What Makes AI Addictive? The Role of Discounting, Risk Aversion and Self-regulation
Published in Proceedings of the International Conference on Big Data Intelligence and Computing (DataCom), and part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13864)) - Author: Renita Murimi, 2022
AI-enabled technology, with its capabilities of parsing large data sets and adaptively tuning its learning capabilities, has the potential to keep users “hooked”. However, this poses a problem for child users, since their ongoing cognitive development is not adequately primed to implement self-regulation. In this paper, we evaluate the impact of technology overuse by studying its impact on limited attention resources among children. We examine the factors that make AI-enabled technology addictive for children, specifically the impact of the short-term and long-term discounting tendencies and the degree of risk-aversion prevalent among child users. Our work in this paper illustrates the unique attributes of child users of technology, and therefore calls for technology design that can enhance the user experience of children by avoiding negative outcomes associated with the over-usage and addiction of AI-enabled technology.