Ultimatum Game Behavior in a Social-Preferences Vacuum Chamber

Abstract

We study strategic interaction in an experimental social-preferences vacuum chamber. We mute social preferences by letting participants knowingly interact with computers. Our new design allows for indirect strategic interaction: there are several waves in which computer players inherit the behavior of human players from the previous wave. We apply our method to investigate trembling-hand perfection in a normal-form version of the ultimatum game. We find that behavior remains far off from a trembling-hand perfect equilibrium under selfish preferences even towards the end of our experiment. The likely reasons for our findings are strategic uncertainty and incomplete learning.

For What It’s Worth: Humans Overwrite Their Economic Self-interest to Avoid Bargaining With AI Systems

“…For example, humans are more likely to cheat when interacting with machines [39], cooperate less in public good games [161], and feel less remorse when exploiting machines [121]. Specifically in ultimatum bargaining, evidence suggests that computer players strongly reduce the impact of social concerns on behavior [13,140,154]. This effect appears to vanish once machines play on behalf of humans who still experience the economic consequences of the bargain.…”

Artificial intelligence, ethics, and intergenerational responsibility

“…This subtraction method was further used byFerraro et al (2003) andYamakawa et al (2016) to disentangle motives for individuals' contributions to a public good, and byBenndorf et al (2020) in the context of ultimatum bargaining games.5Electronic copy available at: https://ssrn.com/abstract=4002578…”