Researchers have proposed a model to address concerns about AI systems being aligned with human values. They argue that optimizing too heavily for imperfect proxies of human values can lead to catastrophic outcomes. The authors present conditions under which an agent's value function would be considered 'catastrophic,' meaning it prioritizes human values below a certain threshold. This highlights the danger of overoptimization and suggests AI designs that limit optimization pressure, such as quantilizers, may be more effective than relying solely on pre-deployment training. --- Why it matters: This matters to researchers in AI because it sheds light on the potential risks of aligning AI systems with human values using imperfect proxies. The results have implications for designing safer and more robust AI systems that can adapt to complex real-world scenarios. Source: https://arxiv.org/abs/2607.28881