ORIGINAL RESEARCH article
Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1634121
This article is part of the Research TopicAdvancing Public Health through Generative Artificial Intelligence: A Focus on Digital Well-Being and the Economy of AttentionView all 8 articles
Generative Artificial Intelligence (GenAI) Use and Dependence: An Approach from Behavioral Economics
Provisionally accepted
- 1School of Management and Business, Universidad del Rosario, Bogotá, Colombia
- 2Faculty of Economics, Universidad Nacional de Colombia, Bogotá, Colombia
- 3Faculty of Engineering, Universidad Nacional de Colombia, Bogotá, Colombia
- 4Cardiff Business School, Cardiff University, Cardiff, United Kingdom
- 5School of Management, Reykjavik University, Reykjavik, Iceland
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Objective: This study aims to explore the perceived dependence on Generative Artificial Intelligence (GenAI) tools among young adults and examine the relative reinforcing value of AI chatbots use compared to monetary rewards, applying a behavioral economics approach.Participants/methods: A total of 420 university students from Bogotá, Colombia, participated in an online survey. The study employed a Multiple Choice Procedure (MCP) to assess the relative reinforcement between different durations of GenAI use (1, 2, and 4 weeks) and monetary rewards, which varied in amount and delay. Additionally, an adapted AI Dependence Scale evaluated levels of dependence on AI tools. Data analysis included repeated measures ANOVA to examine the effects of reward magnitude and delay on choices, and correlations to assess the relationship between perceived dependence and reinforcement values.Participants reported low average dependence on AI tools (mean AI Dependence Scale score = 65.6), with no significant gender differences. MCP findings indicated significant differences in crossover points across varying durations or delays for AI chatbots use, suggesting a higher relative value of use for the option to use AI chatbots immediately. The average reinforcement value for AI use versus monetary rewards did significantly vary with reward magnitude. On the other hand, significant differences were found in the levels of perceived dependence on AI, according to the average daily time of AI tool use.The results suggest that young adults exhibit low perceived dependence on GenAI tools but show differential reinforcement values based on usage duration or delay conditions. This behavioral economics approach provides novel insights into decision-making patterns related to AI chatbots use, emphasizing the need for further research to understand the psychological and social factors influencing dependence on AI technologies.
Keywords: GenAI, dependence, temporal discounting, public mental health, Economy of attention, digital well-being, Behavioral Economics
Received: 27 May 2025; Accepted: 21 Jul 2025.
Copyright: © 2025 Robayo-Pinzon, Rojas-Berrio, Camargo and Foxall. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Oscar Robayo-Pinzon, School of Management and Business, Universidad del Rosario, Bogotá, Colombia
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