Incidents gathered from public reporting around the world. Each one links to the articles it came from. None of it is a finding that anyone broke the law.
Reports people file about their own experience are not shown here and never will be without their agreement. Tell us what happened to you.
44 incidents closest to “Registry ScorePLUS” · matched on meaning · public reporting
The system flagged student assignments as AI-generated, potentially leading to academic misconduct accusations.
1 source article · read the reporting →
A study by Dartmouth College researchers found that the COMPAS recidivism risk assessment algorithm, used by judges in several US states, is no more accurate than random people recruited online. The algorithm, developed by Equivalent, exhibited racial bias by classifying black defendants as higher risk and white defendants as lower risk, leading to harsher rehabilitation recommendations for black defendants. The bias likely stems from skewed arrest rate data. The findings build on a 2016 ProPublica investigation.
10 source articles · read the reporting →
Checkr's system misreported criminal records belonging to someone else on Natasha Davis's consumer report, impeding her ability to gain employment.
1 source article · read the reporting →
Mary Louis and Monica Douglas filed a class action lawsuit in 2022 alleging that SafeRent Solutions' SafeRent Score product discriminated against rental applicants in Massachusetts who held public housing vouchers, violating fair housing and consumer protection laws. SafeRent denied wrongdoing. The court approved a settlement in November 2024, and payments were distributed to eligible class members in 2025 and 2026.
5 source articles · read the reporting →
The Chicago Police Department has used the Strategic Subject List since 2012, an algorithm that assigns risk scores to individuals based on arrest records. The list was kept secret until a court forced its release, revealing that 56% of black men aged 20-29 have a score, and only 3.6% of those on the list were involved in violence. Despite claims it is not used for enforcement, documents show it influences police deployment and arrests, leading to allegations of racial bias and lack of transparency.
9 source articles · read the reporting →
The University of Texas at Austin's computer science department used a machine-learning system called GRADE from 2013 to 2020 to score Ph.D. applicants. Critics argued the system perpetuated bias by training on past admissions decisions and using features like institution prestige and biased language in recommendation letters. The department discontinued the system in 2020, citing maintenance difficulties, but the controversy highlighted concerns about algorithmic fairness in admissions. The system was never disclosed to applicants, and its impact on underrepresented groups remains unknown.
2 source articles · read the reporting →
In October 2020, the California State Bar administered its first online bar exam using ExamSoft's AI-enabled proctoring software. The software flagged 3,190 out of 9,301 test takers for potential rule violations such as gazing off-screen or having food. The state bar is reviewing each case, which could require affected individuals to retake the exam, delaying their ability to practice law. Test takers have expressed distress and hired attorneys to contest the allegations.
2 source articles · read the reporting →
An investigation by SPIEGEL and BR Data reveals that Schufa's credit scoring algorithm often assigns poor risk scores to consumers with only positive credit information. One consumer, Sven Drewert, was denied a credit card limit increase despite having no negative entries. The algorithm uses limited data, and its secret formula can lead to arbitrary categorisations, affecting access to loans, phone contracts, and housing. The system's opacity and potential biases raise concerns about fairness and accountability.
2 source articles · read the reporting →
In August 2020, the UK exam regulator Ofqual used an algorithm to determine A-level grades after exams were cancelled due to COVID-19. The algorithm downgraded approximately 39% of results, disproportionately affecting disadvantaged students from state schools. Following protests and accusations of discrimination, the government reversed the decision and used teacher predictions instead. The incident caused university admissions chaos and prompted a review by the Office for Statistics Regulation.
8 source articles · read the reporting →
The U.S. Department of Justice's Pattern risk assessment algorithm, used to determine federal prisoners' eligibility for early release under the First Step Act, was found to produce racial disparities. A December 2021 DOJ report revealed that the tool overpredicted recidivism risk for Black, Hispanic, and Asian inmates, with only 7% of Black prisoners classified as minimum risk compared to 21% of white prisoners. Civil rights groups have called for the suspension of the tool, while the DOJ is working on an overhaul and reevaluating 14,000 prisoners who were misclassified.
1 source article · read the reporting →
In July 2020, the International Baccalaureate (IB) program used a statistical model to predict final grades for over 170,000 students after cancelling exams due to Covid-19. Many students, including Anahita Nagpal, received lower-than-expected scores, causing them to lose college places and scholarships. Students, parents, and teachers questioned the fairness and transparency of the algorithm, with over 15,000 signing a petition demanding a fairer approach. IB defended the model but offered an appeals process, while some students planned to retake exams at their own expense.
1 source article · read the reporting →
Popular smartphone apps including Life360, MyRadar and GasBuddy reportedly shared users' location and motion data with Arity, an Allstate-owned company. Arity used the data to calculate driving scores that could be sold to car insurers to set rates. Users were said not to be clearly informed that their data would be used for insurance pricing. Life360 and Arity stated that users had to opt in and that no personally identifiable driving data was shared without consent.
2 source articles · read the reporting →
The Markup found that several universities, including UMass Amherst, UW–Milwaukee, and Texas A&M, use EAB's Navigate software which incorporates race as a predictor of student dropout risk. The algorithms label Black and Latinx students as high risk at disproportionately high rates compared to White students. Students, professors, and experts worry this is pushing minority students out of math and science majors through biased advising.
1 source article · read the reporting →
An independent report found that the Australian government's Vera-2R terrorism risk assessment tool included autism spectrum disorders as a risk factor without empirical evidence. The tool was used to assess terrorist offenders, influencing post-sentence orders including ongoing detention. Despite the critical report being received in May 2020, the federal and NSW governments continued to use the tool. The report concluded the tool was 'extremely poor' at predicting risk.
1 source article · read the reporting →
In February 2012, the New York City Department of Education publicly released individual Teacher Data Reports rating over 12,000 teachers based on value-added analysis of student test scores. The ratings, originally intended for internal use, were disclosed after a court ruled in favor of media organizations under the Freedom of Information Act. The teachers' union and education experts criticised the data as unreliable due to large margins of error and failure to account for demographic factors, warning that the release would unfairly shame or praise educators. The Department defended the ratings as a useful perspective on teacher effectiveness.
6 source articles · read the reporting →
Durham Constabulary developed the Harm Assessment Risk Tool (HART), a machine learning algorithm that assesses the recidivism risk of offenders. The tool uses 34 data categories including criminal history, age, gender and two types of postcode, one sourced from Experian's Mosaic marketing segmentation system. Big Brother Watch alleges that using such commercial consumer behaviour data to inform custody decisions risks prejudice and disproportionate targeting of deprived neighbourhoods. The force has stated it is refreshing the model with an aim to remove one of the postcode predictors.
9 source articles · read the reporting →
Amnesty International and coalition partners filed a complaint with the Council of State against CNAF's risk-scoring algorithm used to detect benefit overpayments. The algorithm assigns risk scores based on criteria that discriminate against vulnerable groups, including those with disabilities, single parents, and low-income households. The complaint alleges the system violates human rights to equality and privacy. The EU AI Act's social scoring ban may apply, but its definition remains unclear.
2 source articles · read the reporting →
The Austrian Public Employment Service (AMS) uses an algorithm to classify job seekers into categories A, B, and C, determining their access to benefits and training. Scientists from TU Wien, WU Wien, and University of Vienna have criticised the algorithm for lacking transparency, as only two of 96 model variants have been published. They allege that the system may discriminate against women and people with migration background, and that job seekers are not informed about how the algorithm works or given a chance to appeal.
10 source articles · read the reporting →
The Educational Testing Service's E-rater algorithm, used to grade essays on the GRE and other standardized tests, has been found to systematically give higher scores to students from mainland China and lower scores to African American students compared to human graders. The bias stems from the algorithm's reliance on surface-level metrics like vocabulary and sentence length, which disadvantage certain groups. Despite studies dating back to 1999, the bias persists, and in many states, only a small percentage of essays are reviewed by humans.
10 source articles · read the reporting →
The Austrian Federal Administrative Court overturned a ban by the Data Protection Authority on the AMS algorithm, which predicts job chances of unemployed people. The system, trained on historical data including age, gender, and nationality, categorises individuals as high, medium or low chance of re-employment. Critics argue it discriminates against women and mothers, and that the data is now outdated due to the COVID-19 pandemic. The court ruled that the algorithm is lawful as long as a human advisor makes the final decision on training support.
5 source articles · read the reporting →
UK local authorities are using a system called Covid OneView, developed by data analytics firm Xantura, to harvest millions of personal details from council records. The system uses predictive analytics and AI to assign risk scores to households and individuals, aiming to identify those vulnerable to Covid or likely to break lockdown rules. Privacy campaigners and MPs have criticised the lack of transparency and the extent of data collection, which includes sensitive information such as debt levels, living arrangements, and even notes on unfaithful sex. Xantura and Barking and Dagenham Council have defended the system as compliant with data protection rules and focused on providing support.
6 source articles · read the reporting →
The Suzhou municipal government announced a civility code system that assigns scores to residents based on their behavior, including traffic violations and volunteer work. The system, currently in a trial phase, aims to generate a personal portrait for each resident. Following public backlash and concerns about privacy and potential abuse, an official stated that participation will not be mandatory and that a bad score will not affect citizens. The system is still under development.
10 source articles · read the reporting →
Hangzhou health authorities announced plans to launch a permanent health-tracking QR code system that would assign residents a color and numerical score based on medical records and lifestyle choices. The proposal, an expansion of the existing COVID-19 health code system, has sparked online backlash over privacy concerns and fears of discrimination. Critics argue that the system could lead to public exposure of personal health data and potential misuse by employers. The authorities aim to complete the project by May or June 2020.
10 source articles · read the reporting →
The Scottish Qualifications Authority (SQA) used an algorithm to moderate 2020 exam results after COVID-19 cancelled exams. The algorithm disproportionately downgraded students from disadvantaged backgrounds, leading to a public outcry and a government U-turn. An independent report criticised the SQA and Scottish Government for failing to properly assess the equality impacts and for not making the algorithm available for analysis. The SQA has expressed no regret over the moderation approach.
10 source articles · read the reporting →
