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.
69 incidents closest to “SafeRent Score” · matched on meaning · public reporting
A study of mortgage lending from 2012-2018 found that Latinx and African-American borrowers were charged higher interest rates than white borrowers with similar credit risk. FinTech algorithms reduced the disparity by 40% but did not eliminate it. The discrimination costs minority borrowers an estimated $765 million per year in extra interest.
10 source articles · read the reporting →
Robert Nelson, president of Nelson Management Group, planned to install a facial recognition system at Atlantic Plaza Towers, a rent-stabilized building in Brownsville, Brooklyn. Tenants protested, citing privacy concerns and studies showing the technology disproportionately impacts people of color. After a town hall meeting, Nelson announced he was withdrawing the application with the state housing agency. The reversal was seen as a victory by tenants, who continue to push for legislation banning facial recognition in residential buildings.
10 source articles · read the reporting →
Bankrate published an AI-generated article about the best places to live in Colorado that contained multiple factual errors, including incorrect median home prices and unemployment rates. The article was removed after Futurism pointed out the mistakes. A Bankrate spokesperson blamed the errors on outdated data from an internal database, claiming the article was editor-reviewed. The incident follows a previous scandal where CNET and Bankrate paused AI content after similar errors, but the company has resumed AI article publication.
1 source article · read the reporting →
RealPage's YieldStar algorithm uses private competitor data to recommend rent increases for apartment units. Landlords adopt up to 90% of the suggestions, leading to higher rents for tenants. Critics allege the software may facilitate indirect price-fixing in violation of antitrust law. The company denies wrongdoing and says the software helps eliminate collusion.
10 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 →
A class action lawsuit alleges that UDR, Inc. used RealPage's YieldStar algorithmic pricing software to set rental rates and occupancy levels for its San Diego properties, in violation of a local ordinance. The suit claims the software relied on nonpublic competitor data, contributing to inflated rents and making housing less affordable. The lawsuit, filed in July 2026, seeks to represent all affected tenants. UDR has previously acknowledged using YieldStar as one tool among others in its decision-making.
1 source article · 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 →
A study of over 100 million rides in Chicago between November 2018 and December 2019 found that Uber and Lyft's pricing algorithms charged higher fares per mile for trips to or from neighbourhoods with higher proportions of non-white residents. The researchers analysed trip data against census demographics and found no statistical link to higher demand in those areas. Both companies acknowledged the study and said they would review the findings, but no changes have been reported.
10 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 →
Titus Henderson, a prisoner, filed a civil rights lawsuit against COMPAS and other defendants in the U.S. District Court for the Western District of Wisconsin on July 16, 2018. The lawsuit alleges discrimination related to the use of the COMPAS risk assessment tool. The case is ongoing.
6 source articles · read the reporting →
Allstate proposed an auto insurance rate adjustment plan in Maryland using a retention model algorithm that varied premium changes based on existing premiums. The algorithm would have increased rates up to 20% for customers already paying the highest premiums while capping increases at 5% for others, and would have denied meaningful discounts to thousands owed reductions. The Maryland Insurance Administration rejected the plan as discriminatory, but Allstate claims it was withdrawn and has continued proposing similar models elsewhere. The proposal never took effect in Maryland.
9 source articles · read the reporting →
A study by the Universities of Padua, Udine and Carnegie Mellon found that Italian car insurers, including Genertel, Mps, Quixa and Con.Te, use birthplace and citizenship in pricing algorithms, charging some drivers over €1,000 more. The practice was ruled against in a 2018 decree involving Linear, but the study says it continues. The companies contacted denied or explained the findings.
8 source articles · read the reporting →
The Los Angeles Homeless Services Authority uses the VI-SPDAT scoring system to prioritise unhoused people for subsidised permanent housing. An investigation by The Markup found that Black and Latino people consistently receive lower vulnerability scores than White people, leading to lower priority for housing. The agency has acknowledged the racial disparities and is working on a new tool, but continues to use the current system.
10 source articles · read the reporting →
Nevada replaced its income-based school funding formula with a machine learning model developed by Infinite Campus that generates a 'grad score' for each student. The model reduced the number of students eligible for supplemental funding from 288,000 to 63,000, disproportionately affecting low-income students. Critics argue the model lacks transparency and de-emphasizes economic status, potentially leaving many high-poverty schools underfunded.
7 source articles · read the reporting →
DeepScore, a Tokyo-based company, is marketing an app that uses facial and voice recognition to score people's trustworthiness for lenders and insurers in Japan, Indonesia, Vietnam and the Philippines. The company says the app can detect deception with 70 per cent accuracy, but researchers and privacy advocates say there is no reliable scientific basis for such judgments and warn of discrimination and privacy harms. The chief executive said the system is only one part of lenders' and insurers' decision-making and that people can choose not to use it. Critics respond that an unequal balance of power makes consent difficult.
6 source articles · read the reporting →
Bayerischer Rundfunk journalists conducted experiments with Retorio's AI video interview analysis tool. The AI, which assesses personality traits from short videos, produced different scores when the same actress changed her appearance (glasses, headscarf, wig) or the video background and lighting were altered. The start-up Retorio acknowledged that the AI considers external image, similar to a human interviewer. Experts warned that such software could perpetuate stereotypes and unfairly affect job candidates.
10 source articles · read the reporting →
A former Uber driver in San Diego filed a federal lawsuit alleging that Uber's star rating system, based on passenger reviews, discriminates against drivers who are not white or who have accents. The suit claims Uber terminates drivers whose average ratings fall too low, and that this disproportionately affects minority drivers. Uber denies the allegation, stating that ridesharing has reduced bias. The plaintiff, Thomas Liu, an Asian driver from Hawaii, was fired in October 2015 after his rating dropped below 4.6.
10 source articles · read the reporting →
In Loomis v. Wisconsin, a judge used a COMPAS risk score from Northpointe to sentence a defendant to a harsher punishment. The algorithm was kept secret as a trade secret, preventing the defendant from challenging its accuracy. The Wisconsin Supreme Court upheld the sentence, ruling that the score was only one part of the rationale. The case raises concerns about due process and the use of secret algorithms in criminal sentencing.
10 source articles · read the reporting →
A study by Carnegie Mellon University found that Airbnb's smart-pricing algorithm increased the revenue gap between White and Black hosts, even though it narrowed the gap among hosts who adopted it. The algorithm, which sets daily prices automatically, was adopted by fewer Black hosts, so its suggested prices were closer to the optimum for White hosts. The researchers said the tool could reduce racial disparities only if more Black hosts adopted it.
10 source articles · read the reporting →
The United States Postal Service (USPS) implemented a new algorithm, RRECS, to evaluate rural carrier routes and determine pay. Due to flaws in how carriers scanned packages, the algorithm underestimated route times, resulting in pay cuts for 66 per cent of rural carriers, some losing thousands of dollars annually. Carriers report that they were not adequately trained on the system and that the cuts are scheduled to take effect, though they have been postponed multiple times. The USPS stated that the system is the result of a nationally negotiated agreement.
9 source articles · read the reporting →
A study of 50 million US consumers found that credit scoring algorithms used by mortgage lenders are less accurate for minority and low-income applicants due to sparse credit data, leading to higher rejection rates. The inaccuracy is due to noise in the data, not bias, so fairer algorithms cannot fix it. The study suggests that adjusting for bias had no effect, and that addressing the inaccuracy could reduce disparities by 50%.
6 source articles · read the reporting →
In August 2019, Crystal Marie and Eskias McDaniels, a Black couple, were denied a mortgage for a house in Charlotte, North Carolina, by loanDepot's automated underwriting algorithm. The algorithm rejected the application because Crystal Marie was a contractor, not a full-time employee, despite her high credit score and income. After the couple enlisted their real estate agent and employer to intervene, the lender reversed the decision and cleared them to close. The couple alleged that race played a role in the denial, which loanDepot denied.
10 source articles · read the reporting →
