Responsible AI gets $39.9 million in the federal budget

Artificial intelligence continues to be a focus for the federal government when it comes to the tech sector, and the 2024-25 budget reveals $39.9 million will go towards safe and responsible adoption of AI.

It’s worth noting this isn’t an entirely new investment. Last year’s budget saw $102.2 million over five years set aside to support businesses integrate quantum and AI into their operations.

Part of this included the extension of the National AI Centre and its support of responsible AI usage.

This year, the budget papers allocate $21.6 million over four years, starting in the 2024-25 financial year, to be used to “establish and reshape National AI Centre (NAIC) and an AI advisory body”.

According to the budget papers, this body will sit within the Department of Industry, Science and Resources (DISR).

There is also some good news for those interested, or concerned with, current regulations and laws.

Across two years, $15.7 million will go towards AI policy development and regulation. This will also include a review and strengthening of existing regulations across health care, consumer and copyright law.

That last part is important, particularly to those working in the AI regulation space who don’t believe we necessarily need to invent entirely new laws for AI in places where existing ones may already suffice. It’s certainly going to be an interesting one to see play out.

National security risks related to AI will also be getting a look in, with $2.6 million in funding over three years.

Lastly, the Digital Transformation Agency will develop and implement policies to “position government as an exemplar in the use of AI”.

According to the papers, the costs of this will be met from within existing resources from the Department of Home Affairs and the Department of Industry, Science, and Resources.

Speaking of the government using AI – an unrelated line item in the papers includes $2.2 million for APS uplift projects, “including AI integration and enhancing the quality of data to inform policy analysis”.