Artificial Intelligence and IT Identity: Towards a Comprehensive Understanding of Human-Machine Integration in the Workplace

Abstract

Cognitive computing systems (CCS) are a new generation of automated IT systems that simulate human cognitive capabilities. Cognitive computing reshapes the interaction between humans and machines and challenges the way we study technology use and adaptation in the Information Systems field. The present work introduces co-adaptation theory, which occurs when both the user and the CCS adapt simultaneously to make the system fit the user. Co-adaptation involves two types of adaptation: human adaptation and machine adaptation. Human adaptation refers to the degree to which the user adapts to CCS by either changing system features or changing the way they interact with the system. Machine adaptation refers to the degree to which the user perceives that the CCS adapts itself to fit the user’s needs. Using polynomial modeling, moderated polynomial regression, mediated polynomial regression, and response surface analysis, we examine longitudinal survey data of 248 Intelligent Assistant users. The findings show that when individuals and CCS both adapt at the same rate, it has the greatest effect on individual relationships with the CCS (i.e., strong IT identity). Furthermore, IT identity fully mediates the association between co-adaptation and individual innovative performance. Lastly, anthropomorphism moderates the association between co-adaptation and IT identity. The data shows that in low anthropomorphism individuals expect CCS to adapt more to them.