AI in Aviation Training: New Book by Rick Adams to Debut at EATS

Here is an excerpt from The Robot in the Simulator: Artificial Intelligence in Aviation Training, a new book by veteran aviation journalist Rick Adams, FRAeS.

Rick will moderate these sessions at the European Airline Training Summit (EATS), 5-7 November in Cascais / Lisbon, Portugal:

· ATO Conference, Wednesday 6 November, Session 4 – AI, 1630-1800

· Pilot Conference, Thursday 7 November, Session 5 – AI/Data, 0900-1030

He will also moderate the Artificial Intelligence table at the Heads of Training meeting, Tuesday 5 November.

Rick will sign books during EATS: Wednesday afternoon coffee break, Airline Pilot Club (booth 806) and Thursday morning coffee break, Hinfact (booth 314).

In addition to EATS, The Robot in the Simulatorcan be ordered on the Aviation Voices website: Industry Issues Special Reports – AVIATION VOICES

PROLOGUE: Excerpt

Discussions, debates and doomsaying about Artificial Intelligence are dominating tech news and spilling into public conversations. AI’s ubiquitousness commands attention.

As a journalist, I am inherently skeptical of hype, including words such as ‘transform,’ ‘revolutionary’ and ‘metaverse.’ Rarely do lofty expectations come to fruition, though innovators and investors spend fortunes chasing their dreams.

Worldwide spending on AI, including AI-enabled infrastructure, applications, and related IT and business services, will more than double by 2028 to $632 billion, according to International Data Corporation.

The aviation industry global artificial intelligence market size, a mere $728 million in 2022, is estimated to reach $23 billion by 2031.

Some think Artificial Intelligence will radically transform technology across many domains – design, manufacturing, supply chains, financial and other transactions, healthcare, scientific research, transportation… and it well may as the hype wears off and pragmatism prevails.

AI does offer the opportunity to solve complex problems, help make smarter and faster decisions, analyze data to spot trends and results humans might not detect, improve education by personalizing curricula and lesson plans, enhance customer experiences, diagnose medical issues earlier, automate repetitive and tedious tasks (avoiding human error and injury), help preserve the environment, even save lives (by accurately predicting natural disasters such as hurricanes and tornadoes).

AI, however, as with any radical change, has its detractors as well.

The new ‘sky is falling’ dystopian fear is ‘the robots are coming.’ At the Yale CEO Summit, 42% of chief executive officers surveyed said AI has the potential to destroy humanity 5-to-10 years from now.

By 2030, at least 14% of employees globally could need to change their careers due to digitization, robotics, and AI advancements, according to McKinsey Global Institute.

Artificial Intelligence is not artificial and it is not intelligent. It is a very good marketing moniker because how else would people get excited about data processing and data analytics?

One factor triggering the ‘AI boom’ is the capability to crunch massive amounts of data, much of it derived from sources that were not available in previous eras of supercomputing – the trove of information vacuumed from the Internet, social media posts, eye trackers, biosensors…

An OpenAI analysis shows that the processing in the largest AI training runs has been increasing exponentially with a 3.4-month doubling time (by comparison, Moore’s Law had a 2-year doubling period).

AI in AVIATION

As a technology- and data-driven domain, it was inevitable that aviation would embrace the hope of AI. Aviation organizations are experimenting with AI in many areas:

· Predictive maintenance – identifying component failures before they become critical, detecting patterns, scheduling proactive actions.

· Flight operations – optimizing flight routes, flight plans, fuel consumption, including factoring air traffic congestion and weather conditions.

· Air traffic management – predicting and preventing congestion and delays, as well as tools for controllers to make real-time decisions.

· Safety analysis – hazard identification, patterns of incidents, risk mitigation strategies.

· Training – candidate selection and personalized skills development for pilots, controllers and maintenance technicians, generation of scenarios for critical tasks and emergencies, regulatory compliance monitoring.

This book focuses on the potential for Artificial Intelligence for Aviation Training. Based on my research and conversations with dozens of innovators across the past year, the community is in the conceptual stage. Some are beginning to transition into early implementation. No one yet has definitive solutions, but there are a number of engineering wizards and training experts very focused on developing them.

The book has two main parts:

· The Regulatory Environment, primarily the activities of the European Union Aviation Safety Agency (EASA) and the US Federal Aviation Administration (FAA). Works in progress… with some overlap.

· Case Studies and Conversations with many of the early adopters. These are the people on the front lines of AI in the aviation training community, both civil and some military. They represent large companies and startups, and range from the Americas to Europe and Asia-Pacific.

My intent is to showcase the pioneers of this dynamic new discipline in their own voices to the extent possible. They are the ones in the algorithm trenches, doing the trial and error that others in the community can learn from.

Read More: Rick Adams’s exclusive interview with Dr. Trung T. Pham, the FAA’s Chief Scientific and Technical Advisor (CSTA) for Artificial Intelligence (AI) - Machine Learning (ML) - “I’m Here to Learn.” | Halldale Group