Nevada's AI grad score model cuts funding for low-income students
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.
- Company involved
- Nevada Department of Education
- AI system involved
- Grad score model
7 source articles · read the reporting →
Qoves facial assessment tool ranks journalist's attractiveness and suggests procedures
Tate Ryan-Mosley, a journalist at MIT Technology Review, used Qoves Studio's AI facial assessment tool, which automatically scored her face and listed perceived flaws such as smile lines and under-eye bags. The tool recommended skin-care products and paid surgical consultation reports. She also tried Megvii's Face++ beauty-scoring system, which gave her two percentage attractiveness scores. The article raises concerns that such algorithms are inaccurate, biased and not transparently used by social media platforms.
- Company involved
- Qoves Studio
- AI system involved
- Facial Assessment Tool
9 source articles · read the reporting →
DeepScore markets facial and voice analysis app for trustworthiness scoring despite experts' doubts
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.
- Company involved
- DeepScore
- AI system involved
- DeepScore
6 source articles · read the reporting →
Retorio AI personality test swayed by candidate appearance in BR experiment
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.
- AI system involved
- Retorio AI
10 source articles · read the reporting →
Wisconsin court used secret COMPAS algorithm to sentence Loomis to harsher term
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.
- Company involved
- State of Wisconsin
- AI system involved
- COMPAS
10 source articles · read the reporting →
Facebook Allowed Age-Targeted Credit Card Ads Violating Its Policy
The Markup found that four companies—Aspiration, Hometap, Chime, and Varo Bank—ran Facebook ads for credit cards and home equity loans that were targeted by age, excluding users under 25 or 35. This practice violates Facebook's own anti-discrimination policy and may violate the Equal Credit Opportunity Act and California's Unruh Civil Rights Act. Facebook did not respond to requests for comment, and some advertisers said they would review their ad targeting.
- Company involved
- Facebook
- AI system involved
- Facebook Ad Platform
9 source articles · read the reporting →
Airbnb smart-pricing algorithm increased racial revenue gap, study finds
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.
- Company involved
- Airbnb
- AI system involved
- Airbnb smart-pricing algorithm
10 source articles · read the reporting →
Hospitals use Epic AI to predict Covid-19 decline without validation
Dozens of hospitals across the US are using Epic's deterioration index AI system to predict which Covid-19 patients will become critically ill, despite the tool not being validated for the new disease. The rapid deployment during the pandemic bypassed normal testing and validation processes.
- AI system involved
- Deterioration index
9 source articles · read the reporting →
USPS algorithm RRECS causes pay cuts for two-thirds of rural mail carriers
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.
- Company involved
- United States Postal Service
- AI system involved
- RRECS
9 source articles · read the reporting →
University of Chicago report finds US healthcare algorithms rife with bias
A University of Chicago report alleges that algorithms used by hospitals, insurers and other businesses across the US are biased along racial and economic lines. The algorithms help triage patients, predict diabetes and flag those needing extra care, but the report says flawed products were introduced with little oversight. It says inequitable treatment has continued for more than a decade.
7 source articles · read the reporting →
Denmark's Udbetaling Danmark welfare algorithm illegally surveilled millions
Udbetaling Danmark (UDK), Denmark's centralized welfare payment agency, used automated algorithms to check eligibility and detect fraud. The system collected personal data on millions of beneficiaries and their relatives, including non-beneficiaries, in what a think-tank called 'systematic surveillance'. A complaint to the Danish Data Protection Authority led to a ruling that the data collection violated GDPR, and UDK eventually deleted the illegally obtained data. The system also caused erroneous payments, including underpaying 300,000 pensioners by 94 million euros annually.
- Company involved
- Udbetaling Danmark
10 source articles · read the reporting →
Study finds credit score algorithms less accurate for minorities
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%.
- Company involved
- Mortgage lenders (unnamed)
- AI system involved
- Credit scoring algorithms
6 source articles · read the reporting →
Danish law enables algorithm to profile unemployed for long-term risk
The Danish parliament passed a law in April 2019 that allows an algorithm to analyse personal data of all unemployed individuals to identify those at risk of long-term unemployment. The system uses data on ethnicity, age, health, and education history to produce a risk score for social workers. Critics, including legal experts and unemployment insurance funds, argue the profiling is stigmatising, lacks transparency, and may violate GDPR. The Danish Data Protection Authority has reopened its review of the law.
- Company involved
- Danish Ministry of Employment
10 source articles · read the reporting →
LoanDepot algorithm denied mortgage to Black couple in Charlotte
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.
- Company involved
- loanDepot
- AI system involved
- Classic FICO and Fannie Mae/Freddie Mac automated underwriting software
10 source articles · read the reporting →
Spanish Supreme Court orders release of BOSCO algorithm code for social electricity bonus
The Spanish NGO Civio won a Supreme Court case forcing the government to release the source code of BOSCO, the algorithm that decides eligibility for the social electricity bonus (bono social eléctrico). Civio had demonstrated in 2019 that BOSCO contained serious errors that denied the benefit to vulnerable people who met the requirements. The government had refused to disclose the code, citing intellectual property. The Supreme Court ruled that transparency must prevail, setting a precedent for public access to automated decision-making systems.
- Company involved
- Ministerio para la Transición Ecológica (Gobierno de España)
- AI system involved
- BOSCO
10 source articles · read the reporting →
Immigration NZ uses data model to predict likely troublemakers among overstayers
Immigration New Zealand has been piloting a data modelling system that uses demographic information such as age, gender, and ethnicity of overstayers to predict which individuals are likely to commit crime or incur hospital debts. The system then targets those individuals for accelerated deportation. Critics, including immigration lawyers and a lobby group, have likened the programme to 'Minority Report' and allege it amounts to racial profiling. Immigration Minister Iain Lees-Galloway only learned of the programme on the day of the article and said he would seek a full briefing, but maintained it is not racial profiling and does not breach the Human Rights Act.
- Company involved
- Immigration New Zealand
10 source articles · read the reporting →
Swedish welfare agency's AI system flags marginalized groups for fraud investigations
Försäkringskassan, Sweden's Social Insurance Agency, uses an AI risk-scoring system to flag welfare applicants for fraud investigations. The system disproportionately targets women, individuals with foreign backgrounds, low-income earners, and those without university degrees, according to an investigation by Lighthouse Reports and Svenska Dagbladet. Amnesty International has called for the system to be discontinued, citing violations of the right to equality and non-discrimination.
- Company involved
- Försäkringskassan (Swedish Social Insurance Agency)
6 source articles · read the reporting →
Dutch Ministry of Foreign Affairs used secret algorithm to score visa applicants based on nationality
The Dutch Ministry of Foreign Affairs used a secret algorithm called IOB to score short-stay visa applicants based on nationality, gender, and age. Applicants flagged as high risk were automatically moved to an intensive track with higher rejection rates and delays. The ministry's own data protection officer warned of potential ethnic discrimination, but the system continued to be used. The algorithm has profiled millions of applicants since 2015.
- Company involved
- Ministry of Foreign Affairs
- AI system involved
- IOB
10 source articles · read the reporting →
CJEU rules Dun & Bradstreet must explain automated credit decisions under GDPR
A customer was refused a mobile phone contract because of an automated credit assessment by Dun & Bradstreet Austria. The customer took the case to court, which found that Dun & Bradstreet had infringed the GDPR by failing to provide meaningful information about the logic involved. The CJEU ruled that data controllers must explain automated decisions and that trade secrets cannot automatically override the right of access.
- Company involved
- Dun & Bradstreet Austria GmbH
7 source articles · read the reporting →
Audit of RisCanvi finds biases and reliability issues in criminal justice system
Eticas conducted an adversarial audit of RisCanvi, an AI risk assessment tool used in Catalonia's criminal justice system. The audit uncovered biases in risk classifications against specific demographics and significant reliability issues. The findings call for fairer practices in criminal justice AI.
- Company involved
- Catalonia's criminal justice system
- AI system involved
- RisCanvi
4 source articles · read the reporting →
Dutch probation service's OXREC algorithm flawed, leading to incorrect recidivism risk assessments
The Dutch Inspectorate of Justice and Security (Inspectie JenV) published a report finding that the probation service's (Reclassering) OXREC algorithm contains serious flaws, including swapped formulas and incorrect numbers, causing about a quarter of risk assessments to be wrong. The algorithm, used since 2018 for about 44,000 cases per year, also uses variables that can lead to discrimination, such as neighborhood score and income. The Inspectorate recommended immediate correction or temporary suspension. The probation service announced it would temporarily stop using OXREC.
- Company involved
- Reclassering Nederland
- AI system involved
- OXREC
4 source articles · read the reporting →
Princeton Review charges higher SAT prep fees to Asian Americans
A ProPublica study found that Princeton Review's geographically-determined pricing system charges Asian American students almost twice as likely as other ethnicities to pay the highest prices for online SAT tutoring. The system sets prices based on location, with higher prices in areas like New York City where Asian Americans are concentrated. Princeton Review stated that prices reflect local costs and competition, but the disparity raises concerns about racial discrimination in automated pricing.
- Company involved
- Princeton Review
7 source articles · read the reporting →
UK prison risk algorithm may embed racial bias, experts warn
The Ministry of Justice developed a digital tool to categorize prisoners, which experts and advocacy groups warn could automate and embed racism. The tool uses intelligence data that may reflect existing bias, potentially leading to disproportionate categorization of BAME prisoners. The MoJ claims no evidence of discrimination, but critics question the small trial sample and lack of transparency.
- Company involved
- Ministry of Justice
- AI system involved
- Digital prisoner categorisation tool
5 source articles · read the reporting →
Citizens Advice finds ethnicity penalty in car insurance pricing
Citizens Advice conducted exploratory research into car insurance pricing and found that people of colour may be paying £250 more per year than White people. The research suggests that areas with large communities of colour may be identified as more risky by algorithms, even when objective risk factors are controlled. Citizens Advice has called on the Financial Conduct Authority to investigate the issue.
9 source articles · read the reporting →
