Hangzhou plans permanent health codes with scoring, sparking privacy backlash
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.
- Company involved
- Hangzhou Health Authorities
- AI system involved
- Health Code
10 source articles · read the reporting →
SQA exam algorithm disproportionately downgraded poorer pupils, report finds
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.
- Company involved
- Scottish Qualifications Authority (SQA)
10 source articles · read the reporting →
Titus Henderson files civil rights lawsuit against COMPAS
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.
- AI system involved
- COMPAS
6 source articles · read the reporting →
Allstate's proposed retention model charged big spenders more in Maryland
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 The Maryland Insurance Administration rejected the plan as discriminatory, but Allstate claims it was withdrawn and has continued proposing similar models elsewhere.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.
- Company involved
- Allstate Corporation
- AI system involved
- retention model
9 source articles · read the reporting →
Study finds Italian car insurers charge more based on birthplace
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.
- Company involved
- Genertel, Mps, Quixa, Con.Te
8 source articles · read the reporting →
LA's VI-SPDAT housing scoring system gives lower priority to Black and Latino people
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.
- Company involved
- Los Angeles Homeless Services Authority
- AI system involved
- VI-SPDAT
10 source articles · read the reporting →
Wisconsin’s dropout prediction algorithm labels students high risk with racial bias
Wisconsin’s Dropout Early Warning System (DEWS) uses machine learning to predict middle school students' likelihood of graduating on time, relying on factors including race and income. The Markup found the algorithm frequently mislabels students, with a higher false alarm rate for Black and Hispanic students. The Wisconsin Department of Public Instruction has not informed schools of the racial disparities and continues to use the system.
- Company involved
- Wisconsin Department of Public Instruction
- AI system involved
- Dropout Early Warning System (DEWS)
10 source articles · read the reporting →
Serbia's Social Card law could harm marginalized groups
Serbia's Social Card law, which entered into force on 1 March 2022, establishes a centralized government database to assess eligibility for social security support. Amnesty International and seven other rights organizations submitted a legal opinion to the Constitutional Court, alleging that the automated system is an intrusive surveillance system that could discriminate against Roma communities and people with disabilities. The system processes 130 categories of personal data and lacks transparency, potentially leading to errors and denial of benefits.
- Company involved
- Serbian government
- AI system involved
- Social Card system
10 source articles · read the reporting →
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 →
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 →
Uber sued over alleged racially biased star rating system
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.
- Company involved
- Uber
- AI system involved
- star rating system
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 →
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 →
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 →
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 →
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 →
DCPS used allegedly false test scores in teacher value-added evaluations
The District of Columbia Public Schools used student test scores from schools under investigation for cheating in value-added calculations for teacher evaluations. More than 200 teachers were terminated based on these evaluations. Teachers can appeal their ratings to the chancellor, but decisions will not be made before the next school year. The school system removes affected scores only when cheating is confirmed.
- Company involved
- District of Columbia Public Schools
- AI system involved
- value-added model
10 source articles · read the reporting →
ScaleFactor reportedly failed to deliver promised automated bookkeeping software
ScaleFactor, an Austin-based startup, is reported to have failed to deliver the automated, real-time bookkeeping tools it promised customers, instead relying on human bookkeepers and a Filipino contract accounting firm. The company told Forbes in June that it was shutting down, initially blaming the pandemic, but Forbes later reported that its problems predated Covid-19. Investors reportedly came to see the company as more of a services business than a software platform, and pulled funding after a pivot to a marketplace model. No legal or regulatory action is reported.
- Company involved
- ScaleFactor
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 →
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 →
Uber caps surge pricing at 2.8x during New York blizzard
During a major snowstorm in New York City in January 2015, Uber capped its surge pricing at 2.8 times the normal fare after facing criticism for price gouging during Hurricane Sandy. The company announced the cap in an email to users and said it would donate proceeds to the American Red Cross. The policy was in line with an agreement with the New York Attorney General to prevent massive price surges during emergencies.
- Company involved
- Uber
- AI system involved
- Uber surge pricing
5 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 →
