UAs, GAs, and Automation (Part 2 of 3): “Placing the Bet”

Last time we introduced some facts about UAs and GAs and asked you to consider how you and your organization face this chronic safety issue, and how the use of automation can contribute to safer approaches and successful go-arounds from an Unstable Approach.

For review, here are the numbers from the Flight Safety Foundation’s February 2013 issue of Aero Safety World:

  • In the past 16 years the most common type of aviation accident is the runway excursion, accounting for 33% of all accidents (this statistic includes excursions on both takeoff and approach).
  • The highest risk factor for a runway excursion is an Unstable Approach (UA).
  • UAs account for 3.5-4.0% of approaches across the global fleet.
  • Only 3% of all UAs are taken to a go-around (GA); leaving 97% of all UAs that are taken to a landing.

There were two more extensive reports in the March and April issues of Aero Safety World dealing with the decision to execute (or not) a GA from a UA. I was recently making some notes in a book I was reading and it struck me that part of the decision to continue a UA to landing may in fact be explained by the neuroscience of gambling (no kidding; stick with me). In the book “Good Thinking” the author Denise D. Cummins evaluates the findings of contemporary research when it comes to risk. She reports that, “When people decide to make risky decisions, the reward areas of the brain become highly active just prior to making the decision. In other words, this neural signature shows that they are anticipating large payoffs and are not thinking about the probability of payoffs (Knuston & Bossaerts). This is one reason gambling can be so addictive; the act of placing the bet can feel as rewarding as winning.”

It’s possible that wrapped-up in the decision of whether to execute a GA or continue to landing from a clear UA is the possibility of the “rush” that a pilot or a crew can get from choosing the riskier landing than the safer go-around. This effectively engages the brain’s emotion-based system, and for practical purposes “locks out” the analytic system. It makes some sense out of what otherwise can be clearly categorized as an act of “willful non-compliance.”

Policies designed to avoid landing from an unstable approach are meant to be binary – it’s one or zero: either you’re safe to continue (stable) or not (go-around). Maybe – just maybe – the whole UA/GA dynamic needs to account for the tendency of humans to gravitate towards risk. Looking at the UA/GA dynamic through this lens brings into question how we train, evaluate, and prepare crews to face this pressure-packed and time-compressed decision that has such a devastating impact on the safety of the global aircraft fleet.

Next week, in the last post of this three-part series, we will address the role that flight deck automation can play in creating a successful GA from any unstable approach.

Until our next report, fly safe and fly first.

Memphis, Tennessee 

October 2013


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