You won’t believe it, but this is a radical concept.
Radical because there has been a lot of confusion over just how humans learn.
For most of the 20th century, we thought humans, and therefore machines, learned by being told what to do.
Ergo, by algorithms
IF this is so, THEN do this.
- IF a ball is thrown at your head, THEN duck.
- IF there’s lightning, don’t stand under a tree..
- IF a nuclear bomb drops, hide under your desk.
We thought that thinking was a process of having a bunch of these rules in your head and applying them.
This meant that learning, was the process of acquiring more and more rules.
Learning = Acquiring rules
What is learning?
Many people would agree that learning is about the ability to think, by which they mean to be rational. Scientists have developed many studies to test human rationality. There’s a bunch of them. And in every one, we fail.
One is called the Wason Selection Task, and we’re going to do it right now.
“If one of these cards has an even number on one side then its other side is green.”
Which cards would you turn over, without turning over any cards unnecessarily?
For example, 3 card only; 8 card only; 3 and blue; 8 and green; all the cards
Most common answers:
- 3 card: does not need to be turned over, because it is not even, so it cannot trigger the stated proposition
- 8 card: even, so it must be turned over, because if the other side is not green, then the proposition is not true
- green card: many people choose this card, but it does not need to be turned over, because if the other side is odd, then the proposition is not tested, and if the other side is even, that is consistent with the proposition, but it does not prove or disprove the truth of the proposition
- blue card: does need to be turned over, because if the other side is even, then the proposition is not true
But let’s see what happens if we turn things around a little bit. We’ll make the RADICAL assumption that people ARE rational, how about that? And if they get the problem wrong this much, there must be something amiss in the researchers’ assumptions.
So what are these assumptions? Basically, it’s this:
Rationality = Logic
This lines up well with the algorithmic definition of learning, because presumably the rules you need to learn are logical.
I happen to know a guy who epitomizes this concept.
This is Mr. Spock from the TV series, Star Trek. He’s a Vulcan—notice the ears—and on Vulcan, they believe in logic like a religion.
Now, Spock’s foil on the show is Dr. McCoy,
Dr. McCoy is a folksy country doctor stereotype—nicknamed Bones—and as such, he represents emotion.
In many episodes, Spock and McCoy, logic and emotion, end up arguing opposite sides of a problem. To resolve it, the show brings in Captain Kirk.
So let me ask you.
If Spock brings logic, and Bones brings emotion, what does Kirk bring?
If this were a Kahoot "word salad" I would expect to see writ large: LEADERSHIP. WISDOM. .
And WHAT is the common denominator, according to the literature, of leadership and wisdom?
The COMMON DENOMINATOR of BOTH wisdom and leadership is: Experience.
When we look back at our assumptive definition, Learning = Acquiring logical rules, we see that the missing element is experience.
So, if the acquisition of logical rules isn’t learning, what is?
We'll deal with that in the next blog entry.
A la prochaine,
P.S. FYI, I'll be speaking about AI in L&D at the Learning Guild's LEARN2021 conference, which is now online (the poster is out of date, but ain't it pretty, though?). Check their website for details.