PROGRAM

As part of the Australian Search Experience 2.0 project, we investigate how social, political, and cultural contexts shape interactions with critical information intermediaries. We aim to understand digital inequalities in accessing essential services, particularly in areas like health and social support. To study this at scale, we use generative AI to create diverse user personas, considering factors such as language, location, gender, political views, and cultural background. A key challenge is ensuring these personas reflect real-world diversity without reinforcing hegemonic frameworks. Through collaborative exercises, we will identify topics for longitudinal study, co-develop persona backstories for search simulations, and discuss validation strategies for building a balanced search query dataset. This workshop invites interdisciplinary collaboration to shape ethical, rigorous research on digital search and recommendation systems, grounded in equity, normative frameworks, and diverse perspectives.

Reimagine AI Policy Co-Design. Understand what AI policy means across various domains and contexts, and what considerations are important for democratising policy design for AI! 

Build Policy Together Using an AI Policy Co-Design Toolkit! Brainstorm and generate a diverse set of —current and near-future — AI use cases through a thumbnailing exercise! And use an AI Policy framework to assess these use cases — collaboratively designing policy artefacts to address these new and emerging use cases! 

Walk away with ideas about how to tackle AI policy challenges, a repository of AI use cases, and a collaborative toolkit that you can use to craft better policies in your field! Whether you are an AI researcher, a policy designer, or simply curious about the intersection of technology and governance — this workshop offers an invaluable opportunity to collaborative, innovate, and together make an impact!

Explanatory memoranda remain far too complex for the average literacy level of the Australian public, making it difficult for people to use these open documents to make change.

As part of my PhD research, I am building a small system using python which will take a federal government bill as input, and will output an explanation of that bill at a readability level specified by the user, producing a custom explanatory memorandum. This system uses retrieval augmented generation, open language models, and input from the user to develop the output. In this interactive session we will begin with a walkthrough of the tool, followed by guided exercises where participants can explore its successes and failures. Please bring a laptop for this session.

These initiatives have been in response to the challenges exposed by digital government failures, as exemplified by Robodebt, the new opportunities and risks of Generative AI, and AI governance developments internationally.

One in four women (23%) since age 15 have experienced domestic violence by an intimate partner (Australian Bureau of Statistics [ABS], 2023). AI and similar technologies are increasingly used in domestic and family violence services. Uses include chatbots (Brown 2017), risk assessment (McEwan 2019; Smee 2021; Douglas and Fitzgerald 2021), and GPS tracking of perpetrators (Nancarrow and Modini 2018). Knowing where, when, and how these technologies are used is essential to ensuring transparency and choice for service users—fundamental to trauma-informed, survivor-centred responses. At the same time, automated technologies have enabled new tools of abuse for those using violence, often referred to as technologically facilitated abuse. This includes digital stalking, spying, and the consensual sharing of fake or real intimate images. This panel will unpack the complexities of automation and gendered violence with key experts.

Many HDRs struggle with the workload, bureaucracy, publishing pressure, and imposter syndrome which comes with the territory. While these challenges are something even senior academics can relate to, students may feel that they lack informal, accessible avenues for guidance and support throughout their candidature.

This 90-minute workshop, designed for HDRs within ADM+S, aims to encourage collaboration and mentorship opportunities, while also providing a means of peer-support and connection. It combines the principles of speed dating (structured and rapid networking) with peer mentorship (mutual support and knowledge sharing), and also features an HDR-led panel where attendees can ask questions of HDR representatives from across various nodes, disciplines, and stages of candidature about the experience of being an HDR in the ADM+S. This workshop aims to leave participants with a broader sense of community, a stronger peer network, and practical insights into navigating their HDR journey.

Grasping these possibilities and problems is key. In this workshop, participants will be introduced to AI models, will see how other researchers use them, and will carry out hands-on “unmaking” activities using a custom card deck designed for experimentation and reflection. The workshop is intentionally “no tech,” requiring no devices, formal training, or prior knowledge of technical systems.

Each group will be comprised of 4–6 students to ensure meaningful participation and conversation. Mentors will guide discussions on a range of topics tailored to student interests and career development needs, including but not limited to:
-Research methodologies
-Writing and publishing
-Collaborating with research partners, policy makers, and the media
-Engaging with funders and preparing abstracts, and grant applications
-Communicating research to diverse audiences
-Researcher development and post-PhD career pathways
-Wellbeing and work–life balance

Based on these themes, students will sign up for a group aligned with their interests. Students will be contacted in advance of the symposium to highlight their interest in participating.