AI in regional and remote Australia

The ‘digitisation of society’ is fueling big data and AI (Goodfellow et al., 2016)). In a matter of years AI has become widely available, providing companies that harness its capabilities with a significant competitive advantage (Brynjolfsson & Mcafee, 2017). In Australia people in non-urban locations are scoring lower on the digital inclusion index than their urban counterparts, a trend that is likely that this will continue as AI is embedded further into our daily technology (Thomas et al., 2020). AI focused digital divide literature has predicted that existing factors affecting digital divide are likely to affect AI digital divide (Carter et al, 2020). With issues surrounding the access, usage and affordability of existing digital technologies for people in regional and remote Australia, the question remains as to how AI will impact the digital divide for the communities in these areas.
AI, regardless of it is positive or negative is likely to have an impact on all Australians. This research aims to foster an understanding of how AI can impact people in regional and remote communities. By communicating this impact to technology developers and policymakers it is hoped that people in these communities can better placed to take advantage of the benefits of AI, while mitigating adverse effects.
The first study will take a snapshot of the digital exclusion experience of the participants. This understanding will inform the direction of the subsequent studies. In publishing the findings of study one, it is also hoped that other researchers can draw on the findings to inform their studies.
The participation and by in of people in regional and remote communities is a key pillar to this study. The participants' involvement will allow for targeted and community-focused research and initiative that are more likely to be successful. The research will give the participants and opportunity to voice their lived experience with AI and technology, as well as dictate future research and solutions in this area.

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  Susie Sheldrick

  PhD Candidate

  Faculty of Engineering and Information Technology

  University of Melbourne