Reducing Cognitive Load: AI-Augmented Decision Support for Safety-Critical Governance

This document proposes an AI-augmented decision support architecture designed to reduce cognitive load on Authorizing Officials in federal safety-critical governance by synthesizing compliance evidence into structured briefings rather than replacing human decision authority.

This paper presents a detailed examination of the challenges and solutions addressed by Cognitive Load, providing actionable frameworks for organizations navigating the intersection of AI adoption and regulatory compliance.

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• Establishes a structured approach to cognitive load that aligns technical implementation with federal compliance requirements.
• Demonstrates how Cognitive Load concepts translate directly into measurable engineering controls and audit artifacts.
• Provides implementation patterns validated against real-world deployment constraints in regulated environments.
• Identifies critical gaps in current approaches and proposes concrete architectural solutions backed by operational evidence.