Karen Moore & Jean-François Delisle

Karen Moore, Principal Occupational Psychologist, Symbiotics

Jean-François Delisle, AI Strategist, CAE & PhD Candidate, Polytechnique de Montréal

Karen Moore is a Chartered Occupational Psychologist with considerable experience of assessing individuals at all levels from graduate to board directors and in a diverse range of industries from nuclear, through utilities to banking and aviation. She is interested in ensuring that assessment decisions are of value not only to the hiring company in terms of effective performance but also to the individual, and that outputs can assist them with their personal development either in training or on the job.

Karen joined Symbiotics in 2017 as MD and Principal Occupational Psychologist, to further develop their assessment processes for high consequence industries. Symbiotics specialize in the assessment for aviation roles and particularly of pilots from cadets through to instructor/examiner.

Jean-François Delisle, AI Strategist at CAE. PhD Candidate under the supervision of Prof. Andrea Lodi, Canada Excellence Research Chair in Data Science for Real-Time Decision-Making at Polytechnique Montréal

Jean-François Delisle has more than 20 years of experience in software engineering and data science. He has worked for organizations in a variety of industries, including Desjardins-Finance in business intelligence and data warehousing, the Montreal Transport Agency in urban mobility analysis, and the civil engineering firm SNC-Lavalin Inc. on their project management system. He joined CAE in 2010, and his current mandate is to define flight training solution architectures and lifecycle processes and to improve data analytics and artificial intelligence capabilities. Jean-François has a master’s degree in software engineering and enterprise architecture. He is a PhD candidate at the Ecole Polytechnique de Montréal’s Department of Mathematics and Industrial Engineering and is specializing in data science and artificial intelligence for adaptive flight training.

Predicting Pilot Performance Using Psychometry and Flight Performance Data

We talk about pilots having the ‘Right stuff’, and significant investment is made by both AOCs and ATO/FTOs in assessing entrants to the aviation sector to try to find those people who have the ‘right stuff’ to make a successful career as a pilot.

IATA has a clear competency framework for pilots, with a competency being defined as the knowledge, skills and attributes needed for an individual to carry out the role effectively, in other words their behaviour, what and how they do something. Psychological theory around personality assessment states that understanding a person’s preferences, their natural behaviours, predicts greater success in job performance where there is a good match between personality and the required competencies. Assessment at both ab initio and DE level should be aligned to the IATA competencies for greatest predictive validity. That’s the theory, but does it hold up in practice?

A recent data analysis and artificial intelligence development of training assessments against personality and cognitive test results from two main data sets, Aptitude test data and FTO Performance data and using Hierarchical Agglomerative Clustering, conducted by CAE and Symbiotics, showed some interesting results relating to personality preferences and success in assessments during training, suggesting a need to take personal style of cadets into account in training design.