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

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Summary

Young adults show low perceived dependence on Generative Artificial Intelligence (GenAI) tools. However, AI chatbot use has a higher reinforcement value than monetary rewards, especially when immediately accessible.

Keywords:
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Area of Science:

  • Behavioral Economics
  • Human-Computer Interaction
  • Artificial Intelligence

Background:

  • Generative Artificial Intelligence (GenAI) tools are increasingly prevalent.
  • Understanding user dependence and the value placed on AI interactions is crucial.
  • Young adults' decision-making regarding AI use requires investigation.

Purpose of the Study:

  • To explore perceived dependence on GenAI tools among young adults.
  • To compare the reinforcing value of AI chatbot use against monetary rewards.
  • To apply a behavioral economics framework to AI usage patterns.

Main Methods:

  • Online survey of 420 university students in Bogotá, Colombia.
  • Multiple Choice Procedure (MCP) to assess relative reinforcement of GenAI use versus monetary rewards.
  • AI Dependence Scale and ANOVA for data analysis.

Main Results:

  • Low average dependence on AI tools reported (mean score 65.6).
  • AI chatbot use showed higher relative value, particularly for immediate access.
  • Reinforcement value varied significantly with reward magnitude and daily AI usage time.

Conclusions:

  • Young adults exhibit low perceived dependence but high immediate value for GenAI tools.
  • Behavioral economics offers insights into AI chatbot decision-making.
  • Further research is needed on psychological and social factors influencing AI dependence.