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Bill

S 46

An Act relative to the use of artificial intelligence and other software tools in healthcare decision-making

194th Legislature (2025-2026) Introduced by Jamie Eldridge and 1 co-sponsor

Massachusetts bill requiring transparency, accountability standards, and human oversight for AI tools used in healthcare decisions by providers and insurers.

Accompanied a new draft, see S2632
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Bill Summary · S 46

Legislative bill overview

S 46 establishes regulatory frameworks and requirements for the use of artificial intelligence and software tools in Massachusetts healthcare decision-making processes. The bill aims to ensure transparency, accountability, and patient safety when healthcare providers and insurers deploy AI systems for clinical decisions, treatment recommendations, and coverage determinations.

Why is this important

As AI adoption accelerates in healthcare, decisions made by algorithmic systems can directly affect patient diagnoses, treatment options, and insurance coverage—often without clear visibility into how those decisions were reached. This bill addresses growing concerns about algorithmic bias, lack of human oversight, and patients' right to understand and challenge AI-driven healthcare decisions that impact their care and access to treatment.

Potential points of contention

  • Clinical autonomy vs. regulation: Healthcare providers may argue that prescriptive AI regulations could slow innovation and clinical decision-making, while patient advocates contend that strong guardrails are necessary to prevent harm
  • Transparency and proprietary concerns: Requirements for algorithm explainability and disclosure may conflict with software vendors' intellectual property protections and competitive interests
  • Implementation costs and burden: Smaller healthcare organizations and practices could face significant compliance expenses, potentially disadvantaging rural or under-resourced providers
  • Scope and enforceability: Defining which software tools qualify as "AI" and establishing clear accountability mechanisms when systems fail or produce biased outcomes remains technically and legally complex

Compiled from official sources — confirm details with the bill’s official record.

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