The Role of Generative AI in Education: Beyond Efficiency

Understanding the Shift in Educational Perspectives

Generative artificial intelligence has transitioned from a novelty to a necessity in education. Discussions now encompass policy and integrity, as well as pedagogy and assessment. However, a common misconception persists: the belief that the primary value of AI lies in its efficiency.

This perspective is understandable. Schools are bustling environments, and any technology that promises speed or automation is appealing. Yet, if we begin with efficiency as our primary focus, we risk overlooking a more crucial educational question:

What kind of thinking does generative AI invite, and what kind of thinking does it require from us in return?

The Nature of AI Outputs

Generative AI does not create knowledge in a meaningful epistemic sense. Instead, it produces plausible language-based outputs shaped by patterns in existing data. These outputs often appear confident, coherent, and authoritative. This is precisely why they require careful evaluation. The danger lies not in AI “getting things wrong,” but in it getting things almost right. Such outputs can seem convincing enough to bypass critical judgment.

AI outputs are only as educationally valuable as the thinking we bring to them.

The Importance of Critical Thinking

Critical thinking must remain at the forefront of our educational approach. When students and educators analyse, challenge, compare, and justify AI-generated material, learning is enhanced. Conversely, when these outputs are accepted, reproduced, or treated as final answers, the quality of learning diminishes. In this context, AI does not lower the bar for thinking; it raises it.

Much of my recent work with schools and students has centred on this shift. We are moving from asking whether AI can help us work faster to exploring how it can assist us in designing tasks that require judgment. A well-structured curriculum and assessment should not merely ask students to explain or describe. Instead, they should encourage students to evaluate, justify, recognise limitations, and take responsibility for their claims. AI can support this endeavour by generating contrasting interpretations, surfacing assumptions, or modelling flawed reasoning, but it cannot replace the need for human judgment.

The Question of Expertise in AI

There is no final authority on AI, so who are the experts?

Another claim I frequently encounter is the notion of the “AI expert.” While there are individuals with deep technical knowledge of machine learning systems, data structures, and computational models, this expertise is not as crucial as the media often suggests. In education, the rapid pace of development means that no one can credibly assert final authority over what AI is or will become. The technology evolves too quickly, the contexts of its use are too diverse, and the pedagogical implications are too varied to predict or control.

In educational settings, humility is not a weakness; it is a professional strength. Acknowledging uncertainty, modelling responsible experimentation, and remaining open to revision are far more valuable than projecting confidence or control.

There is no shame in saying “we are still learning”—in fact, it may be the most honest stance available to us.

The Future of AI in Education

As we approach the next phase of AI’s integration into education, the central message is clear: Generative AI will not improve teaching and learning by itself. However, when it is met with disciplined critical thinking, careful curriculum design, and professional judgment, it can enhance our educational practices. The quality of AI outputs will always reflect the quality of the thinking that surrounds them, and that responsibility remains firmly in human hands.

The Role of Educators in AI Integration

Educators play a pivotal role in integrating AI into the learning environment. They must guide students in navigating AI-generated content, encouraging them to question and critique these outputs. This process not only fosters critical thinking but also helps students develop a deeper understanding of the material.

By facilitating discussions around AI, educators can help students recognise the limitations of these technologies. This awareness is crucial in a world where AI is becoming increasingly prevalent. Students must learn to discern between credible information and AI-generated content that may lack depth or accuracy.

Designing Curriculum with AI in Mind

Curriculum design must evolve to incorporate the capabilities of AI while maintaining a focus on critical thinking. Educators should create assignments that challenge students to engage with AI outputs thoughtfully. For instance, tasks could involve comparing AI-generated responses to human-generated ones, analysing the strengths and weaknesses of each, and discussing the implications of relying on AI for information.

Such assignments not only enhance critical thinking skills but also prepare students for a future where AI will play a significant role in various fields. By integrating AI into the curriculum, educators can ensure that students are equipped to navigate a landscape increasingly influenced by technology.

The Ethical Considerations of AI in Education

As AI becomes more integrated into education, ethical considerations must be at the forefront of discussions. Issues such as data privacy, algorithmic bias, and the potential for misinformation must be addressed. Educators should engage students in conversations about these ethical dilemmas, fostering a sense of responsibility and awareness.

By discussing the implications of AI, students can develop a more nuanced understanding of its role in society. This critical engagement will empower them to use AI responsibly and ethically in their future careers.

Conclusion: Embracing the Challenge of AI

In conclusion, the integration of generative AI into education presents both opportunities and challenges. While AI has the potential to enhance learning experiences, it is crucial that we approach its use with a critical mindset. By prioritising critical thinking, careful curriculum design, and professional judgment, we can harness the power of AI to enrich educational practices.

As we navigate this evolving landscape, let us remember that the responsibility for quality education lies with us. Embracing the complexities of AI will ultimately lead to more meaningful learning experiences for students.

Christopher Clyde G. for Verdant Consultancy

Editor’s note

The image accompanying this article shows an unfinished work by Keith Haring. Its incompleteness is intentional. Like generative AI outputs, it offers form and direction without closure. Meaning is not contained within the work itself but emerges through interpretation, judgment, and context.

In 2023, an attempt was made to “complete” this unfinished work using generative AI. While technically impressive, the result underscored a central tension explored in this article: completion is not the same as understanding. The presence of an output does not resolve questions of intention, meaning, or value—those remain human responsibilities.

Selected Reading

International Baccalaureate Organization. Academic Integrity. International Baccalaureate Organization, 2019.

International Baccalaureate Organization. Theory of Knowledge Guide. International Baccalaureate Organization, 2020.

International Baccalaureate Organization. Guidance on the Use of Artificial Intelligence in the IB Programmes. International Baccalaureate Organization, 2023.

Kahneman, Daniel. Thinking, Fast and Slow. Farrar, Straus and Giroux, 2011.

Selwyn, Neil. Should Robots Replace Teachers? AI and the Future of Education. Polity Press, 2019.

Bender, Emily M., et al. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, ACM, 2021, pp. 610–623.