"[The Fair Credit Reporting Act] says, in essence: if you’re a third party generating reports about people that are used to make decisions about their employment, credit, or housing, those people have rights. The right to know a report exists. The right to see it. The right to dispute errors.
The legal theory in Kistler v. Eightfold AI is elegant: if Eightfold generates match scores based on harvested data, and those scores are used by employers to filter candidates, then Eightfold is functioning as a consumer reporting agency. Full stop. And every candidate it scored was entitled to disclosure, access, and dispute rights that they never received."
"When a candidate asks “why was I rejected?”, the system can’t answer. Not because it’s hiding something, but because it genuinely doesn’t know. The reasoning is non-deterministic. Run the same prompt twice and you might get different results. Change one word in the job description and the rankings shuffle. There’s no audit trail, no step-by-step log, no way to verify that a prohibited data point — like the candidate’s zip code acting as a proxy for race — didn’t influence the outcome."
"[M]ost enterprise AI systems have no rigorous chain of custody for their training and inference data. They can’t tell you where a data point came from, when it was collected, whether the subject consented, or whether it’s been modified since ingestion."
"Instead of engineering systems that could explain and defend their decisions, it built black boxes that produced convenient numbers. Instead of respecting candidate agency, it treated job seekers as data points to be harvested and scored. Instead of investing in the hard architectural work of compliance and transparency, it shipped wrappers and hoped nobody would ask hard questions.
Someone asked hard questions. Two people, actually — Erin Kistler and Sruti Bhaumik — who had the standing and the persistence to file a lawsuit that could reshape the industry."
- from the linked Medium article by Ashutosh Singhal, Apr 27, 2026
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