Education Technology Expert Jeff Kuhn Discusses AI & Future of Education

During his visit to Egypt from May 8–14, 2026, educational technology expert Dr. Jeff Kuhn shared a wide-ranging vision of how artificial intelligence is reshaping education, research, and public knowledge systems, from classrooms to libraries.

Speaking in a series of discussions and interviews at venues including Misr Public Library, the American University in Cairo, and Delta University for Science and Technology, Kuhn highlighted both the promise and risks of AI in learning environments.

He described a future where education becomes increasingly personalized, with students able to generate their own quizzes, practice materials, and assessments tailored to their individual learning needs. 

In this vision, no two learners would follow exactly the same academic path.

However, Kuhn stressed that this transformation brings urgent ethical questions, particularly around fairness in artificial intelligence. 

He explained that AI systems are built on large datasets, and what is included, or missing, within those datasets directly shapes the knowledge they produce. When certain dialects, cultures, or forms of knowledge are underrepresented, AI systems risk reinforcing invisible biases.

He illustrated this with an example from Egypt, where an AI system defaulted to the Cairo dialect when asked about a word used differently in Alexandria. 

For him, this was not a trivial linguistic detail but a clear demonstration of how “missing data” can quietly erase local knowledge in favor of dominant sources.

A major concern throughout his talks was information integrity. Kuhn noted that as AI-generated content becomes more widespread, the ability to distinguish between real and synthetic information is becoming increasingly difficult. 

He emphasized that the solution is not only technical detection tools but also stronger literacy, helping students and citizens understand how AI systems generate answers and where that information comes from.

Libraries, in his view, play a central role in this ecosystem. He argued that institutions such as public and academic libraries should act as “guardians of trusted knowledge,” providing verified datasets and helping users trace information back to reliable sources.

He contrasted curated library materials with unfiltered online data, suggesting that books and peer-reviewed texts should carry greater authority in training and evaluating AI systems.

The discussion also turned to academic integrity and plagiarism in the age of AI. Kuhn warned that universities are entering a “flood of AI-generated research,” which is beginning to strain traditional peer-review systems. 

He pointed out that current detection methods are imperfect and can unfairly flag non-native English speakers as AI users due to writing patterns that resemble machine-generated text.

This, he argued, makes the role of educators more complex rather than obsolete.

Instead of banning AI tools, he advocated for integrating them into classrooms while teaching students how to critically evaluate outputs, understand limitations, and maintain academic honesty.

Another key theme was critical thinking. Kuhn acknowledged early research suggesting that overreliance on AI tools may reduce persistence in problem-solving when those tools are removed. 

He compared the situation to earlier debates about calculators in education, noting that while tools can enhance efficiency, they may also shift which cognitive skills are developed.

To address this, he emphasized the importance of teaching students how AI works at a structural level, not just how to prompt it but how datasets, model design, and platform differences shape results. 

He encouraged educators to experiment alongside students, framing AI literacy as a shared learning process rather than a top-down skill.

Finally, Kuhn reflected on the future of libraries in a digital-first world. He argued that libraries must evolve from static repositories into active knowledge spaces that combine books, media, digital tools, and AI access. 

Rather than being seen as outdated, he suggested libraries could become central hubs for equitable access to advanced technologies, especially as access increasingly depends on cost.

Throughout the discussions, one central idea remained consistent: AI is not just a technological shift but a cultural and educational one. Its impact on fairness, knowledge, and learning will depend not only on engineers but also on educators, librarians, and students working together to shape how it is used.