AI Policy
AI Policy encompasses the formal guidelines, regulations, and frameworks that govern the development, deployment, testing, and operational behavior of artificial intelligence systems. These policies operate across multiple levels—from organizational standards within companies to national legislation and international agreements—establishing requirements and expectations for how AI systems are created, evaluated, and used in practice.
Scope and Core Concerns
AI policies typically address system safety, security, and reliability, ensuring that AI systems function as intended and do not cause unintended harm. They also cover transparency and explainability, particularly regarding how AI systems make decisions that affect individuals or organizations. Additional areas include data governance, bias mitigation, and accountability mechanisms that clarify responsibility when AI systems cause adverse outcomes. Policies increasingly address environmental impacts, intellectual property questions raised by AI training, and labor market disruption.
Multi-Level Governance
AI policy development occurs at interconnected scales. Individual organizations establish internal guidelines for AI development and procurement. National governments have begun implementing legislation such as the EU’s AI Act, which categorizes systems by risk level and establishes corresponding compliance requirements. International bodies and standards organizations work to harmonize approaches across jurisdictions, though significant divergence remains in regulatory philosophies and enforcement mechanisms.