Recently Education Horizons’ Advisory Board* discussed how Generative AI can and should impact education. This blog outlines that discussion and some of the key considerations for educators and policymakers in navigating this truly revolutionary technological shift.
Creative destruction – Technology, Society and Education
Without needing the skills of a trained data scientist, Generative AI gives everyone the ability to access and draw meaning from the total sum of recorded human information. The power of this technology to change and reshape the world we live in is almost without parallel.
Gen AI represents the most recent in a series of creative destruction waves made possible by the internet – beginning with Search capability, followed by Social media, followed by Mobile technologies and now Gen AI. This most recent wave will change business models and make whole sectors disappear.
The initial suite of Gen AI tools are great generalists. A key question currently being explored is what happens when this technology is applied to data in a specialised area – via a “walled garden” model.
Importantly, the emergence of Gen AI appears to be one of the first times that Governments around the world have moved at a similar pace to new technology to begin creating new regulatory environments. The pace of change means mistakes will be made, but this work is critical based around fundamental questions of ethics including:
- How will the technology be used and how will our information be gathered and used?
- How will this technology impact wider trends and challenges such as Data Sovereignty and Culture change through economic upheaval – changing jobs, roles and sectors
Organisational leaders are grappling with two different sets of challenges in the face of Gen AI. The first is the short term or tactical question: How do I bring this technology into my organisation to get short term benefits? The second is the long-term strategic question: What is this tech going to do to my sector and the way my organisation works in the future?
The pace of evolution in Gen AI is extreme and bets made by leaders today will have fundamental impacts for the long-term
Short-term and Long-term impacts on Education
Generative AI has the potential to significantly reshape education in terms of both practice in schools and classrooms as well as the education market itself.
Gen AI is already directly impacting education content creation including:
- Companies creating text-book and online learning materials have already seen Gen AI perform these tasks at a comparable and higher level at low or no cost to users
- Unit and Lesson planning is being supported by Gen AI tools – saving significant amounts of teacher time and supporting more consistent and coherent teaching and learning
- There is scope for this to immediately impact almost every area of content within the teaching and learning space from the creation of classroom materials through to student assessment materials and student academic report generation
- Students are using Gen AI to create content for submission and assessment – where Gen AI is used openly and where its use is hidden from teachers and assessors
In the medium-term Gen AI has the potential to significantly impact education through school analytics including:
- Interrogating data to identify critical trends and patterns across individual students and groups of students
- Interrogating workflows, identify recommended next steps and potential process improvements to increase efficiency and efficacy in schools
In the longer-term Gen AI has the potential to impact education through hyper personalisation including:
- Interrogating student data to identify their individual learning needs
- Generating personalised learning content to meet individual student needs including the optimal pace and sequence of learning
- This level of hyper-personalisation has the potential to be delivered at limitless scale, for all students at the same time
These potential short, medium and long-term impacts raise some fundamental questions around human interaction with Gen AI and the changing shape of our education system. Traditional education models which “front-load” learning – where students finish learning before they start working are likely to increasingly conflict with the place and role of Gen AI in education. The capacity of Gen AI to subvert these models has significant implications for both the higher education and senior high school parts of the education system.
At the same time the “social construct” at the heart of K-12 education presents a significant bulwark against wholesale structural change led by new technologies. As a community we accept that schools will take students for 300 minutes per day, five days per week, 40 weeks per year – providing a direct human social interaction and community which is highly valued and seen as fundamental to each young person’s development.
In practice this has often meant that schools have been slow to take up technology solutions – supply side pressures have tended to be met with apathetic and inconsistent demand. However the sheer time-saving benefits of Gen AI today, and its longer term potential to support deeper relationships between teachers and learners has the potential crash through this traditional barrier to new technology uptake in schools. Realising this potential in schools will fundamentally depend on how schools can balance the evident benefits of Gen AI with the core human interactions at the heart of schools and the learning they support
The human space in Gen AI Education
An important starting point for exploring balance between human interaction and Gen AI in education is the fundamental role of humans in Gen AI itself.
Gen AI depends entirely on the creation of knowledge by humans. In the absence of human-created knowledge, Gen AI tools will refine their interrogation of a limited knowledge-base, in turn limiting their evolution and development. In order for Gen AI to learn and grow, there will always be need for new information created by humans. How humans create “the new” will continue to be central to our world. Supporting young people to use existing knowledge to create new knowledge has always been central to teaching and learning and will remain so in the time of Gen AI.
Gen AI tools are imperfect in their interpretation of knowledge: Gen AI tools today are often described as 80 per cent accurate / 20 per cent inaccurate. There is and will continue to be a critical role for humans to verify Gen AI created content. Even as inaccuracy diminishes, it will never disappear – making the human role of knowledge verification increasingly critical. As with knowledge creation above, the ability to assess and verify sources of information has always been central to teaching and learning and will become increasingly so as Gen AI utilisation increases.
Gen AI exists to respond to specific questions. The generalist and emergent nature of Gen AI today has driven rapid growth in information about how best to prompt Gen AI tools to generate the required responses. This includes working with Gen AI to continually refine and shape it’s responses – learning how best to guide the technology while the technology learns how best to understand requests made of it. It is likely that this emerging human skill-set will continue to grow in significance as Gen AI moves further and further into daily life.
Where to from here?
We are already seeing universities shift their focus away from whether students use Gen AI, toward students sharing how they use Gen AI – including demonstrating how their depth of content understanding shapes the questions and prompts they use with Gen AI. Similarly, students are increasingly being tested on their ability to respond to and build on Gen AI content – including assessing its accuracy and relevance while using it as a launching point for their own work.
Bloom’s taxonomy provides a useful framework to explore how great teaching and learning in a K-12 context is likely to be refined by the advent of Gen AI in schools. At one end of Bloom’s scale, Knowledge, Recall, Understanding and Comprehension is likely to be “blown out of the water” by Gen AI – pushing these capabilities toward the background of student learning over time. But at the same time Analysis, Synthesis and Evaluation skills will become more and more important as Gen AI moves further into our lives and our classrooms.
No matter how far and deep this new technology integrates into schools, we will always need great teaching and learning to unpack what this and future technologies can do for us. And the essential social and communal nature of schools will remain a critical incubator for the types of new knowledge creation and skills that Gen AI will depend on for its own evolution.
This suggests Gen AI will become a part of teaching and learning in a way few other technologies have before it – based on a deeper and deeper focus on the human relationships and interactions at the heart of education.
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*This document reflects the invaluable contribution made by each individual member of the Education Horizons Advisory Board. Members of this Advisory Board participated in discussions that contributed to the development of this document. However, being listed as a member of this Advisory Board does not constitute or imply endorsement in whole or in part of the views and/or recommendations expressed in this document.
- Chris Wardlaw (Chair): Deputy Chair, Australian Institute for Teaching and School Leadership
- Mark Cameron: CEO Alyve, NED Simpatico Ai
- Dr Amelia Scholes: Chair, APS College of Clinical Neuropsychologists
- Allan Dougan: CEO, Australian Association of Mathematics Teachers
- David Ensor: CEO, Australian Psychology Accreditation Council (APAC)
