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License: CC BY
Data sources: Datacite
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Presentation . 2025
License: CC BY
Data sources: Datacite
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Fostering an AI-enabled Scientific Future in Australia with the Google Developer Group AI for Science

Authors: Butterworth, Nathaniel;

Fostering an AI-enabled Scientific Future in Australia with the Google Developer Group AI for Science

Abstract

The rapid advancements in Artificial Intelligence (AI) present unprecedented opportunities for scientific discovery. However, the adoption and effective integration of these powerful tools within the Australian research landscape still faces challenges. This lightning talk will introduce a newly established community dedicated to accelerating the use of AI tools in Australian scientific research, the Google Developer Group (GDG) AI for Science. With the support of Google behind it, the GDG AI for Science provides a vital platform for researchers across public and private sectors to connect, share knowledge, and learn from peers and industry experts. Our mission is to foster a thriving ecosystem of AI-powered scientific discovery by empowering scientists with the tools, skills, and collaborative environment needed to leverage advanced computing for their work. This talk will briefly highlight the community's objectives, initial activities, and how it is enabling researchers to unlock new insights, streamline workflows, and tackle complex scientific challenges. Attendees will gain an understanding of how this community is addressing the critical need for greater AI literacy and collaboration within Australian science, ultimately contributing to a more innovative and impactful research future.

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Keywords

Skills, Communities, Workforce

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green