A PCT Model of a PCT Net Discussion

[From Rick Marken (930324.0800)]

Bruce Nevin (Wed 930324 08:44:38) --

The application of PCT to our own ongoing discourse is a Good
Thing, and I hope it continues until I am able to participate
more.

I'm glad you think so because I went to the trouble of developing
a diagram of my PCT model of our PCT discourse. I hope it will
show you what I mean when I talk about controlled and uncontrolled
perceptions.

Here is the diagram:

System Boundary
        >>_____________________________________________________________
"boss || "me"
reality"|| reference for
        >> uncontrolled perception
        >> r
        >> >
        >> v
        >> >C> ---->pure disturbance --> awareness of
        >> ^ error error
        >> >
        >> o------> copy of perception ----> awareness of
Other || | of disturbance disturbance
People's|| |
Posts || |
        >> ____ | __________
d(t) -->|f(d(t)| ------o------>| |
        >______| meaning[d(t)] | | ___
        >> > h[m(d(t) | p(t) | | r reference for
My || | + |----->| C |<--- controlled
Posts || | m(o(t)] | |___| variable
        >>_____ | | | p(t)
o(t) -->|f(o(t)| ------------->|__________| |
^ |______| meaning[o(t)] |
> >> >
> >> >
> >>_____ e(t)= r-p(t) |
  ------|g(e(t)|<----------------------------------
        >______|
        >>
        >>_________________________________________________________________

The column of double vertical lines is the boundary between the control
system (me) and the environment (boss reality). Other people's posts,
d(t), and my posts, o(t), are variables in boss reality. They are
converted into perceptual signals by the perceptual functions, f(),
in the boxes at the interface to boss reality (actually, these boxes
probably represent the SAME function operating at different times; I
use the same perceptual function to extract the same perceptual
variable from my posts and those of others; but I think it is OK
to represent this temporal difference as a spacial difference in the
model). These perceptual functions are pretty fancy boxes because
they turn the posts into a signal (meaning(o(t) or meaning (d(t))
whose magnitude is the "meaning" of the posts; let's imagine that
these boxes transform the words in the post into a signal whose
magnitude indicates the degree of "cause-effect PCT imagery" in
the post. [Of course, I imagine that there are many parallel
perceptual functions that produce signals whose magnitude is
proportional to other "meanings" in the post; I'm just focusing
on one "meaning" aspect of the post in this first level]

The "meaning" signals are the inputs to a "second level" perceptual
function box that uses the h() function to convert the two
inputs into a higher level perceptual signal. This higher level
perception, p(t) is the perception I am controlling in the network
dialog about PCT. A name for this perception might be "average amount
of cause-effect PCT imagery occuring on the net". (Again, this is
just ONE perceptual variable that I might be controlling; many higher
order perceptions of the discourse are surely being computed in
parallel).

To simplify the model I have drawn the perceptions of BOTH o(t) and
d(t) [that is, meaning (o(t)) and meaning (d(t))] as UNCONTROLLED;
in fact, only my perception of d(t) is uncontrolled. All this means
is that there is no feedback link from me to d(t) that can
influence my perception of the "meaning" of d(t) [ of course,
there is a feedback link to other aspects of the perception of
d(t) -- such as whether it exists or not; I can affect the latter
pereption by either reading or not reading my e-mail]. There
IS a feedback link from my outputs to the aspects of o(t) on
which my meaning perception of o(t) depend -- but, for the sake of
(relative) simplicity, I have not drawn them in.

One more aspect of the diagram and then I'll throw it out to the
net for discussion. Note at the top of the graph that I have
shown the perception of d(t) brancing off of its path to the
second level perceptual input. The perception of d(t) is uncontrolled;
it simply exists as my perception of the degree of "cause-effect PCT
imagery" in the other person's post. I can become "aware" of that
perception (this is one aspect of consciousness in the PCT model;
perception of a perception); this is indicated to the signal
branch ending at "awareness of disturbance". If I have a reference
level for this perception then the perception will be compared
to this reference and an error signal will result; this error
signal might also become the object of awareness -- so you perceive
the disturbance "as an error" -- ie. "that was a silly post -- it
has too much "cause effect PCT imagery" in it. But all I can do
is experience this error -- since the perception of d(t) (at this
level) cannot be affected by my outputs; it is just
an uncontrolled perception -- and the error just happens.

Hopefully, this diagram shows the two main points I was trying
to make in earlier posts. First, the system that is controlling
p(t) -- by varying o(t) -- has no information about what was in
the perceptions of the component posts from which this perception
is derived; all this systems knows about and controls is p(t) -- the
"average amount of cause-effect PCT imagery occuring on the net" --
regardless of the lower level perceptions that contribute to this
average. At the same time, however, my consciousness might be
aware of the perception of d(t) and o(t) that happen to
contribute to p(t). I may have a vague idea that the perceptions
of o(t) and d(t) do contribute to the higher level perception
I am controlling -- but, with my awareness sitting at the first
level of the model, I am most likely to see my own outputs,
o(t) as responses to the disturbances, d(t) that I perceive.

This little exercise just made me realize that the first illusion
described in the "Blind men and the elephant" paper applies not
only to observers of other people's behavior -- it applies to
ourselves when we look at our OWN behavior too. Since perceptions
of d(t) and o(t) are sure to be at a lower level than the
perception that is being controlled by o(t), we are very likely
to conclude that our own behavior (o(t)) is a response to
input (d(t)). No wonder people believe that inputs (information,
perception, "feedback", etc) guide behavior; it not only looks
that way when we look at other people -- it also looks that way
when we look at our OWN behavior -- from the wrong level.

Best

Rick