Robayo-Pinzon Oscar, Rojas-Berrio Sandra, Camargo Jorge E, Foxall Gordon R
School of Management and Business, Universidad del Rosario, Bogotá, Colombia.
Faculty of Economics, Universidad Nacional de Colombia, Bogotá, Colombia.
Front Public Health. 2025 Aug 6;13:1634121. doi: 10.3389/fpubh.2025.1634121. eCollection 2025.
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.
本研究旨在探讨年轻人对生成式人工智能(GenAI)工具的感知依赖,并运用行为经济学方法,考察与金钱奖励相比,使用人工智能聊天机器人的相对强化价值。
参与者/方法:共有420名来自哥伦比亚波哥大的大学生参与了一项在线调查。该研究采用多项选择程序(MCP)来评估不同使用时长(1周、2周和4周)的GenAI使用与金额和延迟各不相同的金钱奖励之间的相对强化作用。此外,一个经过改编的人工智能依赖量表评估了对人工智能工具的依赖程度。数据分析包括重复测量方差分析,以检验奖励幅度和延迟对选择的影响,以及相关性分析,以评估感知依赖与强化价值之间的关系。
参与者报告称对人工智能工具的平均依赖程度较低(人工智能依赖量表平均得分 = 65.6),且不存在显著的性别差异。MCP的研究结果表明,在不同时长或延迟的人工智能聊天机器人使用的交叉点上存在显著差异,这表明立即使用人工智能聊天机器人这一选项具有更高的相对使用价值。与金钱奖励相比,人工智能使用的平均强化价值确实会随奖励幅度而显著变化。另一方面,根据人工智能工具的平均每日使用时间,发现对人工智能的感知依赖程度存在显著差异。
研究结果表明,年轻人对GenAI工具的感知依赖程度较低,但根据使用时长或延迟条件显示出不同的强化价值。这种行为经济学方法为与人工智能聊天机器人使用相关 的决策模式提供了新的见解,强调需要进一步研究以了解影响对人工智能技术依赖的心理和社会因素。