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Liability

As explained in LLMs in Production

Legal responsibility for harm, loss, or an obligation resulting from an action or omission.

When an AI product causes harm or skirts consumer-protection rules, responsibility can extend beyond the model to the people and businesses deploying it. Products create expectations, expose reputations, and can trigger lawsuits or new regulatory duties. section 12.2.1

Utah SB-149

Utah’s Artificial Intelligence Amendments bill introduced liability for actors using LLMs to evade consumer-protection laws. Its definition of artificial intelligence covers systems making predictions, recommendations, or decisions that influence real or virtual environments. section 12.2.1

Practical implications include:

  • Treat legal exposure as a production concern rather than waiting for regulations to become fully settled. section 12.2.1
  • Recognize that broad statutory definitions may cover systems ranging from simple conditional logic to LLM agents. section 12.2.1
  • Account for precedent risk: one lawsuit can encourage additional lawsuits and reshape expectations for similar products. section 12.2.1

How LLMs in Production covers it

How deep it goes
Defines regulatory scope and illustrates statutory treatment, but stops short of resolving specific legal outcomes.
Examples
Uses Utah SB-149, an LLM evading consumer-protection laws, and the contrast between if statements and LLM agents.
What you can do after
Evaluate AI products for potential legal exposure, regulatory scope, and precedent risk before deployment.
How it connects
Connects liability with artificial intelligence, consumer protection laws, deceptive acts, lawsuits, and regulation.

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This explainer was generated by Manning's knowledge graph from the text of LLMs in Production. The section links point to the parts of the book it draws on.