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

Abstract

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.

Optimizing User Acceptance of AI Agents in Information-Sharing Environments

“…The AI agent's purpose was to assist the user in decision-making while sharing information. In previous research, it was proven empirically that the AI agent does this significantly better than a human agent (Hirschprung & Alkoby, 2022). The challenge, however, is to convince users to adopt the AI agent's recommendation, in other words, to gain the user's trust (Thiebes, Lins, & & Sunyaev, 2021).…”

“…Others claimed that sharing information via OSNs might enable identity theft and other negative outcomes (Ellison, Vitak, Steinfield, Gray, & Lampe, 2011; Boyd & Ellison, 2007;Brake, 2014;Sasahara Kazutoshi, 2021). Individuals in online IS environments are often unable to manage and control their own privacy and security (Hirschprung & Alkoby, 2022), usually due to a lack of technological literacy, the stochastic nature of the problem (it is probabilistic rather than deterministic, making it more difficult to perceive), and cognitive laziness (Puaschunder, 2021). Moreover, the increasing use of OSNs and the various social circles they embrace make it more difficult for users to control their privacy in multiple environments (Schwartz-Chassidim, Ayalon, Mendel, Hirschprung, & Toch, 2020).…”