Every day, human beings make decisions with social consequences. These social consequences matter most when they impact those closest to us. Recent research has shown that humans exhibit reliable preferences when deciding between conflicting outcomes involving close others – for example, prioritizing the interests of one's family member over one's friend. However, virtually nothing is known about the mechanisms that drive these preferences. We conducted a pre-registered study in a large (maximum N = 375) sample to quantify the computational and motivational mechanisms of human social decision-making preferences involving close others. By pairing assessment techniques from behavioral economics and psychological science with computational modeling and random coefficient regression, we show that value-based cognitive computations (e.g., risk and loss aversion) drive social decision-making preferences involving financial outcomes, whereas socioemotional motivations (e.g., relationship quality) underlie preferences involving social outcomes. These results imply mechanistic heterogeneity, underscoring a need for greater attention to contextual specificity in social decision-making.

每天，人类都会做出具有社会后果的决定。当这些社会后果影响到我们最亲近的人时，它们最重要。最近的研究表明，在涉及亲密他人的冲突结果之间做出决定时，人类表现出可靠的偏好——例如，将家庭成员的利益置于朋友之上。然而，对于驱动这些偏好的机制几乎一无所知。我们在一项大型（最大N = 375）样本来量化涉及亲密他人的人类社会决策偏好的计算和激励机制。通过将行为经济学和心理科学的评估技术与计算建模和随机系数回归相结合，我们表明基于价值的认知计算（例如，风险和损失厌恶）驱动涉及财务结果的社会决策偏好，而社会情感动机（例如，关系质量）是涉及社会结果的偏好的基础。这些结果意味着机械异质性，强调需要更多地关注社会决策中的上下文特异性。