Un Claude Skill qui prend votre liste de postes, votre inventaire d’outils et votre dossier de preuves, et renvoie une matrice de contrôles indiquant quelles obligations liées à l’IA en emploi s’appliquent à quel poste, quels contrôles vous pouvez réellement prouver et quelles lacunes accumulent des amendes au jour le jour. Il évalue les artefacts que vous fournissez — une URL d’audit de biais publiée, un export d’horodatages de consentement, un runbook de suppression — et non les affirmations du vendor, et il n’émet jamais de verdict conforme / non conforme. Le résultat est ce que vous transmettez au juridique pour que sa première heure commence aux questions d’appréciation plutôt qu’à « quels outils utilisez-vous, et où ? »
Quand l’utiliser
Vous allumez un intervieweur IA, une présélection vidéo par IA ou un classement de CV, et quelqu’un a demandé quelle était l’exposition avant la mise en production.
Un poste vient d’ouvrir dans une juridiction que votre stack n’avait jamais couverte. Les postes ouverts au remote sont le déclencheur habituel : une seule annonce « US-wide » peut activer les obligations de New York City, de l’Illinois et de la Californie d’un coup.
Le renouvellement annuel de l’audit de biais de NYC approche et vous devez savoir quels outils entrent dans le périmètre avant de réserver l’auditeur — les missions d’audit se chiffrent par outil.
Un candidat a demandé comment la décision a été prise, ou la suppression de son entretien, et personne ne sait quel est le runbook.
Quand NE PAS l’utiliser
Pour produire l’audit de biais lui-même. La NYC Local Law 144 exige un auditeur indépendant sans relation d’emploi ou financière avec l’employeur susceptible de compromettre cette indépendance. Un skill que vous exécutez vous-même ne peut pas être cet auditeur. Ce skill vérifie qu’un audit indépendant existe, qu’il est dans les délais et qu’il est publié dans la forme requise.
Comme validation finale. Il n’y a délibérément aucun score agrégé dans le résultat. Un chiffre invite quelqu’un à le capturer en image pour le coller dans un board deck comme certificat de bonne santé.
Après réception d’une plainte ou d’une mise en demeure. À ce stade, l’ensemble des artefacts devient une pièce de discovery et le juridique pilote. Produire une évaluation interne parallèle sur les mêmes faits crée un document dont vous n’aviez pas besoin.
Sur des stacks sans scoring automatisé. Si un humain lit chaque candidature et que rien ne classe ni ne filtre, l’essentiel de la matrice ne s’applique pas.
Hors des États-Unis. La matrice fournie couvre uniquement les règles fédérales, étatiques et municipales américaines. Les obligations en emploi de l’annexe III de l’EU AI Act relèvent d’un autre périmètre et exigeraient leur propre fichier de référence.
Setup
Déposez le bundle à apps/web/public/artifacts/ai-interview-compliance-audit-skill/SKILL.md dans votre répertoire de skills Claude Code, avec le dossier references/ à côté.
Faites relire la matrice une fois par un avocat.references/1-jurisdiction-matrix.md contient chaque paramètre légal auquel le skill se réfère — la fenêtre de préavis de 10 jours ouvrés de NYC, la fenêtre de destruction de 30 jours de l’Illinois, le plancher de conservation de quatre ans de la Californie. Une passe de relecture, puis vous maintenez la date checked: à jour. Le skill refuse d’évaluer si cette date dépasse 90 jours.
Remplissez l’inventaire.references/2-tool-and-stage-ledger.md demande les postes avec leurs lieux de travail, et une ligne par outil qui touche un candidat entre la candidature et l’offre. Incluez les outils que vous n’avez pas achetés pour présélectionner — les match scores de l’ATS et les fit scores des outils de sourcing sont ceux que les équipes oublient, et ils classent.
Notez la capacité de revue. La partie C de l’inventaire demande combien de candidatures un humain examine réellement par poste. « 400 candidats, le recruteur traite le top 40 » est le fait qui transforme un outil de classement en filtre de fait, quel que soit le nom que lui donne l’écran de configuration.
Constituez le dossier de preuves selon references/3-evidence-pack-index.md. Quinze lignes d’artefacts ; écrivez MISSING là où il manque. Cette première passe est généralement là où le vrai constat apparaît.
Ce que le skill fait réellement
Six étapes. Le périmètre se règle avant toute évaluation de contrôle, parce que la même configuration est licite dans un État et constitue une violation par jour dans un autre — et parce que l’erreur la plus courante en pratique consiste à cadrer l’audit sur le siège de l’entreprise plutôt que sur l’endroit d’où les candidats postulent.
Régler le périmètre. Construit une matrice poste × juridiction × étape. Si un poste n’a pas de liste de lieux de travail, le skill s’arrête et pose la question au lieu de la déduire de l’adresse de l’entreprise. Les postes ouverts à des États pour lesquels le dossier de preuves n’a aucun artefact reviennent en gap, pas en not-applicable.
Classer chaque outil à partir de la configuration. Quatre questions : la sortie déclenche-t-elle un changement d’étape à un seuil quelconque ? trie-t-elle une liste que le recruteur traite de haut en bas ? un humain voit-il le score avant de trancher ? analyse-t-elle de la vidéo ou de l’audio à la recherche de caractéristiques servant à évaluer l’aptitude ? L’étiquette du vendor occupe sa propre colonne et n’est jamais la réponse. Le test de la Local Law 144 dépend de la question de savoir si la sortie assiste substantiellement ou remplace la décision discrétionnaire, ce qui est un fait sur votre configuration et non sur leur produit — et le vendor a intérêt à le lire étroitement.
Évaluer chaque contrôle sur preuve, avec citation. Quatre statuts : evidenced (artefact cité mot pour mot, avec le passage qui porte la charge), unevidenced (probablement en règle dans les faits, rien à montrer), gap et counsel-review. Il n’existe pas de compliant. Un contrôle sans citation ne peut pas être evidenced — cette règle est ce qui empêche un rapport fluide sur des documents que personne ne détient.
Lancer les vérifications déterministes de dates. L’horloge de l’audit de biais, signalée à 10 mois plutôt qu’à 12 pour laisser le temps de réserver l’auditeur. Le délai de préavis compté en jours ouvrés face au premier passage de l’outil. Le consentement Illinois recueilli avant l’entretien, et non intégré à une confirmation postérieure — l’ordre constitue le contrôle tout entier. Le délai du runbook de suppression face à la fenêtre de 30 jours, et s’il nomme les destinataires en aval et les sauvegardes ou seulement l’ATS principal.
Ordonner la remédiation par exposition. New York City compte chaque jour d’utilisation non conforme d’un outil du périmètre comme une violation distincte, et chaque préavis manquant à un candidat comme sa propre violation distincte, jusqu’à 500 $ pour une première violation et de 500 à 1 500 $ pour les suivantes. Une lacune de préavis sur un poste à 400 candidats par mois s’accumule donc face à un coût de remédiation fixe ; la même lacune sur un poste en pause, non. La liste se trie sur cette différence.
Émettre le rapport. Matrice, résultats déterministes, remédiation, puis les points counsel-review textuellement, avec les deux lectures exposées.
Ce qui a changé récemment, et pourquoi la matrice est un fichier
Le Colorado est la raison pour laquelle les paramètres légaux vivent dans un fichier de référence daté plutôt que dans la tête du modèle. La SB 24-205 — le Colorado AI Act de 2024, avec ses programmes de gestion des risques et ses analyses d’impact annuelles — n’est jamais entrée en vigueur. Sa date d’entrée est passée de février 2026 à juin 2026, puis la SB 26-189, signée le 14 mai 2026, l’a remplacée par un cadre plus étroit d’information et de transparence applicable au 1er janvier 2027 : information préalable à l’usage, description en langage clair dans les 30 jours suivant une décision défavorable, droit de demander une revue humaine et plancher de conservation de trois ans. Toute checklist qui évalue encore des analyses d’impact audite une loi abrogée. L’explication du Colorado AI Act parcourt le texte de remplacement en entier.
L’Illinois a bougé aussi. L’AI Video Interview Act s’applique depuis 2020, mais l’amendement au Human Rights Act interdisant les effets discriminatoires de l’IA — y compris le code postal comme proxy d’une classe protégée — est entré en vigueur le 1er janvier 2026, et les règles de notification du Department of Human Rights sont encore en cours d’élaboration après le retrait d’un premier projet. Les règlements FEHA de Californie sur les systèmes de décision automatisée s’appliquent depuis le 1er octobre 2025, avec un plancher de conservation de quatre ans qui pointe à l’opposé d’une demande de suppression d’un candidat. Le skill expose cette tension au lieu de la trancher.
Le décret de décembre 2025 chargeant une task force du DOJ de contester les lois étatiques sur l’IA figure dans la matrice comme contexte, pas comme contrôle. Aucune règle étatique ci-dessus n’a été écartée. Traitez-le comme une raison de garder les contrôles documentés et transportables, pas comme une raison de retirer une ligne.
Réalité des coûts
Par exécution d’audit — environ 40 à 80k tokens en entrée (matrice, inventaire, textes de préavis, documentation vendor) et 6 à 10k en sortie. Aux tarifs catalogue de Claude Sonnet, cela représente environ 0,30 à 0,60 $ par exécution. Estimation, à partir du profil de tokens d’un stack de trois postes et cinq outils.
Setup — 90 minutes, et ce chiffre n’est honnête que si le dossier de preuves existe déjà quelque part. Les équipes qui le constituent pour la première fois y passent 4 à 8 heures, en grande partie à découvrir qu’un contrôle que tout le monde croyait traité n’a aucun artefact derrière lui.
Temps d’avocat économisé — une première passe d’un avocat en droit du travail externe sur un stack multi-juridictionnel prend 8 à 20 heures à 350-700 $ de l’heure, dont une bonne part en collecte : quels outils, quels postes, quels États, que fait le score. Arriver avec l’inventaire rempli et une matrice évaluée ramène cette collecte en interne. Les questions d’appréciation restent facturées.
Ce qu’il n’économise pas — l’audit de biais indépendant. C’est une mission distincte, chiffrée par outil, et ce skill ne s’y substitue pas.
Métrique de succès
Décompte des unevidenced tendant vers zéro. La répartition entre evidenced et unevidenced à la première exécution constitue la vraie ligne de base. Voir des contrôles passer de unevidenced à evidenced sans le moindre changement opérationnel est le résultat recherché — cela signifie que l’artefact existe désormais.
Horloge d’audit de biais jamais au-delà de 10 mois. Une vérification déterministe qui ne devrait jamais se déclencher deux fois sur le même outil.
Distribution du délai de préavis, pas la moyenne. Suivez le cinquième centile des jours ouvrés entre le préavis et le premier passage de l’outil, par poste. Les moyennes masquent les postes rapides, précisément là où le délai casse.
Temps entre l’ouverture d’un poste dans une nouvelle juridiction et la matrice évaluée. Doit tomber sous la journée une fois l’inventaire en place.
vs alternatives
vs une checklist en spreadsheet. Le statu quo, et il échoue sur deux points précis : il cadre par localisation de l’entreprise plutôt que par poste, et il n’a pas d’horloge, de sorte qu’un audit de biais vieillit en silence au-delà de 12 mois pendant que l’outil continue de tourner. Les étapes 1 et 4 du skill existent à cause de ces deux échecs.
vs les attestations de conformité du vendor.HireVue, Sapia.ai et d’autres publient des résumés d’audit de biais de leurs modèles. Utiles, et ils satisfont les lignes côté vendor. Ils ne satisfont pas les vôtres : l’obligation de la Local Law 144 pèse sur l’employeur ou l’agence de placement, et l’audit qui compte porte sur votre configuration et votre vivier de candidats. L’index de preuves garde les artefacts vendor et employeur dans des colonnes séparées pour que cela ne se confonde pas.
vs un prestataire d’audit dédié. Les cabinets qui réalisent des audits de biais AEDT indépendants font ce que le skill ne peut structurellement pas faire. Utilisez le skill comme passe de préparation avant d’en mandater un — arriver avec un inventaire d’outils déjà classé réduit les allers-retours de cadrage — et comme revérification entre deux audits quand un poste ouvre dans un nouvel État.
vs confier l’ensemble au juridique. Juste pour les questions d’appréciation, cher pour l’inventaire. Le partage que propose ce workflow : vous détenez l’inventaire et le dossier de preuves, le juridique détient la relecture de la matrice et la file counsel-review.
Watch-outs
Le modèle énonce une conclusion juridique.Garde-fou : le vocabulaire de statuts ne contient aucune valeur conforme / non conforme et il n’y a pas de score agrégé. Les questions d’appréciation partent en counsel-review avec les deux lectures imprimées.
Les paramètres légaux dérivent.Garde-fou : les seuils vivent dans references/1-jurisdiction-matrix.md avec une date checked:, et le skill refuse d’évaluer au-delà de 90 jours. Ce paysage a bougé trois fois entre août 2025 et mai 2026.
Une attestation vendor comptée comme votre conformité.Garde-fou : la ligne 14 de l’index de preuves est marquée côté vendor et ne peut satisfaire les lignes d’audit ou de publication de l’employeur.
Cadrer sur le siège.Garde-fou : l’étape 1 n’avance pas sans lieux de travail par poste, et les postes ouverts au remote s’étendent à chaque État de la liste acceptée.
Blanchiment de classification.Garde-fou : la classification provient de faits de configuration consignés dans l’inventaire, avec les données de capacité de revue jointes. Un outil qui classe 400 candidats là où un humain en examine 40 fait un travail de décision, quoi qu’en dise son étiquette.
unevidenced lu comme un feu vert.Garde-fou : ces lignes rejoignent la remédiation aux côtés des lacunes, avec l’artefact manquant nommé.
Conservation et suppression tirant en sens inverse.Garde-fou : le plancher californien de quatre ans et une demande de suppression Illinois se heurtent sur le même enregistrement. L’étape 4 signale le conflit ; le juridique le tranche une fois, et le rapport cite ce mémo.
Stack
Le bundle se trouve à apps/web/public/artifacts/ai-interview-compliance-audit-skill/ et contient :
SKILL.md — la définition du skill
references/1-jurisdiction-matrix.md — les paramètres légaux avec une date checked:
references/2-tool-and-stage-ledger.md — inventaire à remplir des postes, outils et capacité de revue
references/3-evidence-pack-index.md — correspondance contrôle-artefact et trame de préavis et de consentement
Suppose Claude pour l’exécution. Le stack audité comprend généralement un ATS comme Greenhouse et un ou plusieurs outils de présélection IA — HireVue, Sapia.ai ou équivalents.
---
name: ai-interview-compliance-audit
description: Audit a configured AI interviewing and screening stack against the US employment-AI rules that are live today — NYC Local Law 144, the Illinois AI Video Interview Act, the Illinois Human Rights Act AI amendment, California's FEHA automated-decision-system regulations, and Colorado SB 26-189 — and emit a control matrix plus a remediation list ordered by penalty exposure. Grades controls on evidence you supply, not on vendor marketing claims. Produces a readiness report, never a legal conclusion.
---
# AI interview compliance audit
## When to invoke
Use this skill when someone owns a hiring stack that includes AI screening, AI-scored video or async interviews, AI interviewers, or resume-ranking, and needs to know which controls are evidenced, which are missing, and what to hand counsel. Typical triggers: a new AI interviewing vendor going live, a req opening in a jurisdiction the stack has not served before, an annual bias-audit renewal, or a candidate complaint.
Inputs are configuration and artifacts. The skill reads what the stack actually does — which score gates which stage — and what documents exist to prove each control.
Do NOT invoke this skill for:
- **Producing the bias audit itself.** NYC Local Law 144 requires an *independent* auditor with no employment or financial relationship with the employer that would compromise independence. A skill run by the employer is not independent and cannot satisfy that duty. This skill checks whether an independent audit exists, is within its clock, and is published in the required form.
- **A legal opinion, or a "we are compliant" sign-off.** The output is a readiness report with an evidence status per control. It never emits a compliant/non-compliant verdict.
- **Non-US stacks.** The jurisdiction matrix in `references/1-jurisdiction-matrix.md` covers US federal, state, and city rules only. EU AI Act Annex III employment obligations are a different scope and a different reference file.
- **Stacks with no automated scoring at all.** If humans read every application and no tool ranks, scores, or filters candidates, most of the matrix does not attach and the run is wasted effort. Confirm the classification question in step 2 before a full run.
- **Retroactive defense of a decision already challenged.** Once there is a charge or a demand letter, the artifact set is discovery material. Counsel drives; do not generate parallel internal assessments of the same facts.
## Inputs
- Required: `reqs` — the open or planned requisitions in scope, each with the job's work location(s) and whether remote candidates are accepted from other states. Jurisdiction attaches by where the candidate applies for or performs the job, not by where the company is headquartered. See `references/2-tool-and-stage-ledger.md`.
- Required: `tool_ledger` — every tool touching a candidate between application and offer, with the stage it runs at and what its output does (displayed to a recruiter, sorts a list, sets a threshold, advances or rejects automatically). Same file.
- Required: `evidence_pack` — paths or URLs for the artifacts that prove controls: candidate-facing notice text, consent capture record, published bias-audit summary URL, data-retention policy, vendor DPA, deletion-request runbook. See `references/3-evidence-pack-index.md`.
- Optional: `jurisdiction_matrix_path` — override the bundled matrix with your counsel's maintained copy. Recommended once you have one.
- Optional: `as_of` — the date to run clock arithmetic against. Defaults to today.
## Reference files
- `references/1-jurisdiction-matrix.md` — every statutory parameter the skill grades against, with a `checked:` date. The skill reads thresholds from this file and never from model memory.
- `references/2-tool-and-stage-ledger.md` — fillable inventory template for reqs, tools, stages, and what each score actually gates.
- `references/3-evidence-pack-index.md` — control-to-artifact mapping, plus scaffolding for the notice and consent language each rule requires.
## Method
Six steps. Scope resolves before any control is graded, because the same configuration is lawful in one jurisdiction and a per-day violation in another, and because the most common real-world error is scoping the audit to company headquarters.
### 1. Resolve scope before grading anything
Build a req × jurisdiction × stage matrix from `reqs`. A single remote-eligible req can attach NYC, Illinois, California, and Colorado at once. If any req lacks a work-location list, stop and ask — do not infer jurisdiction from the company address, and do not grade a partial matrix.
Flag reqs open to candidates in states the evidence pack has no artifacts for. That cell is `gap`, not `not-applicable`.
### 2. Classify each tool from configuration, not from its label
For each tool in `tool_ledger`, answer from the configuration:
- Does its output gate a stage transition automatically, at any threshold?
- Does it sort or rank a candidate list that a recruiter works top-down?
- Does a recruiter see the score before making the advance/reject call?
- Is it analyzing a video or audio interview for characteristics used to evaluate fitness?
Read the vendor's own classification as an input to be checked, not as the answer. A vendor has an incentive to say its product merely assists, and the LL 144 test turns on whether the output substantially assists or replaces discretionary decision-making — which is a fact about your configuration, not about their product. Record the classification, the configuration facts that drove it, and dissent from the vendor label explicitly where it exists.
The video/audio question is separate and additive: the Illinois AI Video Interview Act attaches to AI analysis of video interviews for Illinois positions regardless of whether the tool also qualifies as an automated employment decision tool.
### 3. Grade each control on evidence, with a citation
For each applicable control in the jurisdiction matrix, assign exactly one status:
- `evidenced` — an artifact in the evidence pack satisfies the control. Requires a verbatim citation: file path or URL, plus the quoted passage that does the work.
- `unevidenced` — the control is plausibly satisfied in practice but no artifact was supplied. This is not a pass. It is the state that turns into a gap the moment anyone asks for proof.
- `gap` — the artifact exists and does not satisfy the control, or the required artifact does not exist.
- `counsel-review` — the determination turns on a judgment call (whether a given tool substantially assists a decision, whether a notice's placement counts as before the interview). The skill states the facts and the competing readings, and stops.
There is no `compliant` status and no aggregate compliance score. Both invite the reader to treat the report as a conclusion. A control with no citation cannot be `evidenced`, which is the guard against a fluent report about documents nobody actually has.
### 4. Run the deterministic date and arithmetic checks
These are computed, not judged, and they surface first because they are the cheapest failures to fix:
- **Bias-audit clock.** Parse the published date of the most recent bias audit. Flag at 10 months, not at 12, so there is runway to schedule the auditor. Past 12 months the tool is out of clock while still in use — which accrues per-day.
- **Notice lead time.** Compare the candidate-notice timestamp to the tool's first run against that candidate. The NYC requirement is at least 10 business days, counted in business days.
- **Consent ordering.** For Illinois video interviews, confirm consent is captured before the interview, not bundled into a post-interview acknowledgment. Ordering is the whole control.
- **Deletion SLA.** Check the deletion runbook's stated turnaround against the 30-day statutory window, and confirm it names downstream recipients and backups rather than only the primary system.
- **Retention floor.** California's FEHA regulations require automated-decision-system records — selection criteria, outputs, audit findings — kept four years. Flag any retention policy that deletes earlier, including a well-intentioned privacy-minimization policy. Cross-check the deletion SLA against the retention floor and surface the conflict rather than resolving it; that tension is a counsel call.
### 5. Order remediation by exposure, not by effort
Rank gaps by how the penalty accrues. NYC counts each day an in-scope tool runs out of compliance as a separate violation, and each missed candidate notice as its own separate violation — so a missing notice on a high-volume req compounds daily against a fixed remediation cost. A gap on a paused req does not. Give each gap: the accrual shape, the artifact that would close it, and who owns it.
### 6. Emit the report
Control matrix first, then the deterministic-check results, then remediation ordered by exposure, then the `counsel-review` list verbatim.
## Output format
```markdown
# AI interview compliance readiness — as of 2026-07-28
Matrix version: references/1-jurisdiction-matrix.md (checked: 2026-07-28)
## Scope
| Req | Work locations | Attaches |
|---|---|---|
| ENG-411 | NYC + remote US | NYC LL 144; IL AIVIA; IL HRA; CA FEHA ADS |
## Tool classification
| Tool | Stage | Output gates | AEDT (configuration) | Vendor label | Dissent |
|---|---|---|---|---|---|
| HireVue | async video screen | recruiter sees score before advance/reject | yes | "decision support" | yes — score precedes the call |
## Controls
| Jurisdiction | Control | Status | Citation |
|---|---|---|---|
| NYC LL 144 | Independent bias audit within 12 months | evidenced | careers.example.com/aedt — "date of most recent bias audit: 2026-03-14" |
| NYC LL 144 | 10 business days candidate notice | gap | notice fires at invite, 2 business days before |
| IL AIVIA | Consent captured before interview | counsel-review | consent is on the invite page; candidate can start without scrolling |
## Deterministic checks
- Bias-audit clock: 4.5 months elapsed — OK (flags at 10)
- Notice lead time: 2 business days vs 10 required — FAIL
- Deletion runbook: names primary ATS only; no downstream or backup step — FAIL
## Remediation (by exposure)
1. NYC notice lead time — ENG-411 is live and high-volume; each missed notice is a separate violation and each day of use accrues. Fix: move notice to the application confirmation. Owner: TA ops.
## Counsel review
1. IL AIVIA consent placement on ENG-411. Facts: [...]. Competing readings: [...].
```
## Watch-outs
- **The model asserts a legal conclusion.** *Guard:* the status vocabulary has no compliant/non-compliant value and the report has no aggregate score. Judgment calls route to `counsel-review` with both readings stated.
- **Statutory parameters drift.** *Guard:* thresholds live in `references/1-jurisdiction-matrix.md` with a `checked:` date; the skill refuses to grade and warns if that date is more than 90 days old. This landscape moved three times between August 2025 and May 2026.
- **Vendor attestation counted as employer compliance.** *Guard:* the evidence index separates vendor artifacts from employer artifacts, and a vendor bias-audit summary can only satisfy vendor-side rows. The LL 144 duty sits with the employer or employment agency.
- **Scoping to headquarters.** *Guard:* step 1 will not proceed without per-req work locations, and remote-eligible reqs expand to every state in the accepted-candidate list.
- **Classification laundering.** *Guard:* classification is answered from configuration facts recorded in the ledger; the vendor's label is a separate column, and disagreement is printed rather than reconciled.
- **Unevidenced read as a pass.** *Guard:* `unevidenced` rows sort into the remediation list alongside gaps, with the missing artifact named.
- **Retention and deletion pulling opposite ways.** *Guard:* step 4 surfaces the conflict between a deletion request and the four-year records floor as a flagged tension rather than picking one.
# Jurisdiction matrix
```yaml
checked: 2026-07-28
checked_by: REPLACE_WITH_YOUR_NAME
```
The skill reads every threshold from this file and never from model memory. Update `checked:` whenever you re-verify against primary sources. The skill warns and refuses to grade if the date is more than 90 days old — this landscape moved three times between August 2025 and May 2026, and a stale matrix produces a confident report against rules that no longer apply.
This is a working parameter table maintained by the employer, not legal advice. Have counsel review it once and then keep it current.
---
## NYC Local Law 144 of 2021 — automated employment decision tools
**Status:** in effect; enforced by the Department of Consumer and Worker Protection since 2023-07-05.
**Attaches when:** an automated employment decision tool (AEDT) is used to substantially assist or replace discretionary decision-making for a job or promotion, for a position located in New York City. Employment agencies are covered alongside employers.
| Control | Parameter | Notes |
|---|---|---|
| Independent bias audit | Within the 12 months preceding use, renewed annually | Auditor must have no involvement in using, developing, or distributing the tool and no employment or financial relationship with the employer that compromises independence |
| Published audit summary | Publicly available on the careers or jobs section of the website | Must include the date of the most recent bias audit and the distribution date of the tool |
| Metrics published | Selection or scoring rates and impact ratios by sex, by race/ethnicity, and by intersectional sex × race/ethnicity categories | The four-fifths screen is the conventional read on the impact ratio |
| Candidate notice | At least **10 business days** before use | Business days, not calendar days |
| Notice contents | That an AEDT will be used; the job qualifications and characteristics it assesses | |
| Data disclosure on request | Within **30 days** of a written request, if not already published | Data collected, source of the data, retention policy |
| Penalty — first violation | Up to $500 | |
| Penalty — subsequent violations | $500 to $1,500 each | |
| Accrual | Each day an AEDT is used in violation is a separate violation; each failure to provide a required notice is a separate violation | This is what makes notice gaps on high-volume reqs the top remediation item |
**The load-bearing determination** is whether the tool substantially assists or replaces discretionary decision-making. It turns on your configuration, not the vendor's product description.
---
## Illinois Artificial Intelligence Video Interview Act (820 ILCS 42)
**Status:** in effect since 2020-01-01.
**Attaches when:** an employer asks applicants to record video interviews and uses AI analysis of those videos to consider applicants' fitness, for positions based in Illinois.
| Control | Parameter | Source |
|---|---|---|
| Notice before the interview | Applicant is told AI may be used to analyze the video and consider fitness | Section 5 |
| Explanation before the interview | How the AI works and the general types of characteristics it uses to evaluate applicants | Section 5 |
| Consent before the interview | Consent to be evaluated by the AI as described; no consent means no AI evaluation | Section 5 |
| Sharing limited | Videos shared only with persons whose expertise or technology is necessary to evaluate fitness | Section 10 |
| Destruction on request | Within **30 days** of the applicant's request, delete the interviews and instruct every other recipient to delete their copies, including all electronically generated backup copies | Destruction section |
| Demographic reporting | Applies only to employers that rely **solely** on AI analysis of the video to decide whether an applicant advances to an in-person interview. Report race and ethnicity of applicants afforded and not afforded in-person interviews, and of applicants hired | Reporting section |
| Reporting deadline | Annually by **December 31**, covering the 12-month period ending the preceding November 30, to the Department of Commerce and Economic Opportunity | DCEO reports to the Governor and General Assembly by July 1 on whether the data discloses racial bias |
**Ordering is the control.** Notice, explanation, and consent must all precede the interview. A post-interview acknowledgment does not cure it.
**The sole-reliance trigger** is narrow and most stacks fall outside it because a recruiter reviews before the in-person decision. Record the fact that puts you outside it; do not assume it.
---
## Illinois Human Rights Act, as amended by HB 3773
**Status:** statutory obligations in effect since 2026-01-01. Illinois Department of Human Rights rulemaking is still open — proposed amendments to Title 44, Part 2520 of the Illinois Administrative Code were published 2026-05-15, after an earlier draft was withdrawn.
| Control | Parameter |
|---|---|
| Discriminatory-effect prohibition | AI may not be used with the effect of subjecting employees or applicants to discrimination on a protected basis, in recruitment, hiring, promotion, renewal, selection for training or apprenticeship, discharge, discipline, tenure, or terms and conditions of employment. Intent is not required |
| Proxy prohibition | Using zip code as a proxy for a protected class is prohibited outright |
| Notice | Required whenever AI is used in a covered employment decision, regardless of whether the use has any discriminatory purpose or effect |
**Notice mechanics — timing, form, and content — are the subject of the open rulemaking.** Grade the notice-existence row now and put the mechanics row in `counsel-review` until the rules land.
---
## California — FEHA regulations on automated-decision systems
**Status:** in effect since 2025-10-01.
**Attaches when:** an employer uses artificial intelligence, machine learning, algorithms, statistics, or other data processing to facilitate human decision-making on recruitment, hiring, or promotion of applicants or employees in California.
| Control | Parameter |
|---|---|
| Records retention | **Four years** for automated-decision-system records, including selection criteria, relevant outputs, and audit findings |
| Third-party liability | The employer is answerable for discriminatory outcomes of a tool sourced from a vendor or run by an agent |
| Anti-bias testing | Not mandated. Evidence of testing may support a defense; the absence of it is admissible against the employer |
**The retention floor conflicts with privacy-minimization defaults and with deletion requests.** Surface the tension; do not resolve it in the report.
---
## Colorado SB 26-189 — automated decision-making technology
**Status:** signed 2026-05-14; effective **2027-01-01**. Attorney General rulemaking pending, and key terms will be defined there.
This replaced SB 24-205, the 2024 Colorado AI Act, which never took effect. SB 24-205's delayed start moved from 2026-02-01 to 2026-06-30 (SB 25B-004, signed 2025-08-28) and was then superseded. **The risk-management program, annual impact assessments, and broad algorithmic-discrimination duties of SB 24-205 are gone.** Any checklist still grading against them is auditing a repealed statute.
| Control | Parameter |
|---|---|
| Pre-use notice | Clear notice that a covered automated decision-making technology will be applied, before use |
| Post-adverse-outcome disclosure | Plain-language description of the technology's role, within **30 days** after a consequential decision producing an adverse outcome |
| Human review | The individual may request meaningful human review and reconsideration of the decision |
| Records | Retain relevant records at least **three years** |
Grade Colorado rows as forward-looking readiness until the effective date. Do not report a Colorado gap as accruing exposure today.
---
## Federal posture — context, not a control
Executive Order "Ensuring a National Policy Framework for Artificial Intelligence" (signed 2025-12-11) directs a Department of Justice AI Litigation Task Force, stood up from 2026-01-10, to challenge state AI laws in federal court, and directed Commerce to identify state laws suitable for challenge by March 2026.
**No state law in this matrix has been displaced by it.** Preemption of a state statute requires a court to say so or Congress to act. Treat the federal posture as a reason to keep controls documented and portable — not as a reason to retire any row above. Note it in the report's assumptions section so the reader knows it was considered.
---
## Not covered by this matrix
Add rows before relying on the skill for any of these: EU AI Act Annex III employment obligations; Maryland's facial-recognition consent requirement; Texas TRAIGA; New York State requirements distinct from the City's; sector rules for federal contractors; and any collective-bargaining commitments on automated evaluation.
# Tool and stage ledger
Fill this out before the first run. It is the input the classification step reasons over, and it is the artifact that makes a later audit reproducible. Replace every `REPLACE_` value.
## Part A — Requisitions in scope
Jurisdiction attaches by where the job is located and where the candidate applies from, not by where the company is headquartered. A remote-eligible req attaches every state in its accepted-candidate list.
| Req ID | Title | Work locations | Remote-eligible states accepted | Volume (applicants/mo) | Status |
|---|---|---|---|---|---|
| REPLACE_ENG-411 | Backend Engineer | New York, NY | US-wide except CO | 400 | open |
| REPLACE_SLS-102 | Account Executive | Chicago, IL | IL only | 120 | open |
| REPLACE_OPS-220 | RevOps Analyst | Remote US | CA, NY, IL, TX | 60 | planned |
If a req's accepted-state list is "anywhere in the US," write that out and expect the matrix to attach every jurisdiction in `1-jurisdiction-matrix.md`. That is usually the finding, not a formality.
## Part B — Tool ledger
One row per tool that touches a candidate between application and offer. Include tools you did not buy for screening but that score or rank anyway — ATS match scores and sourcing-tool fit scores are the ones teams forget.
| Tool | Stage | What it outputs | Who sees it and when | Does it gate a transition? | Threshold | Video/audio analysis? | Vendor's own label |
|---|---|---|---|---|---|---|---|
| REPLACE_HireVue | async video screen | competency scores 1-5 | recruiter, before advance/reject | no auto-advance; recruiter decides | none | yes | "decision support" |
| REPLACE_Greenhouse | application review | match score, sorts the list | recruiter, list is worked top-down | no | none | no | "ranking aid" |
| REPLACE_vendor | resume screen | pass/fail | nobody; auto-rejects | yes | score under 60 auto-rejects | no | "efficiency filter" |
### The four classification questions
Answer from configuration. The vendor's label goes in its own column and is never the answer.
1. **Does the output gate a stage transition automatically, at any threshold?** An auto-reject threshold is the clearest case.
2. **Does it sort or rank a list a recruiter works top-down?** Rank order changes who gets reviewed at all when volume exceeds review capacity. Record the review-capacity number — "400 applicants, recruiter reviews the top 40" is the fact that matters.
3. **Does a human see the score before making the call?** A score presented before the decision is a different fact from a score available afterward on request.
4. **Does it analyze video or audio for characteristics used to evaluate fitness?** Independent of the other three, and it is what pulls the Illinois AI Video Interview Act in for Illinois-based positions.
### Configuration facts to capture per tool
- Where the score appears in the recruiter's interface, and whether it can be hidden.
- Whether the score is recorded on the candidate record and for how long.
- Whether the vendor retrains on your candidate data, and whether that is contractually disclaimed.
- Which sub-processors receive candidate video or audio. This is the list the Illinois destruction obligation reaches.
- Who at the vendor can access candidate video, and under what contractual limit.
## Part C — Review-capacity reality
Fill this in honestly; it decides whether a ranking tool is functionally a filter.
| Req | Applicants/mo | Applications actually reviewed by a human | Effective filter rate |
|---|---|---|---|
| REPLACE_ENG-411 | 400 | 40 | 90% never human-reviewed |
A ranking tool with a 90% effective filter rate is doing decision-making work regardless of what the configuration screen calls it. Record this and let the classification step use it.
# Evidence pack index
Every control graded `evidenced` needs a citation from this pack: a file path or URL plus the passage that does the work. A control with no artifact is `unevidenced`, and `unevidenced` sorts into remediation next to real gaps — because the difference between "we do this" and "we can show we do this" only matters on the day someone asks, and on that day there is no time to build the artifact.
## Part A — Artifact inventory
Fill in the path or URL. Leave `MISSING` where it is missing; that is the point of the exercise.
| # | Artifact | Satisfies | Side | Location |
|---|---|---|---|---|
| 1 | Published AEDT bias-audit summary page | NYC LL 144 publication + metrics | employer | REPLACE_URL |
| 2 | Independent auditor's report and engagement letter | NYC LL 144 audit + independence | employer | REPLACE_PATH |
| 3 | Candidate AEDT notice text, with the send trigger documented | NYC LL 144 notice + contents | employer | REPLACE_PATH |
| 4 | Timestamp export: notice sent vs tool first run, per candidate | NYC LL 144 10-business-day lead | employer | REPLACE_PATH |
| 5 | Illinois video notice + explanation text | 820 ILCS 42 Section 5 | employer | REPLACE_PATH |
| 6 | Consent capture records with timestamps | 820 ILCS 42 Section 5 ordering | employer | REPLACE_PATH |
| 7 | Sub-processor list for video and audio | 820 ILCS 42 Section 10 sharing limit | employer | REPLACE_PATH |
| 8 | Deletion runbook naming downstream recipients and backups | 820 ILCS 42 destruction, 30 days | employer | REPLACE_PATH |
| 9 | Sole-reliance determination memo | 820 ILCS 42 reporting trigger | employer | REPLACE_PATH |
| 10 | Illinois HRA AI-use notice text | IL HRA as amended | employer | REPLACE_PATH |
| 11 | ADS records retention schedule showing four years | CA FEHA ADS | employer | REPLACE_PATH |
| 12 | Anti-bias testing results, if any were run | CA FEHA ADS defense | employer | REPLACE_PATH |
| 13 | Vendor DPA with retraining and access terms | supports 7, 8, 11 | vendor | REPLACE_PATH |
| 14 | Vendor's own bias-audit summary | vendor-side rows only | vendor | REPLACE_URL |
| 15 | Data-retention policy published on the careers site | NYC LL 144 disclosure on request | employer | REPLACE_URL |
**Row 14 cannot satisfy rows 1 or 2.** A vendor's audit of its model is not the employer's audit of the employer's use. The NYC duty sits with the employer or employment agency. Vendors sell attestation packets that read as if they close the employer's obligation; they close the vendor's.
## Part B — Notice scaffolding
Adapt; do not paste. The bracketed values are the ones that make a notice specific enough to be worth anything, and a notice that omits them is the most common `gap` finding.
### NYC AEDT notice — at least 10 business days before use
> We use an automated employment decision tool to help evaluate applications for [JOB TITLE]. The tool assesses the following job qualifications and characteristics: [LIST THEM — the actual assessed dimensions, not "fit"]. The results of our most recent bias audit and our data-retention policy are published at [URL]. You may request an alternative selection process or an accommodation by contacting [ADDRESS]. To request information about the data we collect for this tool, its source, and our retention policy, contact [ADDRESS]; we will respond within 30 days.
Send it on the application-confirmation event, not on the assessment invite. Invite-time sending is what fails the 10-business-day count on fast-moving reqs, and it is the single most common lead-time failure.
### Illinois video interview — notice, explanation, and consent, all before the interview
> This interview will be recorded and may be analyzed by artificial intelligence to consider your fitness for [JOB TITLE]. How it works: [PLAIN-LANGUAGE EXPLANATION — what the system does with the recording]. The general types of characteristics it uses to evaluate applicants are: [LIST THEM]. Your video will be shared only with people whose expertise or technology is necessary to evaluate your fitness for this position. You may request that we delete your interview at any time by contacting [ADDRESS]; we will delete it, and instruct everyone who received a copy to delete theirs including backups, within 30 days.
>
> [ ] I consent to being evaluated by artificial intelligence as described above.
The consent checkbox must be reachable and actionable before the recording starts. If a candidate can begin recording without passing the consent control, that is a `counsel-review` at best.
### Illinois HRA AI-use notice
Notice mechanics are in open rulemaking as of the `checked:` date in `1-jurisdiction-matrix.md`. Give notice that AI is used in the decision, keep the text versioned, and grade the mechanics row as `counsel-review` until the rules land.
## Part C — Evidence hygiene
- **Version the notice text and keep the diffs.** The question is never "what does the notice say," it is "what did it say on the day this candidate applied."
- **Timestamps beat policies.** A policy saying notice goes out 10 days ahead is weaker evidence than an export showing it did.
- **Keep the negative determinations.** The memo explaining why a tool is out of scope is an artifact. An undocumented determination reads later as an oversight.
- **Watch the retention conflict.** The four-year California floor and a candidate's Illinois deletion request point opposite ways on the same record. Decide it with counsel once, write the decision down, and cite that memo rather than re-deciding per request.
