[From Rick Marken (2002.09.25.1630)]
Bill Powers (2002.09.25.1336 MDT)--
Something here still nags at me -- perhaps you can fix it. When I speak of
a causal connection, I mean a reliable way to make something happen. A
thermometer reading is pretty reliably caused by the temperature of the
medium it's put in. Turning a car's steering wheel to the right pretty
reliably caused the car to turn right. In general, "x causes y" means y =
f(x), at least as I understand the term.
Yes. That's what I mean, too: x causes y means y = f(x). But in your examples,
particularly the steering wheel example, y = f(x1) + f(x2) + ... The direction
the car goes (y) depends on the direction in which you turn the steering wheel
(x1) and on other factors (x2...), too. So if you're comfortable with the idea
that the direction of turn of the steering wheel causes the direction of the car
then you should be comfortable with the idea that disturbances cause behavior.
I can also see bringing in multiple causation: y = f(x1, x2, ...), as in
your .qo = d1 - d2. But in that case, I could not predict y unless I knew
beforehand, or could set, the values of x1, x2, and so on. If y = f(x1,
x2) and I can control only x1, then I have no way of knowing what value of
y will result because I don't know what x2 will be. The best I could do
would be to predict the _most likely_ value of y given x1 by computing the
distribution of values of x2 and using the mean value in the prediction. In
any one trial, the prediction would be off by some amount ranging from
small to large.
Sure, that's true of prediction. But this fact about prediction is true for all
systems, control or causal. If the output, qo, of a system is multiply
determined (qo = r - d for control and qo = d1 - d2 for causal) then you can't
predict qo if you know the value of only one of the independent variables.
I'm not used to thinking of a variable being "caused" by another variable
when (a) the supposed causal variable is not the only one that can
contribute to the effect,
But you think of car turning this way even though the steering wheel is not the
only variable that affects the direction of turn.
and (b) the other variables are not predictable.
The direction of the wind is not predictable but it doesn't stop you from
thinking that the direction of the car is caused by the steering wheel and the
So what do we make of this?
What I make of it is what I said in my previous post:
what is unique about control systems [in terms of causality] is _not_
the absence of a causal connection between independent (d) and
dependent (qo) variable nor is it that secular variations in reference
specifications (r) nullify this connection in some way. What is
unique about control systems is that the causal connection between
independent and dependent variable goes through the environment (via
the feedback function connecting dependent and controlled variable); it
does not go though the system that produces variations in the dependent
variable (as appears to be the case with living organisms).
In other words, the important thing about causality when behavior is looked at
through control theory glasses is the _behavioral illusion_. It's not that
behavior is not caused by external circumstances; behavior (the actions that
affect that state of a controlled variable) is caused by disturbances to
controlled variables. Nor is it that behavior is uncontrollable; behavior can be
controlled despite autonomous variations in the reference for the controlled
variable. What we see when we look through control theory classes is that the
function relating stimulus (disturbance) to response (output) in a control
organization is a property of the environment, not the organism. That's what I
make of it.
Richard S. Marken, Ph.D.
The RAND Corporation
PO Box 2138
1700 Main Street
Santa Monica, CA 90407-2138
Tel: 310-393-0411 x7971