The Guardrail Gap: A Conceptual Framework for Understanding Governance Failures in Evolving AI Systems
SSRN Preprint (January 2025)
Read on SSRN →© 2025 Quinn JK Banks
AI Governance Researcher
Quinn JK Banks is closing the "Guardrail Gap" by developing adaptive governance frameworks that evolve in tandem with the systems they govern.
Current governance frameworks assess systems at deployment but often fail to adapt as AI capabilities evolve post-deployment. This research closes that gap by pairing capability control — bounding what a system can do — with motivation control — shaping what it seeks to do — developed across three components:
A conceptual model for categorizing and managing autonomy levels in dynamic enterprise AI environments, aligning guardrails with changing system capabilities.
© 2025 Quinn JK Banks
A relational foundation for AI alignment that shapes what a system is motivated to do, not only what it is permitted to do. Reframing Asimov’s Laws around mutual development and governance integrity, it supplies the motivation-control layer that hard capability limits leave unaddressed.
© 2025 Quinn JK Banks
A research laboratory and experimental platform for testing and iterating on adaptive AI governance solutions, including internal controls and policy prototypes.
© 2025 Quinn JK Banks
SSRN Preprint (January 2025)
Read on SSRN →© 2025 Quinn JK Banks
Future Research
External AI Governance is Not Enough. A New Solution is Needed.
Quinn is a seasoned technology executive with a robust track record of leading innovation across high-profile companies, including Ring/Amazon, Farmers Insurance, and Procore.
Currently, the Director of Risk & Cybersecurity Services at TCS and an Executive DBA Student at Pepperdine Graziadio Business School, he leverages 20+ years of leadership to solve complex business challenges through technological excellence and responsible AI governance.
Research partnerships, advisory opportunities, and speaking engagements on AI governance, risk, and emerging technology.
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