What does 'AI alignment' refer to in the context of AI safety research?
Select an answer to reveal the explanation.
Short Explanation
You need alignment to make sure AI actually wants what we want it to want — and keeps wanting it as it gets more capable. It's the deep safety problem that groups like Anthropic work on.
Full Explanation
AI alignment is a core area of AI safety research focused on ensuring that AI systems pursue goals and exhibit behaviors that are beneficial and consistent with human values and intentions — even as the systems become more capable. Misaligned AI could have goals that superficially seem correct but lead to harmful outcomes, which is the Goodhart's Law problem. Anthropic was founded in part to address alignment challenges, and Constitutional AI and RLHF are practical alignment techniques. The option about optimizing AI models to run efficiently on specific hardware architectures describes hardware optimization, not alignment. The option about aligning text in AI-generated documents to left or right margins is a literal text-formatting interpretation. The option about training AI models to perform equally well across different demographic groups describes fairness or bias mitigation, which is related but distinct from alignment.