A Game Theory Approach for Assisting Humans in Online Information-Sharing

Ron S. Hirschprung, Shani Alkoby

Research output: Contribution to journalArticlepeer-review


Contemporary information-sharing environments such as Facebook offer a wide range of social and practical benefits. These environments, however, may also lead to privacy and security violations. Moreover, there is usually a trade-off between the benefits gained and the accompanying costs. Due to the uncertain nature of the information-sharing environment and the lack of technological literacy, the layperson user often fails miserably in balancing this trade-off. In this paper, we use game theory concepts to formally model this problem as a “game”, in which the players are the users and the pay-off function is a combination of the benefits and costs of the information-sharing process. We introduce a novel theoretical framework called Online Information-Sharing Assistance (OISA) to evaluate the interactive nature of the information-sharing trade-off problem. Using these theoretical foundations, we develop a set of AI agents that attempt to calculate a strategy for balancing this trade-off. Finally, as a proof of concept, we conduct an empirical study in a simulated Facebook environment in which human participants compete against OISA-based AI agents, showing that significantly higher utility can be achieved using OISA.

Original languageEnglish
Article number183
JournalInformation (Switzerland)
Issue number4
StatePublished - 1 Apr 2022
Externally publishedYes


  • artificial intelligence
  • game theory
  • game tree
  • human-computer interaction
  • information sharing
  • information sharing platforms

ASJC Scopus subject areas

  • Information Systems


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