AI Bias Audit Framework for US

US-specific obligations covered

The output is anchored on the regulations that apply to AI deployments in US. The top frameworks cited:

• Colorado Artificial Intelligence Act (SB 24-205, codified at C.R.S. §§ 6-1-1701 to 6-1-1707)state_legislation · Enacted - not yet in force

  Deployers of high-risk AI systems must conduct impact assessments, implement AI risk management programmes, provide consumers with clear disclosure of AI use and adverse action explanations, and notify developers of discovered risks.

• Texas Responsible AI Governance Act (HB 149)state_legislation · In force

  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.

• California Consumer Privacy Act / California Privacy Rights Act (CCPA/CPRA)state_legislation · In force

  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.

• California Bot Disclosure Law (SB 1001 — Cal. Bus. & Prof. Code §§17940-17943)state_legislation · In force

  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.

How the AI Bias Audit Framework approaches this

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.

What you get

• ✓ Two artefacts, two jobs: Executive Summary (.docx) with embedded charts for board sign-off, Detailed Workbook (.xlsx) for the working remediation tracking — no overlap, no confusion.
• ✓ Intake-driven: every gap rating, risk-tier classification, and remediation action ties back to your stated YES/NO/PARTIAL/UNSURE answer — no generic checklist boilerplate.
• ✓ Sector-specific: HR customers get NYC LL 144 + EEOC 4/5ths-rule probes; healthcare gets clinical-algorithm fairness + FDA SaMD; financial services gets ECOA / Veritas FEAT — automatic per industry.
• ✓ Live dashboard with formulas + native radar + doughnut + per-section completion that auto-refresh as you mark items Done — no regeneration needed to see remediation progress. Tailored to your jurisdiction, industry, organisation size, and risk appetite.

Ready to generate?

$39 · one-time — answer a 6-question intake (including jurisdiction = US), and download your tailored document immediately.

Also available framed for your sector → see industry-specific pages