AI Incident Database
Browse AI incidents
Every incident record (metadata only) from the weekly snapshot of 2026-09-07. Filter, then export the selection with its licence attached; each row links to the full record and its reports.
Filter incidents (1 active)
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UK Home Office's Sham Marriage Detection Algorithm Reportedly Flagged Certain Nationalities Disproportionately AIID ↗
UK Home Office's opaque algorithm to detect sham marriages flagged some nationalities for investigation more than others, raising fears surrounding discrimination based on nationality and age.
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UK Visa Streamline Algorithm Allegedly Discriminated Based on Nationality AIID ↗
UK Home Office's algorithm to assess visa application risks explicitly considered nationality, allegedly caused candidates to face more scrutiny and discrimination.
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Tinder's Personalized Pricing Algorithm Found to Offer Higher Prices for Older Users AIID ↗
Tinder’s personalized pricing was found by Consumers International to consider age as a major determinant of pricing, and could be considered a direct discrimination based on age, according to anti-discrimination law experts.
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US DHS’s Opaque Vetting Software Allegedly Relied on Poor-Quality Data and Discriminated against Immigrants AIID ↗
US Citizenship and Immigration Services (USCIS)’s ATLAS software used in vetting immigration requests was condemned by advocacy groups as a threat to naturalized citizens for its secretive algorithmic decision-making, reliance on poor quality data and unknown sources, and alleged discrimination of immigrants using biometric and sensitive information.
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Tech Companies Reportedly Influenced Gig Workers' Behaviors Using Algorithms to Vary Pay for Same Amount of Work AIID ↗
Amazon and Uber were alleged in a multiyear ethnographic study using algorithmic systems based on gig workers' data to vary pay, such as by offering them lower wages for the same amount of work.
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Coffee Meets Bagel’s Algorithm Reported by Users Disproportionately Showing Them Matches of Their Own Ethnicities Despite Selecting “No Preference” AIID ↗
Users selecting “no preference” were shown by Coffee Meets Bagels’s matching algorithm more potential matches with the same ethnicity, which was acknowledged and justified by its founder as a means to maximize connection rate without sufficient user information.
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Sexist and Racist Google Adsense Advertisements AIID ↗
Advertisements chosen by Google Adsense are reported as producing sexist and racist results.
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UT Austin's GRADE Algorithm Reportedly Reduced Review of Lower-Scored PhD Applicants Amid Bias Concerns AIID ↗
From the 2013 through 2019 admissions cycles, UT Austin's Department of Computer Science used GRADE, a statistical machine-learning system trained on past admissions decisions, to score and organize PhD applications. Critics said the system could reproduce historical admissions inequities and reduce attention to lower-scored applicants, while UT Austin said human reviewers still evaluated each file and later discontinued the tool.
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Chicago Police's Strategic Subject List Reportedly Biased Along Racial Lines AIID ↗
The Chicago Police Department reportedly used person-based predictive policing models, including the Strategic Subject List and Crime and Victimization Risk Model, to assign violence-risk scores to hundreds of thousands of residents. Official and media reports alleged that the program gave police a mathematically fragile basis for treating heavily policed residents as future victims or suspects, with Black Chicago residents especially exposed to the consequences of that scoring.
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Police Reportedly Deployed ShotSpotter Sensors Disproportionately in Neighborhoods of Color AIID ↗
Police departments disproportionately placed ShotSpotter sensors in black and brown neighborhoods, which is denounced by communities for allegedly creating dangerous situations, such as one involving in Adam Toledo's death.
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Google Instant's Allegedly 'Anti-Semitic' Results Lead To Lawsuit In France AIID ↗
The organizations SOS Racisme, Union of Jewish Students of France, Movement Against Racism and for Friendship Among Peoples are suing Google due to its autocomplete software suggesting "jewish" when the names of certain public figures were searched on the platform.
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Major Universities Are Reportedly Using Race as a 'High Impact Predictor' of Student Success AIID ↗
Several major universities are reportedly using a tool that uses race as one factor to predict student success.
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IRS Audited Black Taxpayers More Frequently Reportedly Due to Algorithm AIID ↗
The IRS was auditing Black taxpayers more frequently than other groups allegedly due to the design of their algorithms, focusing on easier-to-conduct audits which inadvertently correlated with the group's pattern of tax filing errors.
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Amazon Censors Gay Books AIID ↗
Amazon's book store "cataloging error" led to books containing gay and lesbian themes to lose their sales ranking, therefore losing visibility on the sales platform.
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Automated Adult Content Detection Tools Showed Bias against Women Bodies AIID ↗
Automated content moderation tools to detect sexual explicitness or "raciness" reportedly exhibited bias against women bodies, resulting in suppression of reach despite not breaking platform policies.
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Virginia Courts’ Algorithmic Recidivism Risk Assessment Failed to Lower Incarceration Rates AIID ↗
Virginia courts’ use of algorithmic predictions of future offending risks were found by researchers failing to reduce incarceration rates, showed racial and age disparities in risk scores and its application, and neither exacerbated or ameliorated historical racial differences in sentencing.
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Kidney Testing Method Allegedly Underestimated Risk of Black Patients AIID ↗
Decades-long use of the estimated glomerular filtration rate (eGFR) method to test kidney function which considers race has been criticized by physicians and medical students for its racist history and inaccuracy against Black patients.
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St George's Hospital Medical School allegedly Automated Admissions with Discriminatory Results AIID ↗
From 1982 to 1986, St George's Hospital Medical School used a program to automate a portion of their admissions process that allegedly discriminated against women and members of ethnic minorities.
Disclaimer: informational only, not legal advice. Verify every claim against the linked official sources and consult a qualified lawyer before acting.
Frequently asked questions
What is recorded in each incident?
What happened, when, who was involved as developer or deployer, who was harmed, the sectors and countries affected, and the domain and subdomain the harm falls under. Incidents are mirrored from the AI Incident Database and each links back to its source record.
Does an incident mean wrongdoing was proven?
No. These are reported incidents, not findings of liability. Entities named in a report are named as reported, allegations are marked as alleged, and nothing here is a legal determination.
How current is the incident data?
It syncs directly from the AI Incident Database several times a day, so a new incident usually appears within hours. Each record carries the date it was last synced, and the snapshot date is shown on the page.
Does this page include the full incident reports?
No. The report texts are outside the licence this data is shared under, so only the metadata and the classifications appear here. Every row links to the original incident record, which carries the reports themselves.