As educators, we’ve weathered waves of technological innovation, each heralded as the end of traditional teaching as we know it. Calculators were supposed to render the instruction of maths obsolete, and interactive whiteboards were going to revolutionise the classroom. Yet here we stand, still led by the dedicated teachers who form the heart of education.
Presenting at AI For Education, Verso School, Bangkok.
At the recent AI in Education Conference, hosted by Verso International School and 21st Century Learning, this narrative took centre stage. Far from declaring that artificial intelligence will replace teachers, the conference emphasised a more balanced perspective: AI is a tool to enhance teaching, not a replacement for human educators.
This distinction is critical. AI can generate endless practice problems, analyse patterns in student performance, and provide instant feedback. These capabilities free educators to focus on what truly matters—fostering curiosity, encouraging critical thinking, and supporting students’ emotional and creative growth. Imagine a teacher using AI to generate personalised learning pathways for every student, allowing them to spend more time coaching, inspiring, and connecting.
Dr. John Nash Presenting his Keynote at the conference.
Yet, as the discussions at Verso made clear, AI is no silver bullet [echoing Ethan Mollick more than once]. It cannot replicate the nuanced, lived-in expertise of a teacher. Only a teacher can observe a student's anxiety, adapt lessons to the energy in the room, or offer the empathy that transforms a struggling learner into a confident one. These human qualities remain irreplaceable, underscoring the importance of augmenting the practice of human educators with artificial intelligence.
The question isn’t whether AI will take over teaching. It’s how educators and schools can use it creatively, responsibly, and effectively to enhance their work. As participants explored at the conference, the integration of AI must be guided by clear goals, ethical considerations, and an unwavering commitment to the human element of education. Just yesterday, Apple and Dr. Sabba Quidwai were expressing the same sentiments.
The Ethical Imperative: Frameworks for AI in Education
The rapid adoption of AI in schools requires robust ethical frameworks to guide its integration which was a recurring theme at the conference. The discussions emphasised that technology, for all its potential, is only as good as the values behind its use.
A powerful example discussed was stakeholder mapping—a process of identifying the roles, concerns, and responsibilities of everyone impacted by AI in education:
Teachers need to maintain authentic human connections while ensuring that AI supports their expertise.
Parents want transparency about data usage and assurances that AI won’t undermine teacher-led learning.
Students require clear guidance on AI use, with safeguards to prevent over-reliance on its capabilities.
By addressing these concerns collaboratively, schools can build trust and ensure that AI aligns with their core values. Consider data privacy (The EU’s Right to be Forgotten Laws)—a cornerstone of ethical AI use. Schools must adopt transparent policies and communicate openly about how student data is handled.
The conference also stressed the importance of keeping humans in the loop. Teachers and administrators must actively evaluate AI outputs for biases, inaccuracies, and ethical red flags. Without this active oversight, there’s a risk of ceding too much control to systems that lack judgment and accountability.
Ethical frameworks are about more than compliance; they’re about building a culture of trust, equity, and collaboration. The goal is clear: to ensure that AI serves to empower educators and students, not control them.
Practical Tools for AI Integration: Empowering Educators with Structure and Simplicity
Among the many insights shared at the conference, one of the most practical takeaways was the 6-Point Framework for AI Tool Evaluation. This framework provides educators with a systematic way to assess AI tools, focusing on:
Data Privacy: Is student data handled securely and ethically?
Educational Value: Does the tool align with and enhance learning goals?
Technical Reliability: Is the tool consistent and easy to troubleshoot?
Ease of Implementation: How much training and support is needed for teachers to adopt it?
Resource Requirements: Does the tool justify its time and financial costs?
Ethical Alignment: Does the tool reflect the school’s values?
The Hattiebot for visible learning via Claude/ ChatGPT
These criteria move the conversation from “Is this tool impressive?” to “Does this tool serve our purpose?” For example, a tool like Hattiebot —demonstrated at the conference—helps teachers design lessons using evidence-based strategies from John Hattie’s principles of visible learning. It simplifies planning, offering step-by-step guidance on defining learning intentions, setting success criteria, and incorporating high-impact teaching methods.
Tools like Hattiebot show how AI can streamline workflows, freeing teachers to focus on their students. The key takeaway: AI tools must enhance, not complicate, the teaching process.
Professional Development: Meeting Teachers Where They Are
For AI to be effective, professional development (PD) must address the diverse needs of teachers. The conference identified three key educator profiles, each requiring a tailored approach:
Early Adopters: Confident and curious, these teachers need advanced training to use AI in more complex ways and can mentor others.
Cautiously Interested Teachers: Curious but unsure, these teachers benefit from simple, low-risk AI tools that clearly show value without disrupting routines.
Resistant Teachers: Sceptical teachers need to see how AI saves time and supports, rather than replaces, their teaching.
Effective PD emphasises hands-on examples and ethical considerations. For instance, a teacher hesitant about AI might try using Hattiebot to simplify lesson planning, experiencing its benefits firsthand. By addressing fears and building confidence through real-world applications, PD bridges the gap between scepticism and adoption.
Responsible AI: Ethical Considerations and Student-Centered Design
AI’s transformative potential in education comes with urgent ethical responsibilities. The conference repeatedly emphasised that data privacy, equity, and autonomy are not just technical details but foundational to how schools adopt AI.
For example, AI tools that generate personalised learning exercises or grade assignments must align with clear policies:
Acceptable Uses: AI can support tasks like grammar checks, but should not complete work meant to reflect a student’s understanding.
Prohibited Practices: Clear boundaries prevent misuse, such as AI-generated assignments that undermine academic integrity.
Assessment Design: Define when AI can assist and when human judgment is essential, particularly for subjective tasks like essays or creative work.
Crucially, AI must enhance equity, ensuring that students from diverse backgrounds can access its benefits without creating new divides. Transparent communication with students and parents builds trust, ensuring that AI supports—not diminishes—the values of originality, creativity, and fairness.
At its core, the conference posed a powerful question: How can AI help us uphold what we value most in education? The answer lies in thoughtful integration, ethical practices, and a commitment to amplifying—not replacing—the human touch in learning.
Charting the Future of AI in Education
The message from the conference was clear: AI isn’t here to replace educators; it’s here to empower them. By embracing ethical frameworks, leveraging practical tools, and tailoring professional development, schools can ensure that AI serves their students, teachers, and communities effectively.
This is the future of education: where human expertise and artificial intelligence work hand in hand to inspire future learning.