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EASA Updates Roadmap for Artificial Intelligence in Aviation

EASA has updated its proposed roadmap for the increasing use of artificial intelligence (AI) in aviation. Three years after it published the first version of the document, Europe's aviation safety agency has now published its expanded AI Roadmap 2.0 to include “experience gained from concrete AI use cases involving stakeholders from the aviation industry, academia, and research centers,” the agency said in a statement. 

Through its AI Roadmap, EASA aims to provide a comprehensive plan for the growing use of AI and machine learning (ML) in the aviation industry, with a focus on safety, security, and ethical considerations. 

The AI Roadmap 1.0, a 30-page document published in February 2020, was intended to serve as a basis for ongoing discussions between EASA and industry stakeholders. EASA published its revised AI Roadmap 2.0 on May 10. EASA says it will treat this roadmap as a “living document” that it will amend annually based on those discussions and continuing advancements in AI technologies and their applications in aviation. 

“AI allows us to create intelligent systems that can provide advanced assistance solutions to human end users, optimize aircraft performance, improve air traffic management and in turn enhance safety in ways that were previously unimaginable,” EASA executive director Patrick Ky wrote in a cover letter for the AI Roadmap 2.0. “However, the deployment of AI in aviation also poses new challenges and questions that need to be addressed.”

In its updated roadmap, EASA has added a new chapter to identify and address some common AI challenges in aviation. The challenges EASA describes in this section pertain to things like quality assurance frameworks, knowledge and data management, and the predictability of AI behavior.

The updated document also includes a new rulemaking concept for AI, in which EASA calls for a “mixed rulemaking approach” involving cross-domain rules plus domain-specific rules. EASA anticipates these rules will be developed in two steps. First, it would develop transversal “Part-AI” rules for three major provisions identified in the EASA concept paper on machine learning applications. These include requirements for authorities (Part-AI.AR), requirements for organizations (Part-AI.OR), and requirements pertaining to AI trustworthiness (Part-AI.TR). Step two will be to analyze these rules on a per-domain basis to determine those rules “that need to be complemented to provide an adequate regulatory basis for deploying the new Part-AI,” the document states.

Another notable addition to EASA's AI Roadmap is a new section on aerodromes, including airports and vertiports that transport passengers or cargo. According to EASA, AI can be used for both airside and terminal-based operations. For example, airside AI could be used for UAS detection systems, avian radars, and the detection of foreign object debris on a runway. In the terminal, AI could be used in security and screening procedures.

EASA will continue to update the AI Roadmap as it works with industry stakeholders to understand, develop, and improve AI applications in the aviation industry. The agency is also funding a variety of AI-related research and has partnered with private companies like Daedalean and Collins Aerospace to collaborate on research relevant to the AI Roadmap.