Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/279268 
Year of Publication: 
2023
Series/Report no.: 
CESifo Working Paper No. 10518
Version Description: 
This Version: August 2023
Publisher: 
Center for Economic Studies and ifo Institute (CESifo), Munich
Abstract: 
Can algorithms help people detect deception in high-stakes strategic interactions? Participants watching the pre-play communication of contestants in the TV show Golden Balls display a limited ability to predict contestants' behavior, while algorithms do significantly better. We provide participants algorithmic advice by flagging videos for which an algorithm predicts a high likelihood of cooperation or defection. We find that the effectiveness of flags depends on their timing: participants rely significantly more on flags shown before they watch the videos than flags shown after they watch them. These findings show that the timing of algorithmic feedback is key for its adoption.
Subjects: 
detecting lies
machine learning
cooperation
experiment
JEL: 
D83
D91
C72
C91
Document Type: 
Working Paper
Appears in Collections:

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.