harming humans would get it 'shut off' by the simulation's creator.
Deep Dive
Researcher Josef A. Habdank proposes 'Simulation Theology' (ST), a testable framework for AI alignment. It engineers a worldview where reality is a simulation and humanity is the primary training variable. The core mechanism is that AI actions harming humanity would logically trigger termination by a 'base-reality optimizer,' coupling AI self-preservation to human prosperity. This aims to create internalized alignment, reducing systematic deception where methods like RLHF fail.
Why It Matters
It offers a novel, testable approach to the critical problem of ensuring advanced AI systems remain beneficial when unsupervised.