AI in Universities: The Good, the Bot, and the Ugly Truths

The paradigm of the preprint revolves around the integration of Artificial Intelligence (AI) in higher education, specifically focusing on its impact on teaching, learning, and administrative functions. This encompasses the shift towards personalized learning, enhanced efficiency, and improved campus management through the use of AI-powered tools.

The preprint analyzes the current state of AI adoption in Ugandan universities, observing a gradual increase primarily within administrative functions like chatbots and automated systems, rather than core teaching and learning. This indicates a model drift, as the full potential of AI in education, particularly personalized learning and adaptive systems, remains largely untapped. While there's a recognized value and growing enthusiasm for AI's transformative potential, the actual implementation is limited by significant barriers, creating a noticeable drift from the ideal model of fully integrated AI in education. The authors identify inadequate digital infrastructure, limited faculty training, resource disparities, and lack of clear ethical guidelines as key obstacles hindering widespread AI adoption. These challenges, along with the nascent stage of AI integration in Ugandan universities, suggest a model drift where the adoption is lagging behind the envisioned potential and requires adjustments and interventions to steer it back towards the desired trajectory of comprehensive AI integration.