Makovi, Kinga, Sargsyan, Anahit, Li, Wendi, Bonnefon, Jean-François and Rahwan, Tahal (2023) Trust within human-machine collectives depends on the perceived consensus about cooperative norms. Nature Communications, vol. 14 (3108).

Full text not available from this repository.
Identification Number : 10.1038/s41467-023-38592-5


With the progress of artificial intelligence and the emergence of global online communities, humans and machines are increasingly participating in mixed collectives in which they can help or hinder each other. Human societies have had thousands of years to consolidate the social norms that promote cooperation; but mixed collectives often struggle to articulate the norms which hold when humans coexist with machines. In five studies involving 7,917 individuals, we document the way people treat machines differently than humans in a stylized society of beneficiaries, helpers, punishers, and trustors. We show that a different amount of trust is gained by helpers and punishers when they follow norms over not doing so. We also demonstrate that the trust-gain of norm-followers is associated with trustors’ assessment about the consensual nature of cooperative norms over helping and punishing. Lastly, we establish that, under certain conditions, informing trustors about the norm-consensus over helping tends to decrease the differential treatment of both machines and people interacting with them. These results allow us to anticipate how humans may develop cooperative norms for human-machine collectives, specifically, by relying on already extant norms in human-only groups. We also demonstrate that this evolution may be accelerated by making people aware of their emerging consensus.

Item Type: Article
Language: English
Date: May 2023
Refereed: Yes
Place of Publication: London.
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 14 Jun 2023 12:55
Last Modified: 16 Apr 2024 09:35
OAI Identifier:
View Item