AI in Education: A Challenge We Cannot Ignore, and an Opportunity We Should Not Miss

About the Speaker: These reflections emanate from ideas shared by Professor Dan Banik, Professor of Political Science at the University of Oslo, Norway, during his public lecture "Beyond the Hype: Can Generative AI Deliver Democracy and Inclusive Global Development?" hosted by the Faculty of Social Sciences and Humanities at the University of Mauritius. As a political scientist specializing in democracy and development, Professor Banik offered a balanced, globally informed perspective on AI's dual role as both a transformative opportunity and a democratic challenge—particularly for institutions in the Global South.

Artificial intelligence is no longer a distant or abstract technological development. It is already reshaping how societies learn, work, govern, communicate, and imagine the future of development. Rather than presenting AI as either a miracle solution or an unavoidable threat, Professor Banik invited the audience to consider both sides of the debate. AI is already transforming education, healthcare, agriculture, climate adaptation, public administration, and democratic participation across the Global South. At the same time, it raises serious concerns around misinformation, surveillance, structural inequality, accountability, and the erosion of public trust.

For the Faculty of Agriculture at the University of Mauritius, this discussion is especially important. Agriculture, food systems, animal science, climate resilience, and rural development are all fields where AI may play an increasingly significant role. AI can support access to knowledge, improve decision-making, assist research, strengthen agricultural productivity, and help prepare students for a more data-driven professional world. Yet these benefits will only be meaningful if AI is guided by local needs, transparency, accountability, and human judgement.

🎓 Rethinking Assessment in the Age of AI

One of the immediate concerns raised is the impact of AI on university assessment. Traditional take-home essays, term papers, and written assignments are becoming harder to evaluate in the same way as before. If students can use AI tools to generate or heavily edit written work, lecturers may struggle to know how much of the final submission reflects the student's own understanding.

This does not mean that written assignments have no value. Rather, it means that we need to become more deliberate about what we are assessing. Are we assessing the final text only, or are we assessing the student's ability to think, question, analyse, interpret data, apply concepts, and defend their reasoning?

Some universities are already responding by bringing back oral examinations, in-class writing, pen-and-paper assessments, presentations, and video-based submissions. These formats allow educators to observe not only the final answer, but also the student's thought process.

In agricultural education, this could be highly valuable. Students could be asked to explain a crop management decision, defend a food safety recommendation, interpret animal production data, or present a solution to a real farm-level problem. AI may help them prepare, but the student must still understand the science, the context, and the consequences of their recommendations.

💡 Teaching Students How to Use AI, Not Pretending They Will Not

Universities are already beyond the stage of simply telling students not to use AI. The more realistic and educationally valuable approach is to teach them how to use it properly. This means helping students understand both the strengths and limitations of AI. AI can summarize information, generate explanations, suggest structures, compare ideas, and support brainstorming. But it can also produce false information, oversimplify complex issues, reproduce bias, and present weak arguments with confidence.

For students in agriculture and food science, this distinction matters. An AI-generated answer about pesticide use, animal nutrition, food safety, soil fertility, or climate-smart agriculture should never be accepted blindly. Students must learn to ask:

• Is the information scientifically correct?
• What evidence supports this claim?
• Is the recommendation appropriate for the Mauritian context?
• Are there environmental, ethical, economic, or public health implications?
• Which sources should be checked before applying this advice?

In this sense, AI can become a tool for developing critical thinking — but only if educators design learning activities around questioning, verification, and reflection.

🌍 AI as a Tool for Democratizing Knowledge & Supporting the Global South

AI has the remarkable ability to democratize access to knowledge, building on earlier developments like massive open online courses (MOOCs). Students can now access explanations, translations, examples, summaries, and tutoring support at any time. This can be particularly important for students who need additional help outside formal lecture hours or who learn better through repeated explanation and practice.

In the Faculty of Agriculture, AI could support students by helping them revise difficult concepts such as animal physiology, plant pathology, food microbiology, soil chemistry, agricultural economics, or research methodology. It could help students generate practice questions, simplify complex journal articles, or compare different farming systems.

Another important theme is the difference in how AI is discussed globally. In Europe, the debate often focuses on risks such as deepfakes, job losses, and threats to democracy. In many parts of the Global South, including countries such as India, China, Malawi, and Mauritius, the discussion often includes a stronger focus on opportunity. AI should not be seen only as a technology imported from elsewhere. It should also be seen as a tool that can help address local and regional challenges, from climate-smart agriculture to extension education for farmers.

⚖️ AI, Ethics, and Academic Integrity

The rise of AI requires a serious conversation about academic integrity. If students use AI to produce work without understanding it, then learning is weakened. If they submit AI-generated text as their own thinking, then academic honesty is compromised. But if they use AI transparently to support brainstorming, revision, language improvement, or exploration of ideas, then it can become part of a legitimate learning process.

The challenge is to create clear faculty-level guidance. Students need to know when AI use is acceptable, when it is not, and how it should be acknowledged. A useful direction may be to require students to disclose how they used AI. For example, students could include a short statement explaining whether they used AI for brainstorming, language editing, summarizing sources, generating practice questions, or checking structure. This would move the focus away from secrecy and toward responsible use.

🚜 Preparing Graduates for an AI-Shaped World & The Changing Role of the Educator

Agriculture is becoming increasingly data-driven. Precision agriculture, remote sensing, climate modelling, disease detection, food traceability, livestock monitoring, and supply chain analytics are all areas where AI and digital tools are becoming more relevant. Students graduating from the Faculty of Agriculture will enter a professional world where AI literacy is an advantage. They do not all need to become programmers or AI specialists. But they do need to understand what AI can do, where it can fail, and how to work responsibly with AI-supported systems.

AI literacy should therefore become part of broader scientific literacy. AI does not remove the need for lecturers. If anything, it makes the educator's role more important. When information is abundant, guidance becomes essential. Lecturers help students understand context, evaluate evidence, connect theory to practice, and develop professional judgement.

In agriculture, this local knowledge is especially important. A generic AI answer may not understand Mauritian farming systems, local food preferences, island-specific climate risks, import dependence, land constraints, pest pressures, or the realities faced by farmers. Educators are needed to help students adapt knowledge to real conditions.

🔭 Conclusion: From Fear to Responsible Adoption

The message is not that AI is harmless. AI raises real concerns: misinformation, manipulation, bias, overdependence, and unequal control by powerful technology companies. But AI also offers major opportunities in education, health, governance, accessibility, and development.

For the Faculty of Agriculture at the University of Mauritius, the task is not to resist AI blindly or adopt it uncritically. The task is to shape its use in a way that strengthens learning. AI should help students become better thinkers, not weaker ones. It should improve access to knowledge, not replace understanding. It should support academic development, not undermine integrity. And it should prepare graduates to contribute meaningfully to agriculture, food systems, and sustainable development in Mauritius and beyond.

The future of education will not be AI-free. But with the right guidance, it can be AI-literate, ethical, inclusive, and deeply human.