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GenAI for Social Science Research Workshop Reflections
Rafat
Research Fellow
Attending the GenAI for Social Science Research workshop in Brisbane was a genuinely thought-provoking experience that I did not expect to find so challenging, in the best possible sense. The morning session, led by Distinguished Professor Bronwyn Carlson and Dr Tamika Worrell, framed artificial intelligence through the lens of Indigenous peoples and relational futures. It was a sobering and necessary starting point. The session made clear that AI is not a neutral tool: it is built on data ecosystems that can extract, misrepresent, and commodify the knowledge and cultural property of Indigenous and marginalised communities, often reproducing the very colonial structures that have historically caused harm. The financial and environmental costs of running AI systems, costs that are rarely visible to the end user, were also brought into sharp focus. I left morning tea feeling quietly unsettled, which in hindsight was exactly the right frame of mind to carry into the afternoon.The afternoon session, hosted by Carl Knox, shifted the tone entirely, offering a practical and energising walkthrough of AI tools relevant to social science researchers. On its own, I think I would have found it straightforwardly useful and simply moved on. But because I had spent the morning grappling with questions of whose knowledge AI draws on and who bears the costs of its convenience, I found myself engaging with the practical content in a very different way. Every demonstrated use case carried a quiet counterweight: is this worth it? Who might be affected by how this model was trained? Am I being a thoughtful or a careless user of this technology? That critical perspective made the afternoon richer rather than more paralysing, and I appreciated that the workshop was structured to create exactly that kind of tension.What I take away from the day is less a list of tools and more a way of thinking, a sense that using AI responsibly in research is not simply a matter of accuracy or efficiency, but of ethical accountability. The two sessions were clearly designed as a pair, and the sequencing was deliberate and effective. It would have been easy to run a practical AI workshop for researchers and leave everyone feeling empowered but uncritical. Instead, the day asked us to hold both things at once: genuine enthusiasm for what these tools can offer, and genuine responsibility for what their use costs, in carbon, in cultural harm, and in the consolidation of power that already powerful systems tend to produce. That is a harder position to maintain than pure scepticism or pure optimism, and I believe it is the right one.
Freya
Research Fellow
Reflecting on my experience of the two days of events relating to the use of GenAI, it struck me how broad the spectrum is of both the use cases of AI models, as well as the perspectives on its place in society and social science research. We were lucky enough to hear from some of the leading minds on GenAI and each presenter brought a unique and deeply critical view on how it should be used. The connecting narrative between each of the presenters was the clear power and increasing presence that AI has in our lives, whether that be through the services we access, the way we learn, or how we conduct research.
Distinguished Professor Bronwyn Carlson and Dr Tamika Worrell highlighted the significant ethical issues with using GenAI, highlighting the term ‘Algorithmic Settler Colonialism’ and posing questions like ‘how can technology be accountable to community?’ and ‘who governs data?’. These questions, along with the activities that asked us to think critically about if we should use AI in our research, provided an opportunity to reflect on how our society is shaped by technology. This workshop, along with the presentations from Professor Shonali Krishnaswamy and Dr Carl Knox, left me with the question – where does my ethical line in the sand sit when it comes to AI tools. Weighing the harm GenAI can cause against the potential benefits of these models as accessibility tools has left me feeling torn, and I will continue to reflect on this balance in the weeks and months to come.
Mariel
CEVAW Affiliate
My highlight from the session was the sobering realisation that being oblivious of the harms of AI comes from a position of privilege which continues to be unknown and disacknowledged by most users. For researchers like us, the use of Gen-AI, especially in well-resourced institutions may offer real productivity gains, but the session highlighted the risks of deepening existing colonial oppression from hierarchies of knowledge. The Kahoot quiz reinforced this learning where we had to distinguish between human-made or AI-generated First Nations artworks which proved difficult and after a few rounds the task seemed impossible. Though the activity was light-hearted, it made me realise that the line between tool and threat is more blurry than I had appreciated before attending this seminar. I was very quickly realising potential implications for misinformation, disinformation, and who really holds the power in ensuring accountability for the cost to country and the communities that are deeply affected.
Helen
Research Fellow
The central tension I left this workshop with is not simply that AI can be beneficial or harmful, but that it made something visible that many are overlooking in their everyday lives: who benefits and who is harmed by AI is not evenly distributed. Distinguished Professor Bronwyn Carlson and Dr Tamika Worrell made this uncomfortably clear: the people most likely to be hurt by AI are those who already carry the greatest burden of structural disadvantage, not just individuals, but communities and country. That framing has stayed with me. It has also sent me back to the literature, looking specifically at how AI intersects with colonial structures and gender-based violence, and what this means for girls, women, and gender-diverse people who bear its disproportionate impacts. What I hope the workshop changes is not just awareness but practice. For those of us who use AI in our research or daily life, the question worth sitting with is: whose interests are we centring when we make these choices, and whose are we inadvertently sidelining?
Faroo
Research Fellow
Attending the workshop as a feminist from a marginalised background, and as someone who works and writes in a second language, I was struck by both the promise and the tension of these technologies. On one hand, AI offers a powerful tool, such as helping me refine language, correct expressions, and participate more confidently in global academic and policy conversations. Yet, through a standpoint lens, my experience also sharpened critical questions of ethics and power. I became acutely aware of the absence of marginalised voices in the database that shapes these systems, and how this absence quietly reproduces dominant narratives as if they were universal truths. Equally important was learning from Indigenous experts, who reminded us that the impacts of AI are not abstract: they are material, environmental, and shared. The extraction of resources, the strain on water and land, and the disproportionate burden on Indigenous communities is not only their issue; it is a collective one that demands broader accountability. For me, the workshop was not just about understanding AI’s potential, but about confronting the ethical responsibility of how I will use it and how I can remain grounded in feminist principles, amplify excluded voices, and consciously work to minimise harm environmentally and intellectually.
Xueyin
CEVAW Affiliate
At a time when avoiding AI in research feels increasingly untenable, CEVAW’s workshop on generative AI offered a timely intervention. Across the day, two seemingly contrasting orientations emerged: a critical, ethically grounded interrogation of AI’s impacts, and a pragmatic exploration of its potential to enhance research practice. Rather than being in tension, I came to see that they delivered just the right messages we needed to hear.
That message, as I understand it, is this: we need to consider the ethics of using these tools—grounding decisions in the tangible impacts each
AI query has on our environment and humanity—while also remaining attentive to how they can enhance our learning and agency as researchers. The challenge is to hold both commitments together simultaneously.
The morning keynote and workshop, led by Indigenous scholars Dr Tamika Worrell and Distinguished Professor Bronwyn Carlson, offered a powerful reframing through a relational lens grounded in Indigenous expertise. They asked what it might mean for AI to support, rather than erode, a relational future. Their analysis of generative AI as an extension of colonial extraction—captured in the concept of algorithmic settler colonialism —was both confronting and clarifying. AI systems, as they showed, can reproduce longstanding patterns of exploitation: through data extraction, mis/dis-information, surveillance, and the ongoing exclusion of Indigenous communities from decisions that directly affect them.
They also foregrounded the necessity of Indigenous governance and leadership in shaping AI systems, and invited reflection on our individual responsibilities. One question has stayed with me: what will each of us do to resist data colonialism and its consequences?
I left with a sharpened ethical awareness. A relational perspective asks us to attend not only to outcomes but to relationships, including the labour displaced by AI and the need to uphold digital sovereignty, cultural integrity, and community-defined priorities. More immediately, Dr Worrell’s prompt lingers with me. Every query we enter into a chatbot carries a material cost, drawing on water and energy often sourced from Indigenous lands. This reframes even small, routine uses of AI chatbot as decisions with ethical weight. It prompts a simple question: is this use necessary?
The second half of the day—led by creative technologist
Carl Knox—offered a striking contrast. His workshop encourages us to use generative AI to enhance research. In this framing, AI does not replace expertise—it amplifies it. His advice on transparency offers a useful heuristic on how to maintain integrity and intellectual ownership:
“Know how you got to where you are. If you aren’t proud of what you did in the end, then you have probably given away too much agency.” – Carl Knox
What ultimately connects the two halves of the workshop, despite their differing tones, is a shared insistence that ethics and intention must remain in the driving seat. This workshop has helped me make more conscious decisions about aligning my use of AI with my ethical commitments, while sustaining a hopeful outlook toward a more humane, relational future—with AI as a companion rather than an adversary.
