How do we go about decision-making? Well honestly, most of the time it’s pretty easy, even self-evident. You have a gut feeling to go to a particular cloud, leave a thermal as it’s dying, or to perhaps recenter a half turn in another direction. We make these kinds of decisions all the time. Every time you move the stick, some part of your brain is making a decision.
But that’s not how we are taught to go about decision-making! Think about MC theory; look at the next cloud, calculate its expected lift strength minus any headwind component and centering losses. Entering a thermal, count three seconds and then bank hard. Listen to the variometer… when it spikes plan to recenter in that direction on the next turn. Glance at the yawstring as you turn. Keep your airspeed on the dial on your check-ride. Fly by the numbers!
Some pilots are known as being “artistic” and hardly do any of this calculation. Others are the “engineers” who seem to be a human flying computer.
What’s going on?
Folks who study decision-making typically model it as a dual process. Unfortunately, there is a lot of disagreement as to what drives this binary system. If you look into the research, you will see thinking modeled as “fast and frugal”, or “slow and deliberative”. “Affective” (emotional) or “cognitive”. “Model-based” and “model-free”.
The “heart” or the “mind”
Intuitive or calculating.
The artist or the engineer.
The reality is that it is not quite that clearly demarcated. When you study the brain, no one part of the brain is doing one line of reasoning as opposed to another. The “left brain” vs. “right brain” thinking is a total myth. Everything is interconnected and involved with everything else. A cold, calculating engineer is still relying on affective, intuitive judgment as he is solving his problems. An artist is still using some top-down cognitive reasoning as he decides which paint to put on the canvas.
It’s more of a spectrum rather than a binary system.
Nonetheless, it’s still a useful analogy, or at least a lens to look at decision-making problems.
The intuitive system is exceptionally useful. It operates using past experience and interprets current situations in line with that experience. The current situation need not be exactly the same as one we encountered before; we are great pattern-matching machines!
So when you scan a bunch of clouds and then you find the right one and you feel “good” about it, really it’s your neural network black box outputting that this cloud is the right solution. And this works when you’ve flown under hundreds of clouds and trained your pattern recognition system well!
This process works really well for most problems that we encounter in life and soaring.
However, this approach to decision-making breaks down when we don’t have experience that generalizes to a given situation. The blackbox between your ears still ticks away, but it won’t help you. Or worse yet, it will lull you into a sense of complacency. When you have a system that works 99 percent of the time, it doesn’t jump out at you the 1 percent of the time when your own software starts working against you!
This is not a problem in situations where receive real-time feedback. Thermalling is one of those cases; we are constantly adjusting to the air and variometer and over time we can get quite good at modeling what the air will do.
However, it is a problem when it comes to risk-management and “gear-shifting” for changing weather. Most of us don’t have a sufficiently large bank of experience to do this intuitively. And the problem is that feedback we receive from the current conditions is usually too little, too late!
You fly under one cloud and it doesn’t work. Then under another and it doesn’t work. Now you’re at 2000ft AGL, you realize you’re in the doghouse and now shift into risk minimization.
The trouble is that if the conditions are unreliable, you’ve already missed the boat. If you’re lucky, you will dig out. But do this one too many times in a competition and you will near certainly land out.
Restated, unless you’re actively managing your strategic risk, if you simply rely on intuitive judgment you will very likely be taking too much risk over the long run.
In the case of sporting risk management, John Bird and I solved this by developing a normative model of decision-making. Assess the reliability and quantity of options ahead of you to decide how to go about these decisions.
However, there are many other problems and decisions we encounter that we use a structured, calculated approach. Check-lists are a simple example! Instead of relying on intuition or “flow”, we could simply follow the process and make sure that things are where they need to be. Decision heuristics such as “don’t deviate more than 30 degrees” or “fly MC speed” are other examples. These are effective strategies.
This is not to say that cold-calculation is the best way to go about your flying, far from it! It is impossible to fly as a human computer, we simply don’t have enough bandwidth to do that.
Instead, it is best to recognize what kind of problems are best left to the intuitive system and others that are best handled by calculation. And engage the right decision-making system in the right context.
I thermal with a brush and make my risk-management decisions with a calculator.