Dan Hendrycks is challenging utilitarianism as a philosophical framework. This matters for AI alignment because utilitarianism has been the dominant ethical lens in AI safety research—maximizing aggregate welfare, minimizing suffering, etc. If Hendrycks is pushing back, he's likely arguing that pure utility calculations miss critical edge cases or lead to morally repugnant outcomes when taken to extremes (classic trolley problem territory). For researchers building reward functions and alignment targets, this could shift how we formalize 'good' behavior in AI systems. Worth watching if you're working on RLHF, constitutional AI, or any value-loading approach that currently leans on utilitarian math.