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Evergreen Ledger

SSB 6284

In Committee

Senate

AI consumer protections

Providing consumer protections for artificial intelligence systems.

This status may be delayed. See Action History below for the latest updates.

How does a bill become law?
  1. Introduced: The bill is filed and assigned a number.
  2. Committee: A subject-matter committee holds hearings, takes public testimony, and decides whether to advance the bill.
  3. Floor Vote: The full chamber (House or Senate) debates and votes on the bill.
  4. Opposite Chamber: The bill repeats the committee and floor vote process in the other chamber.
  5. Governor: The Governor reviews the bill and decides whether to sign or veto it.
  6. Signed: The bill has been signed into law.
Introduced: February 2, 2026
Last Action: February 4, 2026
Status: S Ways & Means
Companion Bill:
View Bill Text (HTML) (opens in new tab)View Bill Text (PDF) (opens in new tab)

AI Analysis

This analysis was generated by AI and may contain errors. It is not legal advice. Always refer to the official bill text for authoritative information.
People & CommunitiesBalancedCorporate & Wealthy Interests

This bill establishes Washington’s first comprehensive framework to protect consumers from harmful uses of artificial intelligence, especially when AI makes important decisions affecting housing, jobs, credit, and government services. It requires businesses to assess and manage risks of bias, disclose AI use to consumers, and maintain transparency, while exempting small businesses under certain conditions. It also strengthens government oversight and expands the state’s AI task force to study emerging issues.

  • Requires deployers of high-risk AI systems to use industry-standard practices to protect consumers from algorithmic discrimination, with a rebuttable presumption of compliance if they follow the law.
  • Mandates annual reviews of high-risk AI systems for discrimination and requires deployers to report discoveries of discrimination to the Attorney General within 90 days.
  • Requires deployers to implement and maintain a risk management policy and program based on national standards (e.g., NIST AI RMF or ISO 42001), tailored to their size and risk profile.
  • Requires impact assessments for high-risk AI systems before deployment and after major modifications, including details on data use, risks, transparency measures, and safeguards — with a 3-year retention requirement.
  • Requires businesses to notify consumers before using high-risk AI to make consequential decisions (e.g., jobs, housing, loans) and provide clear, plain-language explanations of the AI system.
  • Requires government agencies to clearly disclose when consumers are interacting with AI, using plain language and avoiding deceptive design (‘dark patterns’).
  • Extends and expands the AI Task Force through 2028 to study AI impacts and advise the legislature, and creates a new AI Workplace Advisory Group to develop principles for fair AI use at work.

Who is affected

  • Businesses and organizations that deploy high-risk AI systems — Businesses that deploy high-risk AI systems in Washington must comply with new transparency, risk management, and impact assessment requirements, though small businesses (under 50 employees not using their own data to train AI) are exempt from some obligations.
  • Washington consumers — Consumers in Washington gain new rights to be informed when AI is used to make important decisions about them (e.g., jobs, housing, loans), and protections against algorithmic discrimination.
  • State and local government agencies — State government agencies must clearly disclose when AI is used in consumer-facing interactions, and must follow transparency requirements for AI systems they deploy.
  • Workers and labor advocates — Workers and labor organizations gain a voice in shaping AI use in the workplace through the new AI Workplace Advisory Group, which develops principles to protect fairness and privacy at work.
  • AI developers and technology companies — AI developers and technology companies must ensure their high-risk AI systems comply with state standards, and may be required to share impact assessments with deployers under certain conditions.
Effective: July 1, 2026Fiscal impact: The bill establishes new administrative responsibilities for the Attorney General’s office and the AI Task Force, including staffing, consultants, and reporting. There may be modest costs for state agencies to implement AI disclosure requirements and for businesses to comply with new risk management and impact assessment obligations. No specific dollar amount is provided.
Model: Intel/Qwen3-Coder-Next-int4-AutoRoundGenerated: Mar 20, 2026 at 2:59 AM

Pro/Con Analysis

Stronger case for benefits

Potential Benefits (5)

  • Mandates plain-language disclosure of AI use in consequential decisions (e.g., housing, jobs, credit) and requires deployers to provide consumers with impact assessments developed by developers — this empowers individuals to challenge biased outcomes and exercise informed consent, directly protecting vulnerable populations from opaque, discriminatory systems.

    Rights & LibertiesPeopleRef: Sec. 6(1)(c); Sec. 7(2)(c)

  • Requires annual reviews for algorithmic discrimination and establishes a rebuttable presumption of compliance only if the law is followed — this creates a strong incentive for deployers to audit for bias, reducing discriminatory outcomes in critical domains like housing and employment, especially for historically excluded groups.

    Rights & LibertiesPeopleRef: Sec. 3(2)(b); Sec. 3(1)(a)

  • Establishes an AI Workplace Advisory Group with mandatory labor representation to develop principles for fair AI use at work — this gives workers and unions a formal voice in shaping AI deployment in employment decisions, countering employer power imbalances.

    Business & EmploymentPeopleRef: Sec. 14; Sec. 11(2)(d)

  • Requires government agencies to clearly disclose AI use in consumer-facing interactions and prohibits dark patterns — this strengthens transparency in public services (e.g., benefits applications, court systems), reducing the risk of automated errors or deceptive design harming vulnerable residents.

    Public SafetyPeopleRef: Sec. 10(1); Sec. 10(3)

  • Requires impact assessments to include analysis of algorithmic discrimination risks and data inputs/outputs — this enables scrutiny of AI used in housing applications, eviction prediction, and rent pricing, protecting low-income and minority tenants from automated bias in access to shelter.

    HousingPeopleRef: Sec. 5(2)(b); Sec. 5(2)(c)(ii)
Potential Concerns (5)

  • Small businesses (under 50 employees not using their own data to train AI) are exempt from impact assessments and risk management program requirements, but only if they use externally trained AI models — this creates a complex compliance tier that disproportionately benefits larger firms with legal teams to navigate exemptions, while small firms still face disclosure and annual review obligations without meaningful relief.

    Business & EmploymentLean industryRef: Sec. 5(6)

  • Mandated plain-language disclosures and prohibitions on dark patterns increase operational costs for all deployers, especially small businesses and startups, which lack economies of scale in legal/compliance infrastructure — the burden falls disproportionately on lower-revenue firms, while large tech firms absorb costs more easily and may even gain competitive advantage by framing themselves as ‘trustworthy’.

    Business & EmploymentIndustryRef: Sec. 7(2)(c); Sec. 10(1)(c)

  • The bill creates a new enforcement mechanism under the Consumer Protection Act (CPA), but limits private rights of action — only the Attorney General can sue, and businesses get 60 days to ‘cure’ violations after notice, reducing accountability and shifting enforcement discretion to a politically appointed official, favoring well-resourced entities that can afford legal counsel to negotiate with the AG.

    Business & EmploymentIndustryRef: Sec. 9(1)(b); Sec. 9(1)(a)

  • The bill allows reliance on NIST/ISO frameworks or AG-designated alternatives, but does not standardize implementation — large firms with resources to interpret and comply with evolving national standards gain advantage, while smaller firms face ambiguous, costly compliance; also, allowing third-party assessments creates a new consulting market dominated by elite firms.

    Business & EmploymentIndustryRef: Sec. 4(2)(b)(A); Sec. 5(5)

  • The bill creates new administrative burdens for state agencies (e.g., AG, OSPI, DSHS) to implement disclosure and oversight, but provides no dedicated funding — this diverts existing resources from other public services, disproportionately affecting communities that rely on underfunded public programs where AI may be most harmful.

    Local GovernmentIndustryRef: Sec. 11 (new chapter in Title 19 RCW); Sec. 12 (new chapter in Title 42 RCW)

Who Is Most Affected

Low-income and minority consumersPositive Impact

Low-income and minority consumers benefit significantly from transparency and bias mitigation in housing, credit, and employment decisions — they are disproportionately targeted by harmful AI and lack resources to challenge opaque systems independently.

Large technology firms and AI developersMixed Impact

Large tech firms and AI SaaS providers face compliance costs but can absorb them and potentially gain market share by branding themselves as ‘compliant’ — they also benefit from preemption-like exemptions (Sec. 8) that shield federal contractors and health providers.

Small businesses and sole proprietorsMixed Impact

Small businesses (under 50 employees) gain partial exemption but still face disclosure and review obligations — they lack legal resources to navigate complex compliance, increasing operational risk and potentially deterring AI adoption even where beneficial.

State and local government agenciesNegative Impact

State and local agencies must implement AI disclosure rules and may need to overhaul legacy systems — this strains already limited budgets and could delay service delivery, especially in rural or underfunded jurisdictions.

Workers and labor unionsPositive Impact

Labor unions and worker advocacy groups gain formal influence through the AI Workplace Advisory Group, enabling them to shape AI use in hiring, promotion, and surveillance — this shifts power toward workers in the digital economy.