The DOI matches its Crossref record; the references it cites are not checked yet.
Robodebt: A Socio-Technical Case Study of Public Sector Information Systems Failure
Abstract
Large-scale public sector information systems (PSIS) that administer social welfare payments face considerable challenges. Between 2014 and 2023, an Australian government agency conceived and implemented the Online Compliance Intervention (OCI) scheme, widely referred to as Robodebt. The scheme's primary purpose was to apply digital transformation in order to reduce labour costs and increase recovery of overpayments. Among its key features were a simplified, but inherently erroneous, estimation method called income averaging, and a new requirement that welfare recipients produce documentation for income earned years earlier. Failure by welfare recipients to comply with mandates resulted in the agency recovering what it asserted to be overpayments. This article presents a case study of Robodebt and its effects on over 1 million of its clients. The detailed case study relies on primary data through Senate and other government hearings and commissions, and secondary data, such as media reports, supplemented by academic sources. Relevant technical features include (1) the reliance on the digital persona that the agency maintains for each client, (2) computer-performed inferencing from client data, and (3) automated decision-making and subsequent action. This article employs a socio-technical systems approach to understanding the factors underlying a major PSIS project failure, by focusing on the system's political and public service sponsors; its participants (users); the people affected by it (usees); and the broader economic, social, and political context. Practical and theoretical insights are presented, with the intention of highlighting major practical lessons for PSIS, and the relevance of an articulated socio-technical frame for PSIS.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
The citation lists haven’t been fetched yet
Cited by 14
Metadata
- Authors
- Clarke, R., Michael, K., & Abbas, R.
- Venue
- Australasian Journal of Information Systems
- Published
- 2024-09-05
- Volume
- 28
- ISSN
- 1326-2238
- Cited by
- 14
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Robodebt: A Socio-Technical Case Study of Public Sector Information Systems Failure. https://app.cochat.ai/papers/10.3127/ajis.v28.4681
- The paper
- Clarke, R., Michael, K., & Abbas, R. (2024). Robodebt: A Socio-Technical Case Study of Public Sector Information Systems Failure. Australasian Journal of Information Systems. https://doi.org/10.3127/ajis.v28.4681
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.