Artificial Intelligence and the Obligation to Lead Clearly.
The emergence of capable generative AI tools has produced two dominant and equally unhelpful responses in higher education: uncritical prohibition and uncritical adoption. Keith occupies neither position. His argument is that institutions and educators have an obligation to think carefully about what these tools actually do, what they change about learning and assessment, and what they do not change about the development of human capability.
His 2025 article on generative AI and authentic assessment examines the specific ways that large language models challenge conventional assessment design and proposes a framework for distinguishing between the production of artefacts and the development of competence. The distinction matters because conflating them produces bad policy and worse pedagogy.
In his own courses, he teaches AI literacy not as a technical subject but as a critical thinking discipline — asking students to interrogate outputs, understand provenance, recognise limitation, and make informed judgements about when and how these tools serve their professional development rather than substitute for it.
Innovation in the Organization and Beyond.
Keith's approach to digital and technological innovation is grounded in a practitioner's sensibility: tools are useful insofar as they serve a clear purpose, are understood by the people using them, and help others develop the confidence to navigate change. He actively develops WordPress plugins, builds web applications, experiments with AI-assisted workflows, and mentors students, colleagues, and emerging professionals as they learn to work effectively in rapidly evolving digital environments. His interest in technology is not driven by novelty, but by a commitment to understanding it deeply enough to teach it, critique it, and apply it responsibly.
He has built custom course management tools, booking systems, relational database applications, and learning management prototypes, all as working software rather than theoretical exercises. That commitment to building real things within real constraints keeps his instruction credible, his mentorship practical, and his perspective on artificial intelligence grounded in experience rather than speculation.
His view is straightforward: institutions that treat AI as a threat to be managed will fall behind those that treat it as a condition to be understood, navigated, and leveraged with clarity, intention, and a commitment to helping others adapt and succeed.
