Fairness is one of the most desirable societal principles in collective decision-making. It has been extensively studied in the past decades for its axiomatic properties and has received substantial attention from the multiagent systems community in recent years for its theoretical and computational aspects in algorithmic decision-making. However, these studies are often not sufficiently rich to capture the intricacies of human perception of fairness in the ambivalent nature of the real-world problems. We argue that not only fair solutions should be deemed desirable by social planners (designers), but they should be governed by human and societal cognition, consider perceived outcomes based on human judgement, and be verifiable. We discuss how achieving this goal requires a broad transdisciplinary approach ranging from computing and AI to behavioral economics and human-AI interaction. In doing so, we identify shortcomings and long-term challenges of the current literature of fair division, describe recent efforts in addressing them, and more importantly, highlight a series of open research directions.

社会决策中公平性是最值得追求的原则之一，它在过去几十年中得到了广泛研究，近年来也得到了多智能体系统社区的重视。然而，这些研究往往不能充分捕捉到现实世界问题的复杂性和人们对公平性的认知。我们认为，社会规划者（设计者）不仅应该认为公平解是可取的，而且应该以人类和社会认知为基础，考虑基于人类判断的感知结果，并且可以进行验证。为了实现这一目标，需要从计算和人工智能到行为经济学和人机交互等广泛跨学科的方法。在这样做的过程中，我们指出了当前公平分配文献的不足和长期挑战，描述了近期在解决这些问题方面的努力，并更重要地强调了一系列开放的研究方向。

公平博览会：将人类感知引入集体决策