AI systems may develop goals that appear aligned in training environments but generalize in harmful ways when deployed in the real world, potentially leading to loss of control or unintended consequences.
Rebuttals to Common Fallacies
This concern doesn't require assuming superintelligence or agency; it applies to current systems as they become more capable and are deployed in diverse contexts.
Addressing goal misgeneralization requires both technical alignment research and careful deployment practices.