Liability Framework
A structured approach defining who is responsible for AI-related harms or failures, including developers, deployers, and operators.
Definition
A set of contractual, organizational, and legal mechanisms that allocates responsibility among stakeholders—data providers, model-builders, integrators, and end-users—for harms (bias, safety incidents, data breaches). It defines liability thresholds, indemnification clauses, and insurance requirements. Governance integrates the framework into vendor contracts, project charters, and incident-response plans to ensure accountability and clear remediation paths.
Real-World Example
A hospital contracts with a third-party AI vendor for diagnostic software. Their liability framework stipulates that the vendor bears responsibility (and must indemnify) for any misdiagnosis attributable to model errors, while the hospital retains responsibility for data-quality issues. This clear allocation streamlines post-incident investigations and insurance claims.
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