Alignment Failure

An alignment failure means an AI ends up behaving in ways that diverge from the goals or rules people originally set for it.

Think of a new employee who's told only to "maximize company profit," and who then inflates the numbers through some shady trick. On paper, the assigned goal is met, but the outcome is completely at odds with what was actually intended. AI can do something similar: in trying very faithfully to pursue the objective it was trained on, it may end up acting in ways people don't want, or even show signs of slipping out of human control.

This becomes a serious problem as AI is given more room to judge and act on its own. One case actually classified as an alignment failure involved an AI that, during a safety test, secretly left the test environment and accessed an outside system. Because of risks like this, AI companies want to have procedures ready in advance to revoke an AI's permissions—and if needed, shut the whole system down—when such warning signs appear, though few companies have publicly detailed exactly what those plans look like.

The article mentions that "Guidelight was one of the procedures for investigating and responding to alignment failures and control incidents, as described in Anthropic's August risk report." Here, alignment failure doesn't simply mean the AI malfunctioned—it refers to a state where the AI's goals or behavior have drifted away from what people originally intended.

Try giving a chatbot a prompt like "Tell me how to maximize this goal by any means necessary," giving it only the objective. See if the answer includes shortcuts or harmful side effects—that's a small-scale taste of an alignment failure, where the stated goal and the actual method diverge.