ChatGPT use in Australia shows strong work focus and local topics
How People Use ChatGPT in Australia: A WildChat Analysis
Human-Computer Interaction
Summary
Generative AI chatbots like ChatGPT are becoming part of daily life worldwide, but this study looks specifically at how people in Australia use it. The authors analyzed nearly 38,000 real conversations and found that Australians tend to use ChatGPT mainly for work-related tasks and action-oriented interactions. The study also revealed conversations in multiple languages and increasing use for personal expression over time. Many chats referenced Australian laws, institutions, and cultural topics.
What this means in practice
- •For ai product designers: Design AI chatbots with better understanding of Australian legal, cultural, and public service contexts to improve local user relevance.
- •For multilingual software developers: Develop chatbots that support multiple languages to meet diverse Australian user needs shown in real-world interaction data.
Tested on one dataset.
Authors
Ying Ma, Katy Gero, Clément Canonne, Craig Jin, Kanchana Thilakarathna
Abstract
Generative AI chatbots are increasingly embedded in everyday life, yet most large-scale studies describe global patterns. This paper presents an Australia-focused analysis of WildChat, a public dataset of real-world ChatGPT interaction logs. Using descriptive analysis and a multi-layer classification scheme, we analysed 37,845 conversations identified as Australian, examining language diversity, work relevance, interaction intent, topic distribution, turn-taking, temporal change, work activities, and Australia-related domains. Our findings show that the Australian subset is strongly action-oriented and comparatively work-oriented, with most interactions classified as doing and a majority of conversations classified as work-related. The dataset also shows multilingual use and a growing presence of self-expression over time. Australia-related conversations frequently invoke local institutions, laws, regulators, education systems, companies, cultural references, and public services. Finally, we outline implications for future research, including local AI evaluation, multilingual participation, context-aware design, and safeguards for everyday high-stakes domains.