It’s been over two years since tools like ChatGPT first reshaped how researchers and professionals engage with text, data, and analysis. Generative AI (GenAI) tools now offer powerful capabilities from advanced search, idea generation, and summarisation to coding, data visualisation, and content editing. These tools are increasingly integrated into academia, government, and industry research environments.

But with great power comes great responsibility. GenAI systems can also produce inaccurate or misleading content, raise ethical concerns, amplify existing biases, compromise data security, and risk breaching intellectual property or cultural protocols.

Please join us for a hands-on, critical, and collaborative workshop to explore the opportunities and risks of using GenAI in research and research translation. Together, we’ll examine:

What GenAI can help us do better—and where it can mislead or fall short
How to use GenAI tools selectively, transparently, and responsibly
Real-world examples and practical tips from researchers across disciplines
How to align GenAI use with academic integrity, ethics, and best practices

This session will focus on large language models (LLMs) used for text generation and data visualisation, including tools like Claude, ChatGPT, and others.

Agenda:

9:30 AM – Welcome & Overview: The GenAI Landscape in 2025
Institutional access, tool options, data protection, and IP considerations

10:00 AM – Use Cases in Action: Research Applications of GenAI
Presentations and group discussion of real-world use cases

10:45 AM – Break

10:55 AM – Risks and Responsibilities:
Data ethics, algorithmic bias, attribution, and responsible AI use

11:20 AM – Limits and Strategies:
Cognitive framing, common pitfalls, and effective prompting

11:45 AM – Wrap-Up and Reflection

Who Should Attend:
Researchers, academics, and professional staff engaged in digital methods, research translation, knowledge mobilisation, or anyone curious about integrating GenAI tools into their workflows.

Workshop Facilitators:

Dr Owen Forbes, CSIRO CERC Fellow
Dr Forbes is a translational data scientist, passionate about using data communication to build bridges between evidence and impact. He applyies data science as a transformative and impactful avenue for social good, community wellbeing and scientific discovery. Dr Forbes is a CERC Postdoctoral Fellow at CSIRO working on data science applications to solve significant science questions, and deliver new applications, tools and analytical approaches to utilising specimen-based biological data.

Dr Bernadette Hyland-Wood, QUT Centre for Data Science Research Fellow & CSIRO Affiliate
Dr Bernadette Hyland-Wood is a Research Fellow at the Centre for Data Science, Queensland University of Technology, specialising in responsible data science and deploying generative AI technologies. Her research explores the adoption of rapidly emerging AI platforms by regulators and industry, focusing on data ethics and governance. Her work bridges academia, industry, and policy, emphasising research translation incorporating responsible AI and data-driven decision-making. Dr Hyland-Wood is a CSIRO Affiliate and serves on the Social Science Human Research Ethics Board (CSSHREC).

An online meeting link will be provided closer to the event date.