Recently in Calgary, Canada, an international panel brought together leading academics to discuss one of the most pressing questions in higher education today: How should we teach engineering in a world shaped by Large Language Models (LLMs)? The conversation explored both the opportunities and challenges of integrating AI into teaching, assessment and professional practice.
Among the contributors, our SI^NZ member Assoc. Prof. Sherlock Licorish highlighted that LLMs are not simple search engines, but conversational partners—capable of supporting developers with tasks such as code review, knowledge exploration and reasoning.
Sherlock also cautioned that, unlike textbooks or community-vetted platforms, LLMs lack built-in mechanisms for truth validation. “In the past we relied on textbooks as the single source of truth,” he noted, “but with LLMs, truth becomes more elusive.” His reflections underscored the need for critical engagement and technical understanding when using these tools in education. We are glad to see Assoc. Prof. Licorish contributing to this important global discussion on the future of engineering education and digital literacy.
