Student flagged by ProctorU for reading aloud during exam
A college student, Dana Jo, was flagged by ProctorU test proctoring software for talking during an exam, which she says was reading a question aloud. Her professor initially gave her a zero and placed an academic infraction on her record, jeopardizing her scholarships. After reviewing a video recording, the professor apologized, reinstated her grade, and removed the infraction. ProctorU's CEO stated that the incident highlights the importance of video recordings for review.
- Company involved
- University (not named)
- AI system involved
- ProctorU
5 source articles · read the reporting →
Iberian pork producers ask Spain to exempt jamón ibérico from Nutri-Score
Spain's Inter-professional Iberian Pig Association is asking for jamón ibérico to be excluded from the Nutri-Score food labelling scheme, which rates it D or E. The association says the algorithm fails to take account of the nutritional value of Iberian pork, including protein, B vitamins and minerals. Spain's agriculture minister has expressed concern; the consumer affairs ministry did not respond to a request for comment.
- Company involved
- Spanish consumer affairs ministry
- AI system involved
- Nutri-Score
10 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 →
FTC settles with Sitejabber over reviews from customers who had not received goods
The US Federal Trade Commission has charged Sitejabber, an AI-enabled review platform, with deceiving consumers by publishing ratings and reviews submitted at the point of purchase, before buyers had received or experienced the products. The FTC alleges this artificially inflated average ratings and review counts for its clients. Sitejabber has agreed to a proposed consent order prohibiting it from making such misrepresentations in the future.
- Company involved
- Sitejabber
- AI system involved
- Sitejabber
10 source articles · read the reporting →
Cleveland State University's room scan requirement ruled unconstitutional
A federal judge ruled that Cleveland State University's requirement for a student to undergo a 360-degree room scan before an online exam was an unreasonable search under the Fourth Amendment. The student, enrolled at the public university, was told shortly before the exam that he would need to scan his private space. The court found that the university's justifications did not outweigh the privacy protections of the home. No final judgment or injunction has been issued yet.
- Company involved
- Cleveland State University
10 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 →
CBSE introduces facial recognition system for students to access digital documents
The Central Board of Secondary Education (CBSE) has introduced a facial recognition system for Class 10 and 12 students to access their digital academic documents. A live image of the student is compared with the photograph on their CBSE admit card and, if the match succeeds, the certificate is emailed to them. The facility is available on Digi Locker for 2020 records and is expected to help foreign students and those unable to open a Digi Locker account.
- Company involved
- Central Board of Secondary Education (CBSE)
- AI system involved
- Facial Recognition 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 →
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 →
Virginia crime lab faces first challenge to secret DNA algorithm
A defendant in an armed-robbery case in Fairfax County is challenging a secret algorithm used by the Virginia crime lab to interpret DNA evidence. The lab could not make a conventional match because skin-cell DNA on the victim's shirt was mixed with DNA from too many people; the algorithm identified the defendant as a contributor. The defendant is seeking to scrutinise the algorithm, reportedly for the first time.
- Company involved
- Virginia crime lab
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 →
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 →
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 →
DeepSeek-R1 censors 85% of sensitive Chinese political prompts in tests
Promptfoo tested DeepSeek-R1 against a dataset of 1,360 politically sensitive prompts and found that about 85% of them were refused. The refusals followed a standard form aligned with Chinese Communist Party policy. The testing also demonstrated that the censorship could be trivially bypassed using simple jailbreak techniques, such as prompt injection or changing the context.
- Company involved
- DeepSeek
- AI system involved
- DeepSeek-R1
5 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 →
iBorderCtrl lie detector falsely flagged honest reporter as liar
A journalist testing Europe's iBorderCtrl virtual policeman at the Serbian-Hungarian border gave honest answers but was deemed a liar by the system, scoring 48 out of 100 with four false answers flagged. The Hungarian policeman said the result suggested further checks, though none were carried out. The reporter only learned of the result after filing a data access request under European privacy laws. Experts and transparency activists have criticised the technology as pseudoscientific and potentially discriminatory.
- Company involved
- iBorderCtrl consortium
- AI system involved
- Silent Talker / iBorderCtrl virtual policeman
10 source articles · read the reporting →
Texas uses AI to grade student STAAR test answers
The Texas Education Agency will use an automated scoring engine to grade written answers on the 2023 STAAR tests, replacing thousands of human graders. The system uses natural language processing and will initially score all responses, with a quarter rescored by humans. Educators have expressed concerns about the system's fairness and the potential for errors, especially for creative or non-standard answers.
- Company involved
- Texas Education Agency
- AI system involved
- automated scoring engine
10 source articles · read the reporting →
Virginia courts' use of algorithms raises fairness concerns
The Washington Post considers the use of risk-assessment algorithms in Virginia's courts, which were introduced to make judicial decisions fairer. The analysis finds that the outcomes have been far more complicated than expected, raising concerns about the system's fairness. The algorithms affect potentially many criminal defendants across the state.
- Company involved
- Virginia court system
7 source articles · read the reporting →
