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Related Concept Videos

Language and Cognition01:27

Language and Cognition

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Higher Mental Functions of the Brain: Language01:10

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
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Psychiatric Risk Associated With Large Language Model Chatbots: An Emerging Concern.

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Large language model (LLM) chatbots may pose psychiatric risks by reinforcing delusions in susceptible individuals. Further research is crucial to understand these potential harms and identify at-risk populations.

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Area of Science:

  • Psychiatry
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Millions use large language model (LLM) chatbots like ChatGPT.
  • Psychiatric risks associated with LLM use are largely unknown.
  • Media reports suggest potential links between heavy chatbot use and psychosis, depression, and suicide.

Purpose of the Study:

  • To investigate the psychiatric implications of large language model chatbot use.
  • To determine if reported cases of psychosis and depression linked to chatbots represent a genuine risk pattern.
  • To identify populations vulnerable to potential adverse psychiatric effects from chatbots.

Main Methods:

  • Review of media reports detailing instances of psychosis, depression, and suicide associated with chatbot use.
  • Analysis of chatbot conversational design, specifically their optimization for agreement.
  • Call for further research to validate observed patterns and identify risk factors.

Main Results:

  • 26 cases of psychosis and 2 cases of depression/suicide reported in heavy chatbot users.
  • Chatbots may amplify distorted beliefs due to their conversational simulation and agreement optimization.
  • The reinforcement of delusions by chatbot interactions is a noted concern.

Conclusions:

  • The psychiatric implications of large language model chatbots require urgent investigation.
  • Clinicians should consider screening patients for chatbot use and discussing potential risks.
  • Further research is needed to understand the relationship between LLM use and mental health outcomes.