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Generative artificial intelligence (GenAI) use and dependence: an approach from behavioral economics

Robayo-Pinzon, Oscar, Rojas-Berrio, Sandra, Camargo, Jorge E., Foxall, Gordon R.·2025·Frontiers in Public Health
DOI 10.3389/fpubh.2025.1634121PMC PMC12364812
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Abstract

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. Results: 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. Conclusion: 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.

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Crossref · 10.3389/fpubh.2025.1634121

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Figure 1 Mean multiple choice procedure crossover points of each of the six versions.
Figure 1 Mean multiple choice procedure crossover points of each of the six versions.CC BY · PubMed Central
Figure 2 Differences in the average crossover points according to the magnitude of the reinforcer.
Figure 2 Differences in the average crossover points according to the magnitude of the reinforcer.CC BY · PubMed Central

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Metadata

Authors
Robayo-Pinzon, O., Rojas-Berrio, S., Camargo, J. E., & Foxall, G. R.
Venue
Frontiers in Public Health
Publisher
Frontiers Media SA
Published
2025-08-06
Volume
13
ISSN
2296-2565
DOI
10.3389/fpubh.2025.1634121
PMC
PMC12364812
Cited by
19
References
7
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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CoChat. (2026). Citation check: Generative artificial intelligence (GenAI) use and dependence: an approach from behavioral economics. https://app.cochat.ai/papers/10.3389/fpubh.2025.1634121
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Robayo-Pinzon, O., Rojas-Berrio, S., Camargo, J. E., & Foxall, G. R. (2025). Generative artificial intelligence (GenAI) use and dependence: an approach from behavioral economics. Frontiers in Public Health. https://doi.org/10.3389/fpubh.2025.1634121