Module 2: Real-Life Examples of Bias
LESSON 2.5: BIAS IN GOVERNMENT FRAUD DETECTION SYSTEMS - CASES IN THE UK AND NETHERLANDS
In recent years, the use of AI algorithms by government agencies to detect fraud has raised serious ethical concerns due to instances of algorithmic bias. These systems, intended to improve efficiency and reduce fraud, have inadvertently discriminated against individuals based on nationality or ethnic background, leading to significant personal and financial repercussions for those affected.
Case in the United Kingdom
In 2023, investigative journalists from The Guardian revealed that the British Home Office uses AI to flag suspected sham marriages. Although designed to streamline the evaluation process, internal reviews showed that the AI disproportionately flagged individuals from Albania, Greece, Romania, and Bulgaria as likely involved in sham marriages. Similarly, the UK Department for Work and Pensions (DWP) employs an AI tool to identify potential fraud in benefits claims. However, the system frequently flagged Bulgarian claimants as suspicious, resulting in suspended benefits and potential financial hardships for these individuals.
Both agencies have claimed their processes are fair because human officers make the final decisions. However, experts point out that due to limited resources, officials rely heavily on the AI’s initial assessment, which means the bias inherent in the algorithm often influences the final decision. Those impacted by these decisions may never realize that they were targeted based on a biased algorithm, as government agencies do not fully disclose the inner workings of their automated processes.
Stacey, K. (2023). UK officials use AI to decide on issues from benefits to marriage licences. The Guardian. Link
Case in the Netherlands
The Dutch Childcare Benefits Scandal A particularly alarming example of algorithmic bias occurred in the Netherlands in 2019, where the Dutch Tax Authority used an AI system to create risk profiles for spotting fraud in childcare benefits. The algorithm flagged families as potential fraudsters based on factors like nationality, specifically targeting individuals of Turkish and Moroccan descent, as well as those with dual nationalities and lower incomes. The consequences were devastating: individuals wrongly flagged as fraudsters were required to repay large sums of money, pushing many families into severe poverty. Some affected families experienced extreme distress, with tragic cases of suicide and children placed into foster care due to financial hardships.
The Dutch Data Protection Authority (DPA) launched an investigation and found that the algorithmic system used by the tax authority was “unlawful, discriminatory, and improper.” In 2021, the DPA fined the Dutch Tax Authority 2.75 million euros, followed by an additional 3.7 million euro fine in 2022 for the misuse of personal data in its “fraud identification facility.”
This scandal led to the resignation of the Dutch government, though officials regrouped later. The incident remains a stark reminder of the potential harm caused by biased algorithms in government decision-making. Experts warn that, without significant regulatory safeguards, similar cases could emerge in other countries.
Heikkilä, M. (2022). Dutch scandal serves as a warning for Europe over risks of using algorithms. POLITICO. Link
Heikkilä, M. (2022). AI: Decoded: A Dutch algorithm scandal serves a warning to Europe—The AI Act won’t save us. Politico. Link
Kuźniacki, B. (2023). The Dutch Childcare Benefit Scandal Shows That We Need Explainable AI Rules. online]. Link