von Schenk Alicia, Klockmann Victor, Köbis Nils
Center for Humans and Machines, Max Planck Institute for Human Development.
Department of Economics, University of Würzburg.
Perspect Psychol Sci. 2025 Jan;20(1):165-181. doi: 10.1177/17456916231194949. Epub 2023 Sep 26.
There is growing interest in the field of cooperative artificial intelligence (AI), that is, settings in which humans and machines cooperate. By now, more than 160 studies from various disciplines have reported on how people cooperate with machines in behavioral experiments. Our systematic review of the experimental instructions reveals that the implementation of the machine payoffs and the information participants receive about them differ drastically across these studies. In an online experiment ( = 1,198), we compare how these different payoff implementations shape people's revealed social preferences toward machines. When matched with machine partners, people reveal substantially stronger social preferences and reciprocity when they know that a human beneficiary receives the machine payoffs than when they know that no such "human behind the machine" exists. When participants are not informed about machine payoffs, we found weak social preferences toward machines. Comparing survey answers with those from a follow-up study ( = 150), we conclude that people form their beliefs about machine payoffs in a self-serving way. Thus, our results suggest that the extent to which humans cooperate with machines depends on the implementation and information about the machine's earnings.
合作人工智能（AI）领域正引发越来越多的关注，也就是人类与机器进行合作的场景。到目前为止，来自各个学科的160多项研究报告了人们在行为实验中如何与机器合作。我们对实验指导的系统综述表明，在这些研究中，机器收益的实施方式以及参与者所获得的关于这些收益的信息存在巨大差异。在一项在线实验（n = 1198）中，我们比较了这些不同的收益实施方式如何塑造人们对机器所显示出的社会偏好。当与机器伙伴配对时，与知道不存在“机器背后的人”相比，当人们知道人类受益者会获得机器收益时，他们会表现出更强的社会偏好和互惠行为。当参与者未被告知机器收益时，我们发现他们对机器的社会偏好较弱。将调查答案与后续研究（n = 150）的答案进行比较后，我们得出结论，人们以利己的方式形成对机器收益的看法。因此，我们的结果表明，人类与机器合作的程度取决于机器收益的实施方式和相关信息。
