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SB 3502

AI PRODUCT LIABILITY ACT

104th Regular Session Introduced by Christopher Belt and 14 co-sponsors

Creates liability standards for harms from AI products, clarifying who is responsible (makers, users, or shared) and requirements for safety, transparency, and data governance.

Rule 3-9(a) / Re-referred to Assignments
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WeVote Research Nonpartisan
Bill Summary · SB 3502

Overview

SB 3502, introduced in the Illinois 104th General Assembly, is titled the AI PRODUCT LIABILITY ACT. The bill seeks to establish liability standards and related procedures for damages arising from the use or deployment of artificial intelligence (AI) products and systems. The sponsor list includes multiple senators as co-sponsors, with initial committee and reading actions occurring in early 2026. The bill has undergone standard committee and floor timeline steps (assignment, committee deadlines, readings, and re-referrals).

Primary purpose and intent

  • Create a framework to address product liability in the context of AI technologies.
  • Clarify when and how developers, manufacturers, distributors, and users of AI products can be held responsible for harms or losses caused by those products.
  • Align liability considerations with the unique characteristics of AI, such as autonomous decision-making, data usage, learning capabilities, and potential for unintended or emergent behavior.

Key provisions and changes (as inferred from bill title and typical AI product liability frameworks)

  • Establish liability standards specific to AI products, potentially distinguishing between:
    • Manufacturer/producer liability for defects in AI systems or training data.
    • User or operator responsibility in certain contexts.
    • Shared or comparative liability in joint scenarios.
  • Define what constitutes an “AI product” for purposes of the act (software, embedded AI in hardware, cloud-based services, and possibly updates or iterations).
  • Address causation and proof requirements in AI-related injury or damage claims, potentially including standards for proximate cause and foreseeability.
  • Specify defenses or limitations relevant to AI, such as:
    • Assumption of risk
    • Comparative fault
    • State-of-the-art or best-available technology defenses
  • Establish duties for AI developers and vendors, such as:
    • Reasonable testing, transparency about capabilities and limitations
    • Data governance and privacy controls
    • Safety and risk assessment requirements
  • Provide procedural rules for claims, including timelines, triggers for discovery, and venue considerations.
  • Create potential safe harbors or regulatory compliance pathways that could influence liability outcomes.
  • May include standards for disclosure of AI behavior, decision-making processes, or risk notices to end users.

(Note: The exact text would specify precise standards, definitions, and procedural rules. The above outlines typical components of an AI product liability framework.)

Who and what would be affected

  • AI developers, designers, and manufacturers of AI-enabled products and services.
  • Distributors, licensors, and vendors of AI technology integrated into products.
  • Businesses and individuals deploying AI systems in commercial, industrial, or consumer contexts.
  • End users and consumers harmed or damaged by AI products, who would have a defined path to seek compensation.
  • Potentially, entities involved in data collection, training, or data governance related to AI systems.

Procedural and timeline aspects

  • Introduction and assignment to committees (notably Rules and Executive/Assignments pathways), with multiple rounds of sponsorships and co-sponsors added in spring 2026.
  • Committee deadlines established (e.g., March to May 2026) for third-reading deadlines and potential final floor action.
  • Re-referral history indicates ongoing consideration and potential amendments before final passage.
  • If enacted, the bill would likely require transition provisions (effective dates) and any regulatory or administrative rulemaking to implement the liability framework.

Potential impacts and considerations

  • Affects the risk landscape for AI product developers by clarifying liability costs and dispute resolution pathways.
  • Could incentivize stronger safety, testing, and transparency practices in AI development and deployment.
  • May influence insurance markets and coverage for AI-related products and services.
  • Potentially interacts with privacy, consumer protection, and data governance laws, given AI reliance on data.
  • The exact scope (broad consumer AI versus enterprise AI, and cross-border applicability) would determine practical impact on innovation and deployment.

Notes

  • The summary reflects the bill’s stated title, sponsor list, and legislative history up to May 2026. For precise definitions, duty ontologies, damages caps (if any), procedural timelines, and enforcement mechanisms, the bill text should be consulted.

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

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