‘Generative AI and Education: Digital Pedagogies, Teaching Innovation, and Learning Design’ by B. Mairéad Pratschke delves into the potential impact of generative AI (GAI) on education. This book, part of the SpringerBriefs in Education series, explores how GAI can influence teaching practices, learning design, and assessment, shedding light on the evolving landscape of AI-powered education. As someone deeply interested in the intersection of AI and ethics and having been influenced by the works of Nick Bostrom, a philosopher known for his work on existential risks and superintelligence, and Stuart J. Russell, a leading AI researcher and author of ‘Human Compatible: Artificial Intelligence and the Problem of Control ‘, this book immediately caught my attention. Its promise to address GAI integration’s pedagogical and practical aspects resonates with my desire to understand how ethical considerations can be translated into actionable strategies within educational settings.

My interest in AI and ethics stems from a long history of teaching AI and ethics in computer science and my fascination with AI’s potential to reshape education and society. The works of Bostrom and Russell, with their exploration of existential risks and the need for human control over AI systems, have profoundly shaped my thinking. This book’s comprehensive exploration of the potential societal impact of GAI, specifically its focus on the need to develop strategies for mitigating its possible negative consequences, resonated deeply with my personal beliefs and concerns. The book’s focus on a human-centred approach to AI, prioritising well-being, equity, and critical thinking, aligns perfectly with the ethical principles I have worked on in IT and ethics for many years.
Quick thinking
Reading this book was a thought-provoking and, at times, unnerving experience (AI in education, especially assessment, is full of ethical dilemmas). The book’s exploration of GAI’s rapid evolution and educational impact filled me with a greater sense of purpose. The sections on AI literacy and the need for a human-centred approach reinforce my belief in the importance of ethical and highly contextual considerations in AI development and deployment in education. The book’s fast-paced narrative, mirroring the rapid advancements in the field, kept my interest throughout, effectively conveying a sense of urgency regarding the need for educators and policymakers to adapt quickly to the transformative potential of GAI with workable solutions.
However, the book’s swift exploration of complex technical concepts, such as the mechanics of large language models (LLMs) and concepts like Retrieval-Augmented Generation (RAG), occasionally presented an attention deficit (and did the book’s many educational frameworks, ouch!). While the author strives to make these concepts accessible to a non-technical audience, a more thorough exploration of these technical aspects and their more profound link to educational theory would have been beneficial for readers like me who are interested in the inner workings of GAI so I can critique it.
The medium is the message.
The book’s central message is clear: GAI is not just a new tool but a transformative force requiring a paradigm shift in education. It compels us to embrace a new model where humans and AI collaborate to design and deliver learning experiences (Ethan Molluck’s book. Co-intelligence: Living and Working with AI echoes this claim). This message aligns with my work in AI and ethics, particularly emphasising critical and active human-centred AI and responsible development (i.e. ‘human in the loop’). This collaborative approach, termed “Generativism”, necessitates a shift in mindset and pedagogical practices. It challenges us to re-evaluate assessment strategies, moving from assessing output to evaluating the learning process.
The book also provides a valuable perspective on the importance of AI literacy for educators and students. Pratschke stresses that AI literacy encompasses
- technical understanding,
- ethical considerations,
- critical thinking skills, and
- the ability to assess AI’s limitations.
By understanding how GAI works, its capabilities, and its limitations, individuals can make informed decisions about its use and contribute to its responsible development and deployment within educational settings. The book encourages the development of AI literacy among educators and students, reflecting the ideas of Stuart J. Russell and many in the broader AI safety field who support the assurance of human control over AI systems.
Historical context
The book excels in framing GAI within the historical context of educational technology, tracing its development from early intelligent tutoring systems to modern adaptive learning platforms. This historical perspective helps contextualise GAI’s emergence and allows a more informed understanding of its potential impact. However, the book’s swift exploration of these concepts could benefit from more in-depth explanations in certain sections (and perhaps this is the natural limitation of the SpringerBriefs series). Additionally, while the book provides a solid theoretical framework, it could be enhanced by including more detailed examples of specific GAI tools and their practical applications in various subject areas. Concrete examples and case studies would bolster the book’s practical value for educators seeking to implement GAI in their teaching (and the book is screaming for a good learning designer, i.e. think points, summaries, and practice opportunities).
“Generative AI and Education” is an essential resource for educators, educational technologists, policymakers, and anyone interested in understanding how AI is transforming the academic landscape. It offers a thought-provoking overview of GAI’s potential, emphasising the need for responsible development, AI literacy, and a human-centred approach. The book’s insights into generative learning design and assessment strategies are particularly relevant for educators seeking to adapt their teaching practices to this new era of learning, equipping them with the knowledge and tools necessary for this transition.
References
Pratschke, B. M. (2024). Generative AI and education: Digital pedagogies, teaching innovation and learning design. SpringerBriefs in Education. https://doi.org/10.1007/978-3-031-67991-9
Mollick, E. (2024). Co-intelligence: Living and working with AI. Penguin.
Nick Bostrom: Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
Stuart J. Russell: Russell, S. (2019). Human compatible: Artificial intelligence and the problem of control. Viking.
AI Writing Statement and Citation
This literature review was conducted with the assistance of Google NotebookLM, a personalised AI research assistant using Google’s Gemini model, to enhance research efficiency and streamline information synthesis.
Google LLC. (n.d.). Google NotebookLM. Retrieved October 10, 2024, from https://notebooklm.google.com/
NotebookLM functions as a research collaborator. It uses retrieval-augmented generation (RAG) to access and process information, which improves accuracy and reduces the likelihood of errors. Google NotebookLM was instrumental in organising and synthesising information from various sources. It assisted with summarising findings, identifying key themes, and generating text.
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