Sharing Identity with AI Systems: A Comprehensive Review

Abstract

Systems, including humans and artificial agents, are involved in a set of coordinated tasks. The technology becomes intertwined with an individual's identity in daily life. The concept explored here encapsulates the extended-self idea within social identity theory. In this comprehensive review, the idea of shared identity of individuals interacting with AI systems is explored, along with methods, applications, and implications. Assuming that the transition to AI-enhanced society happens ubiquitously, in different categories (e.g., data analysis, text comprehension), realizing shared identity with AI systems is an important step in societal development. Because identity consists of personal and social experience, the social experience is reflected in global environment, and it in turn extends to the artificial environment. AI systems act as part of an individual's extended identity, allowing them to navigate digital spaces, share personal information, and interact with various services. The main advantage of shared identity with AI systems is in coordination improvement and task efficiency: people are better at managing tasks when a common identity is highlighted; the same might be assumed for the interaction of a human and AI systems. The application of such ideas is discussed within personal, social and global identities including a social norm, personification, bias identification, recommender system, social network, ethical considerations, cybersecurity, medical use, and developing a sense of global identity and propose ideas for refining AI Global policy. The implication of AI for employment and ethics is explored.

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