This morning I discussed this topic with colleagues from King’s Natural, Mathematical and Engineering Sciences faculty. The session was recorded and a transcript is available to NMES colleagues but, as I pointed out in the session, AI is enabling ways of enhancing and/ or adding to the alternative ways of accessing the core information. By way of illustration the post below is generated from the transcript (after I sifted content to remove other speakers.) The only thing I edited was the words ‘in summary’ from the final paragraph.

TL:DR Autopodcast version

Slides can be seen here

Understanding and Integrating AI in Teaching

Martin Compton’s contribution to the NMS Education Elevenses session revolved around the integration of AI into teaching, learning, and assessment. His perspective is deeply rooted in practical application and cautious understanding of these technologies, especially large language models like ChatGPT or Microsoft Co-pilot.

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My approach towards AI in education is multifaceted. I firmly believe we need a basic understanding of these technologies to avoid pitfalls. The misuse of AI can lead to serious consequences, as seen in instances like the professor in Texas who misused ChatGPT for student assessment or the lawyer in Australia who relied on fabricated legal precedents from ChatGPT. These examples underline the importance of understanding the capabilities and limitations of AI tools.

The Ethical and Practical Application of AI

The heart of my argument lies in engaging with AI responsibly. It’s not just about using AI tools but also understanding and teaching about them. Whether it’s informatics, chemistry, or any other discipline, integrating AI into the curriculum demands a balance between utilisation and ethical considerations. I advocate for a metacognitive approach, where we reflect on how we’re learning and interacting with AI. It’s crucial to encourage students to critically evaluate AI-generated content.

Examples of AI Integration in Education

I routinely use AI in various aspects of my work. For instance, AI-generated thumbnails for YouTube videos, AI transcription in Teams, upscaling transcripts using large language models, and even translations and video manipulation techniques that were beyond my skill set a year ago. These tools are not just about easing workflows but also about enhancing the educational experience.

One significant example I use is AI for creating flashcards. Using tools like Quizlet, combined with AI, I can quickly generate educational resources, which not only saves time but also introduces an interactive and engaging way for students to learn.

The Future of AI in Education

I believe that UK universities, and educational institutions worldwide, face a critical choice: either embrace AI as an integral component of academic pursuit or risk becoming obsolete. AI tools could become as ubiquitous as textbooks, and we need to prepare for this reality. It’s not about whether AI will lead us to a utopia or dystopia; it’s about engaging with the reality of AI as it exists today and its potential future impact on our students.

My stance on AI in education is one of cautious optimism. The potential benefits are immense, but so are the risks. We must tread carefully, ensuring that we use AI to enhance education without compromising on ethical standards or the quality of learning. Our responsibility lies in guiding students to use these tools ethically and responsibly, preparing them for a future where AI is an integral part of everyday life.

The key is to balance the use of AI with critical thinking and an understanding of its limitations. As educators, we are not just imparting knowledge but also shaping how the next generation interacts with and perceives technology. Therefore, it’s not just about teaching with AI but also teaching about AI, its potential, and its pitfalls.