Stingy bots can improve human welfare in experimental sharing networks.

ABSTRACT: Machines powered by artificial intelligence increasingly permeate social networks with control over resources. However, machine allocation behavior might offer little benefit to human welfare over networks when it ignores the specific network mechanism of social exchange. Here, we perform an online experiment involving simple networks of humans (496 participants in 120 networks) playing a resource-sharing game to which we sometimes add artificial agents (bots). The experiment examines two opposite policies of machine allocation behavior: reciprocal bots, which share all resources reciprocally; and stingy bots, which share no resources at all. We also manipulate the bot's network position. We show that reciprocal bots make little changes in unequal resource distribution among people. On the

SUBMITTER: Shirado H 

PROVIDER: S-EPMC10589225 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature