My memory of debating goes back to high school, where it mostly involved not losing your palm cards and sitting in starchy formal school uniform as you faced a broadly indifferent or occasionally baffled audience of your adolescent peers. Thank goodness, times have changed.
The Big Debate was the launch event for UTS Open Education Week, with a topic that drew an audience of 40+ attendees from within and beyond our UTS circles. Unlike some of our school experiences, this event was tightly managed and beautifully delivered, with lively, confident speakers and engaged participants making full use of the chat function and online polling from start to finish.
The provocation that kept us glued to our screens for a full hour was this:
“Generative AI is fundamentally incompatible with Open Educational Practices”
Basically, if Generative AI is changing how we teach, learn, and share knowledge, where does that leave Open Educational Practices and the values of access, equity, and collaboration? There was a lot to get into, and our guest speakers were ready.
Terms of engagement
Our Open Education Week organiser Mais Fatayer chaired the debate, assisted by Janet Wang, Jenny Wallace, and Helen Chan. Our debating teams were:
- Affirmative team: Claire Ovaska and Nikki Anderson (University of Southern Queensland).
- Opposition team: Sarah Steen and Lauren Halcomb-Smith (Deakin University)
For those playing along at home, our terms of reference were:
“Open Educational Practices (OEP) refer to the design of learning experiences that integrate open educational resources (OER) and open licensing to foster collaboration, knowledge sharing and learner agency. The benefits of OEP include significant cost savings and better educational outcomes for learners, greater pedagogical flexibility for educators as well as support for more inclusive and equitable learning environments.” (Jhangiani & Jhangiani, 2024)
“Generative AI is a type of artificial intelligence (AI) that uses machine learning algorithms to produce, copy or rework content. This content output can be text, image, audio, code, or other formats.” (UTS Library, 2026)
Watch the full debate here, or read on for a short summary of how it all unfolded:
Affirmative: GenAI and OEP are fundamentally incompatible
On the ‘affirmative’ team, Claire and Nikki identified GenAI as a whole mechanism – inclusive of both the tools and the training of the tools. GenAI was considered here to be a ‘black box’, and therefore misaligned to core OEP principles of transparency, attribution, and ethical reuse. With its lack of accurate, meaningful citation it becomes an unreliable source of information, rendering it uncompliant with the governance that other sources must adhere to.
OEP relies on shared, accessible information, with reuse requiring attribution and adherence to agreed upon terms. In contrast, GenAI turns open sharing into a one-way transactional extraction without consent or attribution for the creator. Furthermore, the team noted that GenAI creates equity risks and may worsen the digital divide due to costs involved, firewalls and other barriers to accessibility. Biases in Gen AI outputs reflect dominant languages, cultures, and institutions, amplifying visible voices and marginalising others. They maintained that in today’s Australian legal reality generative AI is not compliant with our copyright laws.
For GenAI to be compatible with Open Educational Practices, systemic change would be needed: consent-based training, enforceable attribution, and fair compensation/ licensing reforms. The team highlighted that OEP provided a lens of agency and power due to conscious choices made for use and adaptation, illuminating education for the public good, access to high quality information, and a cultural reality that underpins learner needs. They argued that GenAI conflicts with this transparency; it claims to be innovative but in fact is riffing off the creative work of authors without permission or compensation.
Opposition: fundamentally, GenAI is open…
On the ‘opposition’ team, Sarah and Lauren took issue with some semantics and identified chinks in the other team’s definitions, as good debates often do. “Fundamentally incompatible” was a very strong claim, they asserted, and to say that GenAI and Open Education are “unable to work together in any meaningful way” is a step too far. In particular, they contended that education is an evolving landscape that has had to adapt to new tools and technologies, citing parallels from recent and long past history such as the printing press, the calculator and the internet. The common fear of incompatibility in these instances had not broken or caused lasting damage to the process of education.
Whilst the opposition agreed with the formative assertion that OEP has a deep purpose to offer equity and access, they suggested that this ‘openness’ should also open doors and engage with AI, which is already embedded in education (whether we like it or not!). There are issues to acknowledge with GenAI, but this does not mean it is fundamentally incompatible with OEP. The problems of transparency, attribution and bias should not create incompatibility and could be ironed out with better governance. The team agreed that learners should be central to the educational process, with GenAI providing a platform for learners to access and engage with Open Educational Resources.
Focussing in particular on the equity arguments, they shared several student vignettes to show how GenAI can help learners to manage equity needs, not exacerbate them. GenAI can be a practical solution for issues with language, format and information processing, effectively expanding access to those whose needs are not being met by current educational materials and services.
So that leaves us…
I keep moving back and forth to each side as everyone’s arguments are so good!
Debate audience member
Ultimately, the discussion surfaced some enduring tensions that belied a definitive verdict. Both positions were rigorously defended, with a Mentimeter poll showing the audience shifting position slightly, but ultimately to a very balanced view of both sides. The discussion closed without a clear winner, but there was a sense that given time to resolve issues of integrity with creator and learner input, the two systems could be aligned and integrated ethically.
Further audience comments showed how complex (and engaging!) the discussion was:
Excellent debate! The relationship between OE and AI is complicated. Already most content on the internet is AI generated and soon AI will just recycle its own content and be unable to distinguish new ideas from noise. The only way to prevent AI model collapse is to train AI models on bespoke data. I think OE will play an important role in this training and there will be immense value in human curated open resources. OE can be the saviour of AI.
Julian Pakay, La Trobe University
Brilliantly debated by both teams – I had heaps of fun and have a lot to reflect on ‘the mechanism of openness’ and how that might be changing.
Jenny Wallace, UTS
The session was well summarised by Claire Ovaska, from the affirmative team:
I think we’re actually all winners today because it’s not about one side or the other. This is what universities do well, isn’t it? We debate all of the sides, we get diverse perspectives in together.
Read more about the other events at Open Education Week at UTS and what’s happening with open education at other universities in Australia and around the world.