EveryAILaw.comObligations
Vendor-neutral compliance requirements that regulations implement differently.
accountability Accountability
Requirement to report AI-related incidents, safety concerns, or failures to regulatory authorities within specified timeframes.
Requirement to maintain records of AI system development, deployment decisions, and operational logs sufficient for regulatory review.
competence Competence
Requirement that organizations ensure sufficient AI literacy among staff who develop, deploy, or oversee AI systems, tailored to their roles and responsibilities.
compliance Compliance
Requirement to demonstrate that AI systems conform to applicable requirements through formal assessment procedures, potentially including third-party audits.
disclosure Disclosure
Requirement to provide meaningful explanations of how AI systems reach decisions, particularly when those decisions significantly affect individuals.
Requirement to disclose AI involvement to users, label AI-generated content, and provide adequate information about system capabilities and limitations.
fairness Fairness
Requirement to prevent, detect, and mitigate discriminatory outcomes from AI systems, including testing for disparate impact across protected classes.
governance Governance
Requirement to manage training data, ensure data quality, document data provenance, and maintain appropriate data governance practices for AI systems.
Requirement that humans maintain meaningful oversight over AI-assisted decisions, including the ability to understand, override, and intervene in automated outputs.
Requirement to assess and document the risks posed by AI systems, including potential harms, bias, and impacts on affected individuals.