While standing in the checkout line of a grocery store, recently, I ran into a friend and stopped to chat. Engaged in a robust conversation a few paces from my cart, I noticed a woman with a cane moving ahead of me. I waved my fingers in the air to indicate the cart she was passing was mine and went on talking, thinking little about the consequences until the woman broke into a tirade. She accused me of …. well, I’m uncertain. But soon enough a clerk rushed over, took the customer by her arm and lead her to another register where she received immediate attention.
“You said have let her go ahead of you,” my friend said, once the commotion died down. “She’s old, carries a cane and didn’t have many items.”
My friend had a point. At the very least, I had embarrassed the woman. Aware that many walking wounded are among us, I vowed to learn from my mistake.
Lucy Kellaway of the Financial Times pooh-poohs the idea of learning from mistakes. (“The truth about mistakes,” Lucy Kellaway Financial Times, excerpted The Week, 10/9/15, pg. 38) According to her, no evidence exists to show we learn from our gaffs. Nor should the effect of mistakes be softened by the notion they have a salutatory effect. Mistakes, she argues, cause harm no matter how innocently made, and people need to be held accountable.
Kellaway’s views differ from mine, though I agree we need to be accountable for our mistakes. Fear of error leads to a fear of failure, and that results in paralyses. If learning from mistakes isn’t real, how are we to account for thousands of lab rats that, being lost in a maze, finally learn how to find the cheese? In fact, the model for artificial intelligence is based on the way we think we learn — which is through trial and error. (“When Computers Surpass Us,” by Kristoff Koch, Scientific American Mind, Sept/Oct 2015, pg. 27.) IBM’s supercomputers Watson and Deep Blue grew their intelligence precisely by that method. (Ibid pg. 27)
As Kristoff Koch admits in his article about training computers, we humans don’t know much about intelligence — what it is or how it works. (Ibid pg. 27). We do know that advances in education, science and medicine generally come from taking a risk and learning from failures. Get it right the first time and you don’t know why. Kellaway may be correct that there’s no evidence to prove a relationship exists between trial, error and success. But there’ a reason for that, I suspect. Why study the obvious?