🇺🇸 United States · AI Bias Audit Framework
A two-artifact deliverable: an Executive Summary Word document for sign-off (Risk Classification Scorecard, top 5 bias risks, sign-off block), plus a 9-sheet Excel workbook with Risk Classification by AI Use Case (Unacceptable / High / Limited / Minimal tiering), 34-item bias audit checklist with intake-pre-filled customer answers, fairness testing protocol with thresholds and acceptance criteria, RACI matrix, permitted/prohibited use cases, monitoring & remediation plan, prioritised action plan, and a live Dashboard with native radar + doughnut charts that auto-refresh as you mark items Done.
The output is anchored on the regulations that apply to AI deployments in US. The top frameworks cited:
Developers of covered ADMT must give deployers technical documentation (intended uses, categories of training data, known limitations, usage instructions); deployers must notify individuals before ADMT use in a consequential decision and disclose an adverse outcome within 30 days; consumers may request data correction and meaningful human review. Core obligations begin 1 January 2027.
AI developers and deployers must avoid prohibited uses, provide clear disclosures when consumers interact with AI in consequential contexts, conduct algorithmic-discrimination assessments for in-scope systems, and report adverse incidents to the Texas Attorney General. Compliance with NIST AI RMF and recognised standards is treated as a rebuttable presumption of reasonable care.
Businesses must disclose automated decision-making logic upon consumer request, allow opt-out of profiling for targeted advertising or significant decisions, and conduct and document risk assessments for high-risk data processing activities.
Operators of bots that interact with California consumers in commercial or electoral contexts must clearly and conspicuously disclose that the consumer is communicating with a bot, with the disclosure designed to inform a reasonable person communicating with the bot. Disclosure must not be hidden behind interaction or buried in a privacy notice.
You describe your organisation and AI estate, then answer 25 self-assessment questions across four phases (use-case characterisation, current bias-testing maturity, governance posture, and a 5-question sector-specific block tailored to HR / Healthcare / Financial Services / Government / Education / Insurance / Universal). The tool maps your stated posture into a structured, evidence-based bias audit framework ready for your compliance, legal, and AI-governance practitioners.
The Executive Summary Word document is a one-page sign-off artifact — Risk Classification Scorecard, top 5 bias risks tied to specific AI systems, 30/90/365-day path forward, sign-off block, embedded heatmap + doughnut + gauge charts. The detailed Excel workbook is the working remediation instrument: tier each AI tool, pre-filled audit checklist, fairness testing protocol with explicit thresholds, RACI ownership, permitted/prohibited lists, monitoring cadence, action plan, and a live Dashboard. Both are AI-assisted drafting aids intended to accelerate review by qualified practitioners.
$39 · one-time — answer a 6-question intake (including jurisdiction = US), and download your tailored document immediately.
Audit AI Bias →Also available framed for your sector → see industry-specific pages