National Disability Insurance Agency staff are using machine learning to help create draft plans for NDIS participants, documents obtained by Guardian Australia reveal.
Documents related to NDIA’s use of AI released under freedom of information laws showed 300 staff participated in a six-month trial of Microsoft’s Copilot AI from January last year.
The agency said Copilot uses generative AI, which was only utilised for the NDIA’s emails, meetings and other non-client-facing tasks – not for participant plans.
But the documents reveal before the Copilot trial began, the NDIA was already using a form of AI – machine learning – to prepare draft budget plans for participants.
Machine learning was defined as “a subset of AI that involves the use of algorithms to learn from data and make predictions or decisions without being explicitly programmed”.
The NDIA stated that NDIS staff made all final decisions on plans and its AI policy document from April 2024 stated that “AI tools must not access participant records” unless otherwise expressly authorised by the chief information officer and authorised under the NDIS Act.
The briefing document, which was prepared for Senate estimates 2023-24, read: “While machine learning is utilised within draft budgets (or Typical Support Package) for first plans based on key information from a participant’s profiles.
“The algorithm is only ever used to make recommendations, with decisions made by actual delegates.”
The documents continued that “the machine learning recommendations are used to assist delegates by speeding up the initial analysis to provide quicker resolutions for participants and improved service”.
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In a report in June 2024, it stated staff had experienced improved productivity in preparing documents and emails by “interpreting NDIA policies and generating a summary of the purpose”.
NDIA staff overall reported a 20% reduction in task completion times during the Copilot trial and a 90% satisfaction rating – including hearing-impaired staff who reported positively of the use of live-transcription during meetings.
The report noted difficulties facing the trial included staff concern about the findings of the robodebt royal commission on automated decision-making, and concerns about AI being used to reduce staff numbers.
The end-of-trial report notes that one of the risks of using Copilot was accidental data exposure, but the agency said it would have robust access controls, regular audits, and training for employees.
Dr Georgia Van Toorn, from the University of New South Wales, who has written about the impact of algorithmic decision-making in the public sector, said machine-learning and data-driven approaches often fail “in dealing with complexity and nuance”.
“I don’t think it’s necessarily a bad thing, especially for cases that are relatively straightforward, but … we can’t expect a machine-learning approach to be able to predict the…
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