Recently, Professor Shi Lei of Yunnan University of Finance and Economics (YUFE), in collaboration with Aalto University (Finland), Kyushu University (Japan), Tsinghua University, Shanghai Artificial Intelligence Laboratory, and other institutions, published an academic paper titled "Beyond a binary theorizing of prosociality" in the Proceedings of the National Academy of Sciences (PNAS), with Professor Shi serving as the first corresponding author.

This paper delves into two opposing theoretical hypotheses—prosocial preference and confused learners—based on a study of human cooperation in public goods games. By introducing a robot opponent that always chooses to cooperate in a one-shot anonymous prisoner's dilemma game, and by artificially controlling the participants' awareness of information about their opponents, the study found that neither existing theory can fully explain the experimental results. This demonstrates that the complexity of human cooperation behavior surpasses the framework of existing theories. The study calls for establishing more comprehensive theories to characterize human cooperative behavior.

Professor Shi Lei and his collaborators found that when a few "always-cooperating" individuals exist, and when this commitment to cooperation is transparent to others, overall cooperation levels can be significantly increased. This finding has implications for public policy and organizational management: by emphasizing altruism, ensuring information transparency, and clearly stating commitments to cooperation, broader cooperation can be encouraged. The study also indicates that human cooperative behavior is a complex phenomenon driven by multiple motivations. Future research needs to move beyond binary frameworks, build more comprehensive theoretical models, and explore how to use non-material incentives and transparent communication strategies to promote higher levels of cooperation in social policies and organizational decision-making.

The experimental data for this paper were all collected in the laboratory at Yunnan University of Finance and Economics. Professor Shi Lei and Professor Petter Holme of Aalto University (Finland) jointly served as corresponding authors. The collaborative team included Dr. Chen Shen (Kyushu University), Dr. He Zhixue (YUFE), Dr. Guo Hao (Tsinghua University), Dr. Hu Shuyue (Shanghai Artificial Intelligence Laboratory), and Professor Jun Tanimoto (Kyushu University). This is Professor Shi's fourth paper published in PNAS, with the previous three published in 2018 and 2020. One of the 2018 papers was an ESI highly cited and ESI hot paper.