A theme I have been exploring in this blog has been heuristic
thinking. You might think that I have
been downgrading rational thinking. I’m
not, but the point is that rational thinking, which counts on extensive
information gathering and calculations of that information is, one, simply not
what people do and, two, not what people, in many situations, can do. Oh; it turns out; heuristics seem to have a
pretty good track record. To remind you,
heuristic thinking is the thought process one employs that is based on a “rule
of thumb.” Let me share an example that
I think is very telling and refers to the best sport devised by humans,
baseball. The example is provided by
Gerd Gigernzer.[1]
Assume you want to study how players
catch balls that come in from a high angle – like in baseball, cricket, or
soccer – because you want to build a robot that can catch them. The traditional approach, which is much like
optimization under constraints, would be to try to give your robot the complete
representation of its environment and the most expensive computation machinery
you can afford. You might feed your
robot a family of parabolas because thrown balls have parabolic trajectories,
with the idea that the robot needs to find the right parabola in order to catch
the ball. Or you feed him measurement
instruments that can measure the initial distance, the initial velocity, and
the initial angle the ball was thrown or kicked. You’re still not done because in the real
world balls are not flying parabolas, so you need instruments that can measure
the direction and the speed of the wind at each point of the ball’s flight to
calculate its final trajectory and its spin.
It’s a very hard problem, but this is one way to look at it.
A very different way to approach this
is to ask if there is a heuristic that a player could actually use to solve
this problem without making any of these calculations, or only a very few. Experimental studies have shown that actual
players use a quite simple heuristic that I call the gaze heuristic. When a ball comes in high, a player starts
running and fixates his eyes on the ball.
The heuristic is that you adjust your running speed so that the angle of
the gaze, the angle between the eye and the ball, remains constant. If you make the angle constant the ball will
come down to you and it will catch you, or at least it will hit you. This heuristic only pays attention to one
variable, the angle of gaze, and can ignore all the other causal, relevant
variables and achieve the same goal much faster [making catching the ball
possible], more frugally, and with less chances for error [a likely event given
the number of complex computations described above].[2]
Please excuse the length of this quote, but I think it’s so
cool. Why? Because I loved playing baseball and I, in an instinctive manner, applied the gaze heuristic on the streets of my New York
neighborhood playing stickball some sixty or so years ago. This is not such an outstanding achievement
on my part; dogs apply the same heuristics catching Frisbees.[3] What the example shows, among other things,
is that some heuristics are part of our evolutionary wiring. Yet some are taught and some are developed
subconsciously due to their functionality – our subconscious mind notes that if
we act this way, this other desired event will happen.
Now, what if our robot is not built to catch a ball but to
carry you along in traffic (as in self-driving cars)? Would you feel comfortable if that car
functions with a set of heuristic formulas or would you want it to take into
account as many variables as possible? I
can’t help thinking that this is part of the design thinking that those
companies who are developing these cars are considering. My point is:
we can’t make a blanket statement that all heuristic formulas are better
than reasoned calculations. I mentioned
above that heuristics are formed by our mental makeup, our being taught them,
or by our subconscious developing relations between events. But there is another way: we believe relations because our emotions
dispose us to believe certain heuristics even when experience should teach us
otherwise. Gigerenzer quotes H. G.
Wells: “If we want to have an educated
citizenship in a modern technological society, we need to teach them three
things: reading, writing, and
statistical thinking.”[4] So part of a civics teacher’s job is to
convince students that reality is complex; that in order to deal with that
reality, a variety of thinking is needed, some rational and reasoned and some
instinctive and based on hunches relying on as good a knowledge base as is
practical given the constraints of the situation. My hunch is that we don’t pay those who are
to do this sort of thing enough compensation.[5]
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