Decoding the algorithmic operations of Australia's National Disability Insurance Scheme

Author:

van Toorn Georgia12,Carney Terry23

Affiliation:

1. School of Social Sciences University of New South Wales Sydney New South Wales Australia

2. ARC Centre of Excellence for Automated Decision‐Making and Society (ADM+S) Carlton Victoria Australia

3. Law School The University of Sydney Camperdown New South Wales Australia

Abstract

AbstractIn recent years, Australia has embarked on a digital transformation of its social services, with the primary goal of creating user‐centric services that are more attentive to the needs of citizens. This article examines operational and technological changes within Australia's National Disability Insurance Scheme (NDIS) as a result of this comprehensive government digital transformation strategy. It discusses the effectiveness of these changes in enhancing outcomes for users of the scheme. Specifically, the focus is on the National Disability Insurance Agency's (NDIA) use of algorithmic decision support systems to aid in the development of personalised support plans. This administrative process, we show, incorporates several automated elements that raise concerns about substantive fairness, accountability, transparency and participation in decision making. The conclusion drawn is that algorithmic systems exercise various forms of state power, but in this case, their subterranean administrative character positions them as “algorithmic grey holes”—spaces effectively beyond recourse to legal remedies and more suited to redress by holistic and systemic accountability reforms advocated by algorithmic justice scholarship.

Publisher

Wiley

Reference79 articles.

1. Navigating the Australian National Disability Insurance Scheme: a scheme of big ideas and big challenges;Ardill A.;Journal of Law and Medicine,2020

2. Australian Government. (2021)National Disability Insurance Scheme oversight Tuesday 18 May 2021 Canberra. Australian Parliament. Available from:https://parlinfo.aph.gov.au/parlInfo/search/display/display.w3p;query=Id%3A%22committees%2Fcommjnt%2Ff025947f‐e54b‐4d95‐a2b8‐68ddee7decc3%2F0000%22[Accessed 6th June 2022].

3. AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias

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