Employment AEDT, healthcare AI transparency, companion chatbot safety, and consumer notification obligations mapped to SWT3 witness procedures.
Who this is for: HR and employment counsel, healthcare compliance teams, AI product managers, and GRC architects responsible for Connecticut AI obligations across employment, healthcare, and consumer-facing AI systems.
Signed May 27, 2026. The Connecticut AI Responsibility and Transparency Act (CART Act, SB 5) is the most comprehensive US state AI law. AEDT discrimination liability begins October 1, 2026. Employer notice requirements begin October 1, 2027. This is a separate law from Connecticut SB 2 (AI Accountability Act). See the SB 2 crosswalk for the earlier, narrower law.
The CART Act covers four distinct AI domains in a single law, making it the broadest US state AI regulation enacted to date:
The Act applies to employers doing business in Connecticut, employers with Connecticut employees, and employers accepting job applications from Connecticut residents. The employment provisions have the broadest reach and earliest enforcement dates.
| Date | What Takes Effect | Who It Affects |
|---|---|---|
| May 27, 2026 | Law signed by Governor Lamont | All covered entities |
| Oct 1, 2026 | AEDT discrimination liability begins; employer use of AEDT is not a defense to discrimination complaints | All employers using AI in employment decisions |
| Oct 1, 2026 | WARN Act AI disclosure: employers must state whether layoffs are "related to the employer's use of artificial intelligence" | Employers filing plant closing or mass RIF notices |
| Oct 1, 2027 | Full employer notice requirements: disclose AI use in hiring, provide explanation of AI's role, offer human review option | Employers with CT employees or CT applicants |
| Obligation | Domain | Requirement |
|---|---|---|
| AEDT Discrimination Liability | Employment | AI use is not a defense to discrimination complaints. Employers bear responsibility for AI-driven discriminatory outcomes. |
| Employer AI Disclosure | Employment | Notify candidates and employees when AEDT is used in employment decisions. Provide explanation of AI's role. |
| Human Review Option | Employment | Offer affected individuals the option of human review for AI-driven employment decisions. |
| WARN Act AI Disclosure | Employment | Disclose whether mass layoffs are related to AI or technological change in WARN Act filings. |
| Healthcare AI Transparency | Healthcare | Disclose AI involvement in clinical decisions, diagnosis support, and treatment recommendations. |
| Companion Chatbot Safety | Online Safety | Safety measures for AI companion chatbots interacting with minors. |
| Consumer Notification | Consumer | Notify consumers when consequential decisions are made using automated systems. |
| CART Act Obligation | SWT3 Procedure | What It Witnesses | Evidence Produced |
|---|---|---|---|
| AEDT Discrimination | AI-FAIR.1 | Bias detection and fairness attestation | Factor A: protected attribute, Factor B: metric result, Factor C: threshold |
| AEDT Discrimination | AI-DPIA.1 | Impact assessment completion | Factor A: assessment scope, Factor B: risk rating, Factor C: review authority |
| Employer AI Disclosure | AI-TRANS.1 | Transparency report generation | Factor A: report type, Factor B: coverage, Factor C: publication status |
| Employer AI Disclosure | AI-EXPL.1 | Explanation generation and delivery | Factor A: explanation method, Factor B: confidence, Factor C: factors cited |
| Human Review Option | AI-HITL.1 | Human-in-the-loop decision verification | Factor A: decision type, Factor B: reviewer hash, Factor C: override authority |
| Healthcare Transparency | AI-INF.1 | Inference provenance | Factor A: model identifier, Factor B: provider, Factor C: clearing level |
| Healthcare Transparency | AI-HITL.1 | Human oversight of clinical AI | Factor A: decision type, Factor B: reviewer hash, Factor C: override authority |
| Companion Safety | AI-SAFE.1 | Safety testing and validation | Factor A: test type, Factor B: pass rate, Factor C: coverage |
| Companion Safety | AI-GRD.1 | Guardrail configuration attestation | Factor A: guardrail type, Factor B: rule count, Factor C: enforcement mode |
| Consumer Notification | AI-TRANS.1 | Transparency disclosure | Factor A: report type, Factor B: coverage, Factor C: publication status |
CART Act requires: Employers are liable for discriminatory outcomes from AEDT. Using AI is "not a defense to a complaint alleging a discriminatory practice." This effectively requires employers to test for and mitigate algorithmic bias before and during deployment of AI hiring tools.
How SWT3 addresses it: The witness_fairness() call records which protected attribute was tested (gender, age, race, disability), the fairness metric result, and the threshold applied. Regular AI-FAIR.1 anchors demonstrate continuous bias monitoring, not just pre-deployment testing.
AI-FAIR.1 anchors at regular intervals prove bias monitoring is active. Factor A identifies the protected attribute. Factor B records the metric result (demographic parity, equalized odds, disparate impact ratio). If any Factor B value exceeds the threshold in Factor C, cross-reference with remediation records to show the employer took corrective action. The absence of AI-FAIR.1 anchors during AEDT operation is itself evidence of non-compliance.
CART Act requires: Beginning October 1, 2027, employers must provide an "explanation of the AI's role" in employment decisions to affected candidates and employees. The explanation must be sufficient for the individual to understand how AI influenced the outcome.
How SWT3 addresses it: The witness_explanation() call records the explanation method used, the confidence score, and the factors cited in the explanation. Each explanation delivery produces an anchor proving the employer fulfilled the disclosure obligation for that specific decision.
AI-EXPL.1 anchors prove explanations were generated and delivered. Factor A identifies the method. Factor C lists the factors cited, which should correspond to legitimate job-related criteria. The ratio of AI-INF.1 (inference) to AI-EXPL.1 (explanation) anchors shows what percentage of AI-driven decisions received explanations. For CART Act compliance, this ratio should approach 1:1 for consequential employment decisions.
CART Act requires: Employers must offer affected individuals the option of human review for AI-driven employment decisions. For healthcare AI, human oversight is required for clinical decision support and diagnostic recommendations.
How SWT3 addresses it: The witness_hitl() call records the decision type, a hash of the reviewer's identity, and the override authority level. This creates evidence that human review was available and, when exercised, that a qualified individual participated.
AI-HITL.1 anchors prove human review infrastructure exists. For employment: show that human review was offered (AI-TRANS.1 disclosure) and exercised when requested (AI-HITL.1 anchors with matching decision types). For healthcare: show that every clinical AI output has a corresponding AI-HITL.1 anchor from a qualified clinician.
CART Act requires: Multiple transparency obligations: employer disclosure of AI use in hiring, WARN Act AI disclosure, consumer notification for consequential decisions, and healthcare AI disclosure. All require proactive notification to affected individuals.
How SWT3 addresses it: The witness_transparency() call records the report type, coverage, and publication status. Each disclosure event produces an anchor proving the organization fulfilled its notification obligation at a specific time for a specific audience.
AI-TRANS.1 anchors prove transparency disclosures were made. Factor A identifies the disclosure type (employment notice, WARN filing, consumer notification, healthcare disclosure). Factor C records publication status. For employment: AI-TRANS.1 anchors should appear before or concurrent with AI-INF.1 anchors for the same decision process, proving disclosure preceded the AI-driven outcome.
CART Act requires: The AEDT discrimination liability provisions effectively require employers to conduct impact assessments before deploying AI in employment decisions. Without documented assessment, employers cannot demonstrate they took reasonable steps to prevent discriminatory outcomes.
How SWT3 addresses it: The witness_dpia() call captures the assessment scope, risk rating, and review authority. The anchor timestamp proves the assessment was completed before the AEDT was deployed in production.
AI-DPIA.1 anchor timestamps must predate the first AI-INF.1 anchor for the same AEDT system, proving assessment before deployment. Factor B records the risk rating. Factor C identifies who approved the assessment. Cross-reference with AI-FAIR.1 anchors to show that bias testing was part of the impact assessment process.
| Examiner Question | Where to Look |
|---|---|
| Do you test your hiring AI for bias? | AI-FAIR.1 anchors at regular intervals. Factor A identifies protected attributes tested. Factor B shows metric results. Continuous anchors prove ongoing monitoring, not just pre-deployment testing. |
| Did you conduct an impact assessment before deploying AEDT? | AI-DPIA.1 anchor timestamp must predate the first AI-INF.1 anchor for the same system. Factor C identifies the approving authority. |
| Do you notify candidates about AI use in hiring? | AI-TRANS.1 anchors with Factor A = "employment notice." Anchors should appear before or concurrent with AI-INF.1 for the same decision process. |
| Can candidates request human review? | AI-HITL.1 anchors prove the capability exists. The ratio of human review requests to AI-driven decisions shows how often the option is exercised. |
| Did you disclose AI in your WARN Act filing? | AI-TRANS.1 anchors with Factor A = "WARN filing." The anchor provides independently verifiable proof that the AI disclosure was included. |
| How do you ensure companion chatbot safety? | AI-SAFE.1 anchors for safety testing. AI-GRD.1 anchors for guardrail configuration. Factor B in AI-GRD.1 shows rule count; Factor C shows enforcement mode (blocking vs advisory). |
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