Artificial Intelligence
Multi-pronged approach to AI regulation: Educate the public about AI's benefits, advocate for risk-based federal policies, bolster American leadership, and push back against a patchwork of state regulations.
Efficiency: Policymakers must evaluate the applicability and enforcement of existing laws and regulations and focus on filling gaps in existing regulations to accommodate new challenges created by AI usage.
Neutrality: Laws regarding AI should be created only as necessary to fill gaps in existing law, protect citizens’ rights and foster public trust. Rather than trying to develop a one-size-fits-all regulatory framework, this approach to AI regulation allows for the development of flexible, industry-specific guidance and best practices.
Proportionality: When policymakers determine that existing laws have gaps, they should attempt to adopt a risk-based approach to AI regulation. This model ensures a balanced and proportionate approach to creating an overall regulatory framework for AI.
Collegiality: Federal interagency collaboration is vital to developing cohesive regulation of AI across the government.
Flexibility: Laws and regulations should encourage private sector approaches to risk assessment and innovation.