Potential Cognitive Risks of Generative Transformer-Based AI Chatbots on Higher Order Executive Functions

Umberto León-Domínguez*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Chat generative retrained transformer (ChatGPT) represents a groundbreaking advancement in Artificial Intelligence (AI-chatbot) technology, utilizing transformer algorithms to enhance natural language processing and facilitating their use for addressing specific tasks. These AI chatbots can respond to questions by generating verbal instructions similar to those a person would provide during the problem-solving process. Aim: ChatGPT has become the fastest growing software in terms of user adoption in history, leading to an anticipated widespread use of this technology in the general population. Current literature is predominantly focused on the functional aspects of these technologies, but the field has not yet explored hypotheses on how these AI chatbots could impact the evolutionary aspects of human cognitive development. Thesis: The “neuronal recycling hypothesis” posits that the brain undergoes structural transformation by incorporating new cultural tools into “neural niches,” consequently altering individual cognition. In the case of technological tools, it has been established that they reduce the cognitive demand needed to solve tasks through a process called “cognitive offloading.” In this theoretical article, three hypotheses were proposed via forward inference about how algorithms such as ChatGPT and similar models may influence the cognitive processes and structures of upcoming generations. Conclusions: By forecasting the neurocognitive effects of these technologies, educational and political communities can anticipate future scenarios and formulate strategic plans to either mitigate or enhance the cognitive influence that these factors may have on the general population.

Original languageEnglish
JournalNeuropsychology
DOIs
Publication statusPublished - Jan 2024

Bibliographical note

Publisher Copyright:
© 2024 American Psychological Association

All Science Journal Classification (ASJC) codes

  • Neuropsychology and Physiological Psychology

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