【主题】Human (In)Compliance to Extortions: Algorithm Awareness Matters
【报告人】杨扬（副教授, 中山大学岭南学院）
【时间】2024年4月19日周五10:00-11:30
【地点】经济学院701会议室
【语言】英文
【摘要】When confronting extortions or oppression, human may take actions to struggle against exploitation even at very high costs, eg. Spartacus Rebellion and workers organizing protests to demand better pay and benefits. Does such incompliance persists when the extortions are implemented by algorithms? This study uses an economic experiment to examine the behavioral responses of human subjects when confronted with an opponent employing an extortionate Zero-Determinant (ZD) strategy, either informed (under I condition) or uninformed (under U condition) that their opponent is an algorithm-based computer. The findings reveal a significant divergence in human behavior depending on their awareness of the opponent's algorithmic nature. In treatments with U condition, subjects demonstrated a propensity of incompliance, even at the expense of their own payoff. Conversely, in treatments with I condition, their rate of cooperation—and thus compliance—increased markedly. Further investigation into the relative income status (advantage, parity, or disadvantage) of human subjects vis-à-vis their opponents across various treatments suggested a nuanced impact of algorithm awareness on incompliance behavior. Subjects displayed a pronounced concern for their relative income status over their absolute income under U condition. However, this preoccupation with relative income status was supplanted by the pursuit of absolute payoff when exposed to I condition. This study provides insights into the influence of algorithm awareness on human economic behavior.
【报告人简介】Yang Yang is an associate professor of economics at Lingnan College, Sun Yat-sen University. She received her PhD in economics from University of Amsterdam. Her research interests are behavioral economics, experimental economics, linguistic economics and platform economics.
