Introduction

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I'm a primary school teacher, and this book came from nothing other than a deep care and concern for the students who look back at me in our classroom.

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Why this concern? Put aside any sci-fi tech fears or narratives that are swelling around AI at the moment, and there is one common, abiding, and almost irrefutable truth that everyone arrived at regarding generative AI. That it will fundamentally change not only the culture but also the nature of work in countless ways as extensively documented by researchers such as Brynjolfsson and McAfee (2014) in their seminal work on the second machine age and confirmed by recent OECD (2023) analysis on AI's impact on global labor markets.

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As Ian Dunt mentioned in the podcast "Origin Stories", predictions and hopes about AI have been wildly optimistic and the timelines off by years, decades, or more each time. Yet the advent of ChatGPT in November 2022 was a very strange and irrational occurrence. It was the complete opposite of at least 100 years of unfulfilled dreams. Instead, it actually came too soon.

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Anyone who can remember the first time they used it will recognise that feeling they had. Perhaps similar to the first time the internet was experienced, but far more personal. Freud talked of the feeling of 'uncanny' as the effect of things that are strangely familiar—like dolls or wax figures—things that blur the line between the real and the unreal. Here was a machine that talked back to us. Two years on, and this morning my 9yo daughter was prompting Chat GPT to create completely photorealistic new fluffy animals. The tech has moved on almost by the hour since 2022, but instead of subsiding, the uncanny feeling seems to stick around. Uncanny, but also a strange unease, like talking to a long-dead friend or relative in a dream.

So where do you go when you are faced with something perplexing? You head to those who you think might be experts, who can collate and summarise the data and give us rational-sounding answers. These are experts and academics usually in the first case and maybe government departments or trusted corporations in the second case.

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In my own observation of these sources, there have been two themes throughout:

1. A nascent attempt to find meaning in what's happening by talking about the fake skills that AI could achieve.

2. A strange need to temper optimism regarding AI's effect on education.

I don't know why, but it's almost like this is a question too big to approach. This book will attempt to fill this gap. There is no point in providing a snapshot of where we are at, as there is general recognition that by the time you finish that sentence things have moved on. Rather, it aims to provide a reality check for schools and institutions that seem to be also approaching the technology as if it's just another tool, or a way to gamify lessons, or even more limply help teachers with their admin.

Toby Walsh had seen a lot in the 40 years as an AI researcher and professor. When asked what surprised him, he said in his seminar in 2025 that everything appeared as usual, but he worried that AI is like a tsunami that's approaching and everyone is looking the other way. He also was surprised by the sheer scale of investment (at that point a billion dollars per day) that was being poured into the tech—a perspective supported by the McKinsey Global Institute (2023) report estimating that generative AI could add $2.6-4.4 trillion annually to the global economy.

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This book is an attempt to turn around and face the tsunami with a holistic, system-wide perspective. It aims to cut through the trivialization that seems to be propelled by institutional responses, and face the implications head-on and with as much honesty as possible. As Holmes et al. (2019) argue in their comprehensive framework for AI in education, we need to consider the full implications and potential of these technologies rather than merely their instrumental applications.

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The education system is naturally, like any human social network, based on inherently hierarchical structures. I believe that there is a resistance to acknowledge the impact of the technology across the board, mainly due to the fear inherent in this hierarchy. Christensen et al. (2015) have extensively documented why established institutions struggle to adapt to disruptive technologies, and Zhao (2022) specifically identifies how education systems resist change precisely because of their hierarchical structure. Look at any department of education website or school website or in fact university research website and try to find references to artificial intelligence. I am currently completing a university course in differentiating pedagogy for diverse learners such as EAL/D etc. AI is absolutely tailor-made for assisting in this. Recent research by Escueta et al. (2023) confirms this through meta-analysis, showing emerging evidence for AI-assisted differentiation for diverse learners. Basic applications would be instant translations or voice of PowerPoints via an iPad for students, or being able to instantly adapt the content for learners from multiple skill levels or cultures.

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In 8 weeks of lecture materials, endless academic reading and tutorials, do you think there has been one mention of AI? Correct.

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There is a fear in the management of these institutions of AI's transformative effect, and so ignoring it or pretending that it will have minor effects is the quickest way to not endanger your position in the institution. Selwyn (2023) examines precisely this disconnect between technological advancement and educational institutions' responses in his work on educational futures in the age of AI.

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Teachers and educators in the classrooms can see how quickly the students are adapting and moving into the new tech, something I will talk about later, but there seems to be the fear that if it is mentioned to a supervisor or manager, you will be seen as a troublemaker or worse, a crank, and subsequently ignored. This gap between student adoption and institutional response is well-documented by Luckin and Cukurova (2023), who found that students are already using AI tools regardless of institutional policies, a finding further supported by recent Pew Research Center (2023) studies showing rapid adoption of AI tools among youth. As you can probably guess, I had this experience myself in a public school, where I chose every channel I could to raise awareness. Emails went unanswered, which is not unusual, but staffroom discussion was met with suspicion, and staff meeting discussion was met with being quickly shut down to talk of more important things.

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This book will hopefully help others like me, providing practical guidance and ideas for teachers navigating this uncharted territory and explore the transformative potential of artificial intelligence in primary education. In this effort, we will draw on frameworks like those proposed by Dede (2022) for rethinking education completely for the AI era, and UNESCO's (2023) guidance for educational institutions implementing AI technologies, with particular attention to Warschauer and Tate's (2022) concerns about how AI could either mitigate or exacerbate existing inequalities in education.

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References

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W.W. Norton & Company.

Christensen, C. M., Raynor, M. E., & McDonald, R. (2015). What is disruptive innovation? Harvard Business Review, 93(12), 44-53.

Dede, C. (2022). The 60-year curriculum: New models for lifelong learning in the digital economy. Routledge.

Escueta, M., Quan, V., Nickow, A. J., & Oreopoulos, P. (2023). Education technology: An evidence-based review. Journal of Economic Literature, 61(1), 1-58.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Luckin, R., & Cukurova, M. (2023). AI and education: Promise and implications. British Journal of Educational Technology, 54(1), 42-60.

McKinsey Global Institute. (2023). The economic potential of generative AI. McKinsey & Company.

OECD. (2023). The impact of artificial intelligence on the labour market. OECD Publishing.

Pew Research Center. (2023). Teens, technology, and AI. Pew Research Center.

Selwyn, N. (2023). Educational futures: Learning in the age of AI. Routledge.

UNESCO. (2023). AI and education: Guidance for policy-makers. UNESCO Publishing.

Warschauer, M., & Tate, T. (2022). Digital equity in education. Review of Research in Education, 46(1), 297-334.

Zhao, Y. (2022). Toward autonomy-oriented education: An education revolution for the AI age. Educational Philosophy and Theory, 54(6), 845-857.