How should well-being be prioritised in society, and what trade-offs are people willing to make between fairness and personal well-being? We investigate these questions using a stated preference experiment with a nationally representative UK sample (n = 300), in which participants evaluated life satisfaction outcomes for both themselves and others under conditions of uncertainty. Individual-level utility functions were estimated using an Expected Utility Maximisation (EUM) framework and tested for sensitivity to the overweighting of small probabilities, as characterised by Cumulative Prospect Theory (CPT). A majority of participants displayed concave (risk-averse) utility curves and showed stronger aversion to inequality in societal life satisfaction outcomes than to personal risk. These preferences were unrelated to political alignment, suggesting a shared normative stance on fairness in well-being that cuts across ideological boundaries. The results challenge use of average life satisfaction as a policy metric, and support the development of nonlinear utility-based alternatives that more accurately reflect collective human values. Implications for public policy, well-being measurement, and the design of value-aligned AI systems are discussed.

翻译：如何在社会中优先考虑福祉，人们在公平与个人福祉之间愿意做出哪些权衡？我们通过一项针对英国全国代表性样本（n=300）的陈述偏好实验来探究这些问题。实验中，参与者在不确定性条件下评估自身及他人的生活满意度结果。我们使用预期效用最大化（EUM）框架估计个体层面的效用函数，并检验其对累积前景理论（CPT）所描述的小概率事件过度加权特征的敏感性。大多数参与者呈现出凹形（风险厌恶型）效用曲线，并且对社会生活满意度结果中的不平等表现出比个人风险更强烈的厌恶。这些偏好与政治立场无关，表明在福祉公平性方面存在跨越意识形态边界的共同规范立场。该结果挑战了将平均生活满意度作为政策衡量指标的做法，并支持开发能更准确反映集体人类价值观的非线性效用替代方案。最后讨论了其对公共政策、福祉测量以及价值观对齐人工智能系统设计的启示。