The Risks of AI and Social Media for the Developing Brain
By Ran D. Anbar, MD and Ayush Prakash
In previous blogs, I have discussed how AI and digital technology might be used to enhance education, but can also be harmful. In this blog we will explore how overuse of AI in education and exposure to social media may affect the brain, which typically continues to develop until around the age of 25 years.
To best understand how AI affects brain development and therefore education, we must first review the nature of AI systems in current use. The most prominent AI systems today are Large Language Models (LLMs) like ChatGPT, Claude, Grok, Perplexity, and Gemini.
These systems work through computational models that mimic the human brain's structure, thus termed “neural networks.” They consist of interconnected nodes that process and learn from internet data, enabling pattern recognition and decision-making in the field of artificial intelligence called “Machine Learning.” LLMs are trained on massive datasets containing billions of words from books, websites, and other text sources.
Critically, LLMs do not “understand” anything in the ways humans do. Simply, they identify statistical patterns. When an LLM generates a response, it is essentially completing a pattern based on similar contexts it encountered during training (Bender, et al., 2021).
This means that in addition to providing information, LLMs can reproduce biases present in their training data, generate plausible sounding but incorrect information (a phenomenon called “hallucinations”), and completely lack the ability to synthesize genuinely novel ideas that go beyond recombination of existing patterns. (Chollet, 2019)
Perhaps more consequential are the recommendation algorithms that power social media platforms, video streaming services, and content feeds. These systems are similarly a product of the field Machine Learning and predict what content will keep users engaged longest. The algorithms analyze vast amounts of data about user behavior (what they click on, how long they watch, what they share, when they pause or scroll) to build predictive models of individual........





















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