AI Safety Aviation

Roadmap Overview

Focuses on the integration of artificial intelligence, particularly machine learning, into safety-critical aviation systems while maintaining the highest standards of safety and trustworthiness. It encompasses a phased approach, starting with human assistance/augmentation (Level 1 AI), progressing to human-AI teaming (Level 2 AI), and ultimately advancing to more automated solutions (Level 3 AI). Key aspects include developing AI assurance frameworks, addressing human factors in AI integration, implementing safety risk mitigation strategies, and ensuring compliance with evolving regulatory requirements. This technology aims to enhance aviation safety, efficiency, and performance across various domains including aircraft design and operation, air traffic management, and unmanned aircraft systems.

Scope Down Idea (Draft)

• Hybrid cockpit with AI supporting pilot by improving situational awareness and translate pilot intent to automated systems.

DSM Allocation

Roadmap Model

Decomposition of 3ADC Roadmap

Figures of Merit

Important FOMs for 3AISC

Figure of Merit	Description	Trends	Units
Incident Rate	Rate of incidents and accidents normalized by flight time aircraft	decreasing	$\frac{\text{incidents}}{\text{passenger mile}}$
System Maintainability	How much time is spend maintaining aircraft systems, measured by comparing maintenance time per flight time	decreasing	$\frac{\text{maintenance hours}}{\text{passenger mile}}$
Response Time	Time required to identify and mitigate safety issues	flat	$\text{minutes}$
System Uptime	Amount of time aircraft is available to be dispatched on a mission as a percentage of wall time	increasing	$\text{\%}$
Cognitive Load on Crew	As measured by industry standard NASA TLX score	flat	$\text{unitless}$

Detail of Accidents per passenger hour