Who gets hired
Your AI can’t disfavor candidates on protected class: race, sex, age, disability. Outcomes are scrutinized, intent or not.
We monitor what the law cares about — continuously and under privilege. You keep moving.
AI decides who’s hired, approved, flagged. It also writes, calls, sells — faster than anyone can review. Most laws don’t ask who did it. They ask what happened.
Your AI can’t disfavor candidates on protected class: race, sex, age, disability. Outcomes are scrutinized, intent or not.
Your AI’s lending calls carry liability for protected-class outcomes, plus a duty to explain denials.
Your AI steering ads or scoring tenants can’t disfavor protected classes; disparate impact alone is liability.
Your AI in patient care can’t yield discriminatory outcomes; HHS now reaches decision-support tools directly.
Your AI rating risk can’t produce unfair discrimination, and states now make you test and govern the models.
When your AI scores someone, they can might demand the reasons and dispute the result; private suits attach.
Your AI can’t use or infer genetic or family-health data in an employment call; flat ban.
Take federal money and your AI can’t discriminate by race or national origin; one hook into health, schools, benefits.
These duties land state by state, and no two regimes agree: CA, NYC LL144, IL, TX, and counting.
Every false thing your AI tells a customer; FTC, 50 state AGs, and under state law the customer.
How your AI pressures, steers, or exploits a customer; actionable even when nothing it said was false.
Your AI inside a financial product can be unfair, deceptive, or abusive; CFPB and state regulators bring these.
When your AI asserts a falsehood about a real person, tort liability attaches; no statute, no cap.
If your AI conjures someone’s face, name, or voice to sell, that's their property and their lawsuit.
Reviews or testimonials your AI fabricates are deceptive per se, and the FTC penalizes them.
Your AI dialed it: $500–$1,500 a message, and consumers can sue.
How your AI contacts people about debts (harassment, falsehoods, timing) all still bind; private right of action.
Your AI’s marketing mail must honor unsubscribes and identify the sender; liability accrues per message.
If your AI profiles or targets children, consent rules are strict and FTC penalties steep.
If your AI reads a face or voiceprint, each person gets a private suit and statutory damages.
PHI moving through your AI’s training or inference triggers privacy, security, and breach duties; OCR enforces.
When your AI monitors workers, the NLRB can treat it as interfering with protected organizing.
Your AI’s chat, scoring, and scheduling must work for people with disabilities; DOJ-readable, private suits.
We measure real outcomes with custom legal classifiers — a live read on what your AI does. Not a yearly audit. Not policy document. Where you stand, and the moment it changes.
Your diligence can create evidence for the other side. But skip it, and not knowing becomes the exposure.
Privilege is the answer. Working through counsel, we examine your systems without building the other side’s case — turning diligence into a record that works for you, not against you.
We don’t sell questionnaires. We put our questions to your systems and measure the answers.
Our team takes you from your risk map to live oversight in weeks.
We map your systems and data onto your legal obligations. Counsel ranks the risk.
We bind that data to custom legal classifiers. Counsel sets the thresholds.
We monitor continuously, surfacing findings to counsel. Counsel tells you what it means.
Under privilege, the more you know, the stronger your position gets — which is exactly how it’s supposed to work.
Counsel sees a live record and actionable advice, not a quarterly memo. Pilots stuck in legal review finally ship.
Monitoring reaches the exposure — customer-facing, adverse-outcomes. The use cases you’d have shelved come back on the table.
We care about outcomes, not how you got there. The model underneath is yours to change — what matters stays checked.
We’ve built enterprise systems for regulated enterprises, represented Fortune 500 companies, advised the White House and federal regulators, and led delivery in defense and intelligence environments.
Unpacking the realities behind AI layoff claims.
When CEOs blame the layoffs on AI, they’re borrowing credibility from the moment. Here’s how to tell a real efficiency story from a convenient one — and the four numbers that force the question.
By Joe Ewing, Co-Founder and CTOLet’s get you unstuck. Hop on a short call and we’ll tell you how we can help.
hello@privlex.com