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Michigan MiDAS Unemployment Fraud Algorithm
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Rotterdam Welfare Fraud Risk Algorithm
Rotterdam’s Analytics Uitkeringsfraude model helped select social-assistance recipients for human review; its score did not establish fraud or terminate benefits.
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Muhtasari
The 2021 audit warned of opacity and proxy-bias risks, while a separate successor effort began in January 2022 and was paused in 2023; a public-register entry documents a 2017–2022 selection model, but its exact link to the recovered artifact is unproven.
Dive ya kina
Rotterdam’s Analytics Uitkeringsfraude project used a risk model to help select recipients for review. In a 2021 parliamentary answer, the Dutch government relayed the municipality’s account: the model estimated risk from historical benefit-administration data; recipients could then be invited to a conversation, and an employee assessed legality. The municipality said it did not autonomously establish fraud and described training as a human-run process using historical investigations and held-out records. A score can still shape who faces scrutiny. The Rotterdam Court of Audit’s 2021 report “Gekleurde technologie” identified governance and transparency gaps. It said citizens had little ability to understand how the algorithm affected selection and warned that proxies such as low literacy could create biased outputs. The audit did not investigate whether outcomes had in fact been unfair. The government response acknowledged that indirect relationships with protected characteristics can produce bias and cited speaking ability as a possible proxy for origin or ethnicity. These are documented risks, not a finding that every group was discriminated against. A 2023 investigative team published code and described acquiring a trained model and records. Its repository documents a 315-feature artifact and controlled profile perturbations. These tests speak to that recovered version and chosen profiles; they do not estimate all recipients’ error rates or prove a legal violation. The Court of Audit also found the municipality had not adequately evaluated whether the model outperformed older methods or what impact it had. The register entry “Heronderzoeken Uitkeringsgerechtigden” dates a selection algorithm January 2017–February 2022 and marks it stopped early 2022. Its period and selection function align with the older Analytics Uitkeringsfraude project, but do not prove this register record is the recovered code artifact. The Court of Audit’s 2024 follow-up separately says development of a successor re-examination risk model began January 2022 and paused in 2023. The register is not identified as that successor. A score alone established no fraud.
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The Future of Rotterdam Welfare Fraud Risk Algorithm
The 2021 audit and parliamentary answer describe the former fraud-risk project and its human-review role. The public register dates a selection algorithm from January 2017 to February 2022 and marks it stopped in early 2022; the 2024 audit separately reports that successor-model development started in January 2022 and was paused in 2023. The available sources do not establish that the register entry is the successor or that it exactly matches the recovered artifact. Check the record and version before making a current-deployment claim. Continue to distinguish documented proxy risks, artifact tests, measured outcomes and formal legal findings.
Utekelezaji wa Ulimwengu Halisi
A recipient asks whether an invitation to review their benefit followed an algorithmic score and what information influenced selection.
An auditor distinguishes a risk ranking from an investigator’s fact-finding and a municipality’s legal decision about an individual benefit.
A fairness review tests whether language or caseworker-recorded features act as proxies for protected traits, without treating correlation as proof of discrimination.
A researcher scopes controlled tests of a recovered model artifact to that version and those test profiles instead of calling them a population-level impact study.
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What is Rotterdam Welfare Fraud Risk Algorithm?
Rotterdam’s Analytics Uitkeringsfraude model helped select social-assistance recipients for human review; its score did not establish fraud or terminate benefits. The 2021 audit warned of opacity and proxy-bias risks, while a separate successor effort began in January 2022 and was paused in 2023; a public-register entry documents a 2017–2022 selection model, but its exact link to the recovered artifact is unproven.
What role did Rotterdam’s Analytics Uitkeringsfraude risk model play?
The 2021 government response described a risk estimate used to invite recipients to a conversation; a person then assessed benefit legality.
What did the Rotterdam Court of Audit conclude about actual discriminatory outcomes in its 2021 review?
The audit identified proxy risks and insufficient safeguards but said it had not investigated whether outputs had in fact been unfair.
Why can historical investigation records be a risky training target?
Models trained on previously investigated cases can inherit the way those cases were selected; this is a methodological risk, not proof of a particular disparity.
What proxy concern did the 2021 audit and government response discuss?
The audit discussed low literacy; the government answer noted speaking ability could indirectly relate to origin or ethnicity.
What can controlled tests of the recovered model artifact establish?
The released reproduction supports artifact-specific perturbation tests; synthetic profile sensitivity is not a population impact estimate or legal finding.
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