If, instead of a photo of running accompanying this column, a picture of President Trump appeared.
Your reaction to the photo — good, bad, indifferent — would be instantaneous and an example of what’s called “Fast Thinking” a problem.
On the other hand, if I have run 63 races (each of 5K ) with an average time of 24 minutes, then how many total minutes was I running? (Hint: 63 x 24). Now this problem, in contrast to the first example is called “Slow Thinking” a problem.
I’m confident that all of you can do that multiplication. The point is, how? When you see 63 x 24, you reach for a pencil (if you’re old enough to know what a pencil is), a calculator (middle age) or a smartphone (if you’re older than 3). The point of the example is that few of us would look at the problem and immediately think: 1,512 minutes. Slow thinking will produce answers only with some deliberation.
What does this have to do with running? Well, running is the perfect opportunity for the brain to have some downtime and to allow your heart, lungs, muscles, etc. to do the heavy lifting. Now, in fairness, your brain is never in a downtime mode. First, it’s monitoring all those essential functions to make sure these components are not running into trouble: heat exhaustion, heart attack as potent examples. Second, the baseline monitoring can be done and yet allow your brain to deal with the backlog of “slow” problems that have accumulated.
The best example from my experience is from a time when people were smart and computers were dumb. They were large boxes, incredibly expensive and stored in a controlled atmosphere protecting their delicate electronics. Trust me that the calculation power of a smartphone today would require a warehouse then.
I did a certain amount of programming associated with risk analysis. Machines were so primitive that the programmer had to monitor processing and memory usage to ensure programs didn’t exceed defined limits. Generating a report was not as simple as pushing a “print” button. The programmer had to count the number of print lines, so the program would issue a page break and start a new page. Those were the kinds of details you had to consider.
So I had this program, and when I started it, absolutely nothing happened. I just sat in front of the monitor and watched a blank screen. I knew there was a decision node in the code that, based on a computed value, directed the processing back up through the loop or onward to the rest of the program. In “Monte Carlo simulation,” the computer produces a range of outcomes that are driven by probability distributions. To illustrate from our current situation, you could simulate New York City COVID-19 disease outcomes with probabilities on hospital capacity, social distancing, compliance with regulations, etc. So after a defined number of iterations, the simulation moves to the next phase of the program to summarize and report. In my case, the processing never moved on — like a kid staying in 7th grade forever.
I could not imagine what was wrong. I tested and retested various segments of the code. After hours of frustration, I did the normal thing. I gave up. Even so, the brain continued to work with the problem, though I was not conscious of that effort.
Here’s the running part. I didn’t go for a run to solve my problem; I just went for a run. Then, after 20 minutes, I was running up Heart Break Hill (to those of you who know Central Park it’s on the northwest corner). My body was completely engaged in surviving this endless hill, when out of nowhere, my brain told me,”Hey, stupid, here is why your computer program is not working” and the answer came to me. Sure enough, I’d solved the problem. It was as clear and obvious as the road in front of me.
Running/walking provides great physical value. But, you may be surprised how well your brain functions when you allow it to ponder “Slow Thinking” problems.
For a great read to understand how brains work, check out Daniel Kahneman’s “Thinking Fast and Slow” (Farrar, Straus and Giroux, 2011).