Adaptive Risk-Tiered Framework for Responsible AI Governance

OVERVIEW

The rapid advancement of artificial intelligence (AI) technologies presents both unprecedented opportunities and significant governance challenges for organizations worldwide. This policy brief proposes an Adaptive Risk-Tiered Framework for AI deployment and application, ensuring safe, ethical, and innovative AI operations across various sectors. The framework emphasizes proportional oversight mechanisms that scale with risk levels, balancing innovation with appropriate safety precautions. By adopting this framework, organizations can lead in responsible AI governance, fostering trust and driving innovation while mitigating potential risks.

The framework is informed by global best practices, including the EU AI Act and the NIST AI Risk Management Framework, and is designed to be adaptable to the unique needs and contexts of any organization. It addresses the critical need for safeguards to ensure responsible and ethical AI use, particularly in high-stakes domains such as healthcare, transportation, public safety, employment, criminal justice, human rights, and finance.

Key objectives include ensuring the safe and ethical deployment of AI, fostering trust through transparency and accountability, promoting innovation while mitigating risks, and aligning with global best practices. The framework also strengthens organizational leadership in AI governance, providing a structured yet flexible approach to managing AI risks effectively.

Implementing this framework will allow organizations to enhance safety, build public trust, foster innovation, and position themselves as leaders in responsible AI governance. The proposed approach is particularly well-suited to the dynamic and evolving nature of AI technologies, making it a promising strategy for AI governance in any organizational context.

Presented By

Sky Bell Headshot

SKY BELL

Manager of Legal Technology Integration, Innovation & AI – New York State, Office of Information Technology Services, Chief General Counsel Office, Division of Legal Technology