Artificial Intelligence and Digital Learning: Architecture, Hallucinations, Information, Findability, The First Rung, and The Arts of Inquiry
Keywords:
Artificial Intelligence, Digital Learning, Information Structure, Entry Level Jobs, Inquiry ProcessAbstract
The authors address Artificial Intelligence (AI) powered by Large Language Models (LLMs) and its relationship to learning in contemporary education. Initially, they explain the underlying functionality of AI using transformer architecture, embedding, and tokenization to create language symbolism. Next, they discuss the transformed search concept and how scale-free networks and power law distributions portray information sources dominated by AI hubs that couple and decouple digital learning resources. They contend that Artificial Intelligence will replace bottom- and entry-level jobs by removing a foundational rung of new graduates’ career development. This shift, termed the answer machine, will impact graduates, industry, and education, creating an urgent need to mitigate the risks and leverage the opportunities AI presents. Finally, they consider potential consequences to human creativity, insight, wisdom-related knowledge, and the arts of inquiry in an AI-driven world, emphasizing the need for critical engagement and thoughtful integration of AI in education.
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Copyright (c) 2026 Chuck Dziuban, Gardner Campbell, Colm Howlin, Mark Smith
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