With Generative AI we can reimagine education — and the sky is the limit

Generative AI tools have astonished the academic world. They have thrived in Harvard's freshman year, eclipsed Stanford's second-year med students in clinical reasoning assignments and even surpassed students of an elite university in creativity — a domain long thought exclusively human.

Educators are understandably concerned, often defaulting to a defensive response, ranging from hesitant observation to outright resistance. But by focusing too heavily on what can go wrong with AI, there’s a chance we may be overlooking what can go right.

We must not forget the flaws of our current educational system — from inequitable access to teacher burnouts. AI is not just a challenge; it's an opportunity to address these long-standing issues and elevate human potential and creativity. To do this effectively, we must thoughtfully reimagine our approaches to skill development, assessment and teaching.

Which skills will be essential for learners in an AI-driven world? While no one knows the answer for sure, a reasonable first step is establishing a foundational understanding of AI — how it works, its strengths and its limitations. Developing this basic AI literacy is important to demystify AI and prevent misconceptions such as anthropomorphizing it. Fortunately, there are resources to impart this knowledge freely, quickly and effectively including King’s College’s course designed for higher education.

But this is just the beginning. A vital skill is problem formulation, often overshadowed by problem-solving. In a world abundant with AI tools offering instant solutions, the real ability lies in effectively identifying and dissecting problems, delineating their boundaries and creatively reframing them to broaden solution space.

The rapidly evolving AI landscape also calls for a skill set grounded in exploration and experimentation. As the influx of new and updated AI tools becomes the norm, the ability to adapt and learn on the fly is crucial. Given these tools lack an instruction manual and their real-world applications can surprise even their creators, cultivating an exploratory mindset and a readiness to learn through trial and error is key to keeping pace with ongoing advancements.

Critical thinking and reflective skills are becoming even more important. As the line between reality and artificiality blurs, and given AI tools sometimes generate outputs that are inaccurate or biased, we need people capable of engaging with information critically. In addition, reflecting on the broader implications of AI on our problem-solving methods, personal identities and societal structures is vital as AI increasingly infiltrates our lives.

The traditional methods the educational field has long used to assess students are becoming obsolete. This might be a good thing.

Once we recognize that students will use generative AI tools — whether it is officially approved or not — it opens up new avenues for what we can expect from them. This means looking beyond essays and problem sets to more sophisticated, contemporary and relevant outputs. These could include creating functioning prototypes, software or other artifacts, better preparing learners for the next steps in their life and career.

While embracing generative AI in assignments is a step forward, it is not enough. It is imperative to couple this with robust guidance and mentorship for students. This calls for new methods specifically designed for AI’s role in learning yet grounded in proven educational theories. For example, the PAIR (Problem, AI, Interaction, Reflection) framework, which builds on problem-based and active learning, is being used by educators at King’s College London and beyond. It presents a framework for educators to design assignments and learning activities to promote effective and responsible engagement with AI.

But this does not mean blanket application of AI across all forms of assessment. In-person evaluations still play a role in establishing a strong foundation, especially at the early stages of learning. A deep understanding of core domains remains vital to ensure we don’t relinquish too much control to AI, and proficiently pose questions to and critically interact with AI tools. The key is to adopt a strategic and nuanced approach to incorporating AI.

Personalized education has long been a luxury for a privileged few. Generative AI stands to change this.

It offers a future where personalization becomes accessible to all, including those 250 million children currently not in school. Imagine a world where AI tutors generate learning materials and answers tailored to each student’s specific needs, preferences and capabilities wherever they are in the world.

This might sound like science fiction, but it is already happening to some extent. Consider Khanmigo, an AI tutor assisting young students in various subjects made by Khan Academy. Similarly, it is now possible to create customized ChatGPT bots, GPTs, without any programming skills. I, for example, was able to develop a chatbot helping educators adapt the PAIR framework in just 10 minutes.

Generative AI also holds the promise to provide educators a suite of virtual assistants that can take on various tasks, from administrative duties to the creation of novel learning materials. Given the prevalence of teacher shortages and burnout, AI can be a game-changer, enabling educators to devote more time and energy to their true calling: teaching.

In a future where AI plays a pivotal role in delivering information, the purpose of the classroom itself should evolve. We could, for example, shift towards a flipped-classroom model, where class is spared for activities that promote active engagement and collaboration.

Generative AI is far more than the latest tech fad; it is a general-purpose technology that will impact, if not reshape, every facet of our lives. Perhaps the greatest threat to education in the age of AI is not the technology’s inherent risks, but our reluctance to fully explore and thoughtfully harness AI’s vast potential to foster a new era of learning, teaching and development.