The Air Transport Association of America (ATA) yesterday filed comments expressing serious and broad concerns about a Federal Aviation Administration’s (FAA) proposed regulation that would rewrite pilot, flight attendant, flight engineer, and dispatcher training requirements. In particular, ATA believes that the proposal could adversely impact current “best practice” training programs – a result neither the FAA nor the industry want to see.
Instead of proceeding directly to a final rule, ATA recommends that the FAA suspend this rulemaking and immediately convene an Aviation Rulemaking Committee (ARC) to address the many conflicts and inconsistencies identified in the ATA comments.
While the preamble of the notice of proposed rulemaking (NPRM) states laudable goals that ATA fully supports, a careful examination of the details of the proposed regulation reveals numerous unworkable aspects, internal conflicts, conflicts with current advisory material, and inaccurate assessments of current industry standard practices.
ATA member airlines take training extremely seriously and believe that any rule changes in this area must yield an improvement over existing regulatory requirements. After spending thousands of hours analyzing the proposed rule, training experts from ATA member airlines unanimously concluded that the proposed rule contains substantial and material inconsistencies that make it logistically impossible to implement. Furthermore, the proposal seems to abandon the advancements in pilot training programs that have been instrumental in improving airline safety.
“While we appreciate the FAA’s desire to quickly adopt new training rules, we believe that the rule as proposed could set the safety clock back by more than a decade,” said ATA president and CEO James C. May.
For example, the Advanced Qualification Program (AQP) enables operators to customize their crew training programs based on real-world operating environments. ATA believes that the FAA proposal fails to recognize the value in this and other innovative, data-driven approaches.