Skills gap for AI-enabled research: What is available and what must be done?

Dr. Abdullah Shaikh1, Mr. Muhammad Ali, Dr Gnana Bharathy, Mark Gray, Dr Anastasios Papaioannou, Dr Alain-Dominique Gorse, Mr. Mitchell Hargreaves, Mr. Matt Bixley, Dr Nisha Ghatak, Mr. Brint Gardner, Pat Loria, Dr Slava Kitaeff, Mrs. Kathryn Unsworth

1National Computational Infrastructure (NCI), Australia

Biography:

Dr. Abdullah Shaikh is working as the Digital Skills Development Manager at NCI. He oversees NCI’s training program and leads a talented team of highly skilled trainers. He is looking for opportunities to keep Australian researchers up-to-date with the ever-growing suite of tools and technologies.

Abstract:

How ready are Australian researchers to leverage AI? Are Australian eResearch organisations and universities ready to invest infrastructure, people, and time, to support AI-enabled research?

This BoF builds on the discussions at the eResearch Conference 2023 and Supercomputing Asia 2024 to answer these questions and to ask more. Progressing these discussions is timely, as NCI (National Computational Infrastructure), Pawsey, and NeSI (New Zealand eScience Infrastructure)—region’s Tier 1 supercomputing centres—are receiving increasing requests to support GPU acceleration for AI-related projects, implement and assess large language models (LLMs), and advise on responsible AI practices. This underscores the need to identify the skills required to ensure researchers are AI-savvy.

The BoF session focuses on identifying the skills to equip researchers to tackle ever-growing AI capabilities and requirements. As an action item from the previous BoF, we also aim to gather ML4AU community of practice stakeholders and wider research support staff, academics, and professionals across Australia and New Zealand. With targeted, measurable, and achievable actions, the objective is to guide digital skills development teams in shaping their training and engagement strategies.

The session aims to identify the knowledge gaps for skills development teams to address, consider leveraging the existing training resources and platforms, and define clear future action items for this group to work on. The ML4AU community of practice will track discussions, ideas, and action items.

 

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