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Algorithmic Fairness Compliance Evidence & Implementation Kit

$249.00
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Algorithmic Fairness Compliance for US Product Counsel · map liability, inventory statutes, justify the metric, document the model, defend the decision
Turn algorithmic fairness from an unbounded litigation exposure into documented, defensible, jurisdiction-mapped controls.
Every control handed to you adopt-ready, from the disparate impact and disparate treatment liability mapping and a statute inventory across credit, employment, housing and advertising, through a fairness metric chosen and justified against the impossibility result, model documentation an examiner can follow, testing and monitoring with the four-fifths screen, and a governance, vendor and litigation-readiness record.
Ready in a weekend, not a quarter.

Here is the honest situation. Here is the honest situation. Algorithmic decisioning now sits inside credit, hiring, tenant screening and ad delivery, and every one of those is already governed by an anti-discrimination or consumer-protection regime that predates the model, ECOA and Regulation B on credit, Title VII and the four-fifths rule on employment, the Fair Housing Act on housing, and FTC Act Section 5 across all of it, with newer instruments like NYC Local Law 144 and the Colorado AI Act layered on top. Most product teams ship the model first and reach for a fairness metric only when a plaintiff, a regulator or a reporter asks, and by then the exposure is unbounded because no one wrote down which legal theory applies, which metric was chosen, or why. Fairness is not a single number you can bolt on at the end, it is a documented set of choices you make deliberately and can defend.

This Kit removes the guesswork. It is algorithmic fairness compliance written as adopt-ready controls, so the liability theory is mapped to each use case, the governing statutes and jurisdictions are inventoried, a fairness metric is selected and justified in writing, the model is documented the way an examiner reads it, disparate impact is tested for and monitored over time, and every decision is held in a record you can put in front of a regulator or opposing counsel.

What you get, the moment you buy

18
Controls, adopt-ready. Every control, written so you personalize and apply it.
18
Evidence-they-examine checklists. For each control, exactly what a reviewer examines, plus where teams fall short, so you close the gap first.
1
Control Matrix, pre-built. Every control in a working spreadsheet, ready to record status, owner and evidence location.
1
Gap & Readiness Assessment. Score each control and the workbook returns your readiness as a single percentage, and exactly what to fix next.

Grounded in US anti-discrimination and consumer-protection practice, including disparate treatment and disparate impact theory, the four-fifths rule under the EEOC selection guidelines, ECOA and Regulation B adverse action, the Fair Housing Act and HUD disparate impact analysis, FTC Act Section 5, NYC Local Law 144 bias audits for automated employment decision tools, the Colorado AI Act duty of reasonable care, the fairness-metric impossibility result, model documentation, vendor automated-decision due diligence, and litigation defensibility.

Choose and document the fairness, do not discover it in discovery
A decisioning system shipped without a written fairness position carries an unmanaged discrimination-and-enforcement tail, and the fix is not a single metric but a deliberate record of the legal theory, the chosen metric and the reason it was chosen. This Kit builds the liability mapping, the statute and jurisdiction inventory, the fairness-metric justification, the model documentation, the disparate impact testing and monitoring, and the governance, vendor and litigation-readiness record that make the outcome defensible before anyone asks.

What one control looks like

This is the opening control, where the analysis begins. All 18 are built to this depth.

ALGOFAIR-1 Map each algorithmic decision to a governing liability theory LEGAL THEORY AND LIABILITY MAPPING
Put this control in place

Require [your organization name] to maintain a register that links every automated or model-assisted decision to the specific liability theories it can trigger, including Title VII disparate impact, ECOA and Regulation B discrimination, Fair Housing Act discrimination, and FTC Act Section 5 unfairness, with the responsible legal owner named for each.

Control note.

Start the register from the decision the model influences, not the model itself, because one model can feed several legally distinct decisions.

Evidence a reviewer examines
  • Liability mapping register listing each decision system and its associated legal theories
  • Named legal owner and product owner recorded against each entry
  • Dated review notes showing the register is refreshed when a model or use case changes
  • Cross-reference from each entry to the relevant statute or rule citation
Common finding they raise: Teams often catalogue models by technical function but never connect each one to the concrete causes of action it creates, so legal exposure is discovered only after a complaint or regulator inquiry.

Why this is not another template pack

  • The analysis is engineered. A model that passes one fairness check proves nothing if no one recorded which theory applies or why that metric was chosen. This tells you how to map liability, inventory statutes, select and justify a metric, document, test and defend, for every control.
  • The specifics built in. Disparate treatment versus disparate impact, the four-fifths rule, ECOA and Regulation B adverse action reasons, Fair Housing Act screening, FTC Act Section 5, NYC Local Law 144 bias audits, the Colorado AI Act duty of care, the impossibility of satisfying every fairness definition at once, and vendor automated-decision due diligence are written into the controls, not left generic.
  • Built on real practice, not one lawsuit. The controls are principle-level, so they hold across credit, employment, housing and advertising and stay useful as state AI laws and enforcement priorities change.

Who buys this

Product counsel, privacy and regulatory lawyers, and AI governance leads accountable for algorithmic decisioning in credit, employment, housing or advertising.

By the end of the weekend you will have
✓  An adopt-ready control for all 18 areas
✓  A completed control matrix
✓  The evidence a regulator and opposing counsel examine
✓  A liability mapping that separates disparate treatment from disparate impact for each use case
✓  A statute and jurisdiction inventory, a justified fairness metric, model documentation, a four-fifths and disparate impact testing loop, and a litigation-readiness record
✓  A readiness percentage and a fix list

Common questions

Is it really editable? Yes. Word and Excel files you own and adapt. No portal, no subscription.

Does it cover the whole compliance picture? Yes. Legal theory and liability mapping, statutory scope and jurisdiction inventory, fairness metric selection and justification, documentation and defensibility, testing, validation and monitoring, and governance, vendor and litigation readiness each have their own controls with their own evidence.

Is this tied to one statute or one use case? No. The controls are principle-level, disparate treatment and disparate impact, the four-fifths rule, ECOA and Regulation B, the Fair Housing Act, FTC Act Section 5, NYC Local Law 144, the Colorado AI Act, fairness-metric justification, model documentation and vendor due diligence, so they apply across credit, employment, housing and advertising and across jurisdictions.

Who is it for? Product counsel, privacy and regulatory lawyers, and AI governance leads who must make algorithmic decisioning fair and prove it.

Do not let a model you assumed was fair become the disparate impact a plaintiff or a regulator finds, or a fairness choice you never wrote down become an exposure you cannot defend.
Every control is fast to adopt with the Kit. It is instant, and it is guaranteed.
Add it to your cart and be ready this weekend.

Instant digital download · 30-day money-back guarantee · The Art of Service Pty Ltd, GPO Box 2673, Brisbane QLD 4001 · support@theartofservice.com

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