Reasons for my appeal

[From Bill Powers again --]
For those wondering why I found the Pruszinski, Kurtzer, et al. paper so
upsetting, annoying, or whatever (I haven’t yet figured out which
reaction is on top), there are some reasons more defensible than just
that I want to be appreciated.
The basic intellectual reason is that the paper cites as
“influential theories” only the main one against which I have
argued for some 50 years. It’s known now as “optimal control
theory.” That’s why I found it so surprising that Dr. Kurtzer should
be found subscribing to it – he has heard and I had thought long ago
understood and agreed with my arguments, and now appears to have rejected
them. I’d like to know why, and also I’d like to have my objections
recorded and at least discussed in public.
Optimal control theory is basically a strategy for designing control
systems that, for all I know, has virtues in general engineering
applications, but is to my mind an extremely unlikely or even flatly
wrong model of the behavior of any organism. It is based on deriving a
specification for a “control” (what we in PCT would call an
“output”) that will cause some external system to behave in a
particular way – open loop. Even if feedback (as we define it in
PCT) is involved in the form of eventual knowledge of the results of an
action, the feedback is used as a basis for revising the model from which
the output effects of the control are predicted, not as the primary
variable under control as in classical control theory and PCT.
In order to predict the effect of a vector of outputs, the predictor must
take into account (correctly) all the properties of the nervous
system and muscles, the kinematics of the body, the dynamics of the
interactions between the body and the physical world outside, the
behavior of independent variables in the environment that can disturb the
outcome as it is developing, and all the physical and chemical
interactions that occur between the actual outputs of the organism and
the final result that is to be achieved.

The authors of this paper acknowledge that there is great difficulty with
the multiple ways in which an output can have a particular final effect.
They note the ambiguity that arises when an attempt is made to trace
cause and effect from the environment to a perturbation of a joint angle
(shoulder in this case), since as they say there is an infinity of
combinations of causes that would have the same effect. That fact makes
for difficulties in designing an output “control” that will
have just one particular effect. How can the predictor know, given only
an experienced effect, which external cause is operating, so as to be
able to compute an opposing action to cancel the unwanted effect? The
correct answer is, “It can’t.”

Behind the optimal control approach is, I believe, a notion of control
that grew up because engineering is basically a commercial enterprise.
Because control systems are built by engineers to accomplish ends that
their customers want to be accomplished, the focus is on what the
control system produces to satisfy someone else’s desires. Therefore
engineers call the variable being controlled the “output” of
the controller, since it is the ultimate point of the design. The output
of a cruise control in a car is the speed of the car, because that’s what
the driver (not the controller) wants to be controlled. This, despite the
fact that the only output an actual cruise control device can produce by
itself is displacement of a linkage to a throttle. It can’t even sense a
headwind or tailwind or the upslope or downslope of the road or a soft
tire or a dragging brake. Talk about ambiguity!

In optimal control theory, it is said that the system controls its
behavior, planning its actions just so and thereby producing the desired
result. If you think of the desired result simply as a consequence of a
carefully adjusted behavior, it makes sense to think of control as
control of action. Control the action just right, and the desired result
will follow.

Of course that is all perfectly correct, in an exactly reproducible
environment free of unanticipated disturbances, with actions being
carried out by precisely adjustable actuators which never suffer changes
in their calibration, energy supplies, or physical integrity. However, it
is a pipe dream in the world in which organisms must learn to survive
using their own inherited equipment.

In a cruise control, what is actually controlled is not the speed of the
car, but a sensory signal representing the speed. If the sensor changes
its calibration, the cruise control will maintain the same sensed speed,
not the same actual speed. If the sensor is reading high, the actual
speed will be too low. Only a mythical or hypothetical cruise control can
sense the calibration of its own speed sensor. Real ones can’t.

Every practical control system works this way in the real world. What is
controlled is not the actuator output, the visible behavior, but the
sensory input. If a thermostat’s sensor becomes too sensitive to air
temperature, the room will be colder at the same setting of the
adjustment lever. If the gyrocompass starts reading too far west of
north, the airplane’s autopilot will faithfully steer a course too far
east of north. If a putative Mars Lander’s perception of its orbit is
expressed, accidentally, in the wrong units – say English rather than
metric – it will never be (and never was) heard from again.

Living control systems, and most nonliving ones, control their sensory
inputs, not their motor outputs.

The authors seem to have appreciated this because they speak in their
abstract of the “intelligent manipulation of sensory feedback.”
But in the world of optimal control theory, feedback is not from the
system’s output to its own input, but from the sensory input to the
output action. The effect is fed back from the input of the system to the
observer of the system. So now the model depends on converting a sensory
input effect into the right motor output, which makes it even less
believable as a theory of organismic behavior.

The whole problem arises from choosing the wrong point of view from which
to see a control process. Optimal control is described as seen by the
engineer building the system, not as the system itself would see it. The
system itself can know nothing of the external world but what its sensors
tell it; it can control nothing but what its sensors report to be
happening. Behavior of a living control system is the control of
perception, not action.

I could go on about the felicitous properties of hierarchical
multidimensional classical control, but I think the foregoing points are
enough to explain my frustration. I think there is room for discussion
here, if anyone would show up to discuss anything. Is that ever going to
happen? At the age of 85, I can’t wait too long to find out.

Best,

Bill P.

(Gavin Ritz 2011.10.27.11.46NZT)

[From
Bill Powers again --]

Bill

from what
I understand of your comments here.

There’s
really not much similarity other than the concept of feedback which is as old
as the hills.

Do you
want them to negate their ideas?

Does it
matter if their fundamental concept is just conjecture?

The whole
of cybernetics and their feedback model coupled with information theory is
conjecture. (and they have a huge following, I have told them so right in the lions
den, I have even suggest that they look at PCT, if they want to see how
testing, evidence and corroboration works in scientific thinking).

Have you
seen, Dennett’s Dawkins and Searle’s following, the Memetic Kings
it’s enormous, and their ideas are not conjecture it’s just plain
jingle musing.

Does it
really matter that Kurtzer has changed his mind? (That’s his prerogative)

Do you
want them to acknowledge PCT?

I’m
still not sure what the appealing would be about?

Kind regards

Gavin

For those wondering why I found the Pruszinski, Kurtzer, et al. paper so
upsetting, annoying, or whatever (I haven’t yet figured out which reaction is
on top), there are some reasons more defensible than just that I want to be
appreciated.
The basic intellectual reason is that the paper cites as “influential
theories” only the main one against which I have argued for some 50 years.
It’s known now as “optimal control theory.” That’s why I found it so
surprising that Dr. Kurtzer should be found subscribing to it –
he has heard and I had thought long ago understood and agreed with my
arguments, and now appears to have rejected them. I’d like to know why, and
also I’d like to have my objections recorded and at least discussed in public.
Optimal control theory is basically a strategy for designing control systems
that, for all I know, has virtues in general engineering applications, but is
to my mind an extremely unlikely or even flatly wrong model of the behavior of
any organism. It is based on deriving a specification for a “control”
(what we in PCT would call an “output”) that will cause some external
system to behave in a particular way – open
loop
. Even if feedback (as we define it in PCT) is involved in the
form of eventual knowledge of the results of an action, the feedback is used as
a basis for revising the model from which the output effects of the control are
predicted, not as the primary variable under control as in classical control
theory and PCT.
In order to predict the effect of a vector of outputs, the predictor must take
into account (correctly) all the
properties of the nervous system and muscles, the kinematics of the body, the
dynamics of the interactions between the body and the physical world outside,
the behavior of independent variables in the environment that can disturb the
outcome as it is developing, and all the physical and chemical interactions
that occur between the actual outputs of the organism and the final result that
is to be achieved.

The authors of this paper acknowledge that there is great difficulty with the
multiple ways in which an output can have a particular final effect. They note
the ambiguity that arises when an attempt is made to trace cause and effect
from the environment to a perturbation of a joint angle (shoulder in this
case), since as they say there is an infinity of combinations of causes that
would have the same effect. That fact makes for difficulties in designing an
output “control” that will have just one particular effect. How can
the predictor know, given only an experienced effect, which external cause is
operating, so as to be able to compute an opposing action to cancel the
unwanted effect? The correct answer is, “It can’t.”

Behind the optimal control approach is, I believe, a notion of control that
grew up because engineering is basically a commercial enterprise. Because
control systems are built by engineers to accomplish ends that their customers
want to be accomplished, the focus is on what the control system produces
to satisfy someone else’s desires. Therefore engineers call the variable being
controlled the “output” of the controller, since it is the ultimate
point of the design. The output of a cruise control in a car is the speed of
the car, because that’s what the driver (not the controller) wants to be
controlled. This, despite the fact that the only output an actual cruise
control device can produce by itself is displacement of a linkage to a
throttle. It can’t even sense a headwind or tailwind or the upslope or
downslope of the road or a soft tire or a dragging brake. Talk about ambiguity!

In optimal control theory, it is said that the system controls its behavior,
planning its actions just so and thereby producing the desired result. If you
think of the desired result simply as a consequence of a carefully adjusted
behavior, it makes sense to think of control as control of action. Control the
action just right, and the desired result will follow.

Of course that is all perfectly correct, in an exactly reproducible environment
free of unanticipated disturbances, with actions being carried out by precisely
adjustable actuators which never suffer changes in their calibration, energy
supplies, or physical integrity. However, it is a pipe dream in the world in
which organisms must learn to survive using their own inherited equipment.

In a cruise control, what is actually controlled is not the speed of the car,
but a sensory signal representing the speed. If the sensor changes its
calibration, the cruise control will maintain the same sensed speed, not the
same actual speed. If the sensor is reading high, the actual speed will be too
low. Only a mythical or hypothetical cruise control can sense the calibration
of its own speed sensor. Real ones can’t.

Every practical control system works this way in the real world. What is
controlled is not the actuator output, the visible behavior, but the sensory
input. If a thermostat’s sensor becomes too sensitive to air temperature, the
room will be colder at the same setting of the adjustment lever. If the
gyrocompass starts reading too far west of north, the airplane’s autopilot will
faithfully steer a course too far east of north. If a putative Mars Lander’s
perception of its orbit is expressed, accidentally, in the wrong units – say
English rather than metric – it will never be (and never was) heard from
again.

Living control systems, and most nonliving ones, control their sensory inputs,
not their motor outputs.

The authors seem to have appreciated this because they speak in their abstract
of the “intelligent manipulation of sensory feedback.” But in the
world of optimal control theory, feedback is not from the system’s output to
its own input, but from the sensory input to the output action. The effect is
fed back from the input of the system to the observer of the system. So now the
model depends on converting a sensory input effect into the right motor output,
which makes it even less believable as a theory of organismic behavior.

The whole problem arises from choosing the wrong point of view from which to
see a control process. Optimal control is described as seen by the engineer
building the system, not as the system itself would see it. The system itself
can know nothing of the external world but what its sensors tell it; it can
control nothing but what its sensors report to be happening. Behavior of a
living control system is the control of perception, not action.

I could go on about the felicitous properties of hierarchical multidimensional
classical control, but I think the foregoing points are enough to explain my
frustration. I think there is room for discussion here, if anyone would show up
to discuss anything. Is that ever going to happen? At the age of 85, I can’t
wait too long to find out.

Best,

Bill P.

[From Kenny Kitzke (2011.10.26)]

Tomorrow is my 68th birthday. I don’t really celebrate birthdays any more but I must tell you that your explanation below was so convicting that I sense you have taught me something profound and valuable about science, myself and my behavior. I guess that is a gift with significant and lasting value for a old engineer like me. You are appreciated in this man’s sojourn in life.

In a message dated 10/26/2011 1:23:37 P.M. Eastern Daylight Time, powers_w@FRONTIER.NET writes:

···

[From Bill Powers again --]
For those wondering why I found the Pruszinski, Kurtzer, et al. paper so upsetting, annoying, or whatever (I haven’t yet figured out which reaction is on top), there are some reasons more defensible than just that I want to be appreciated.
The basic intellectual reason is that the paper cites as “influential theories” only the main one against which I have argued for some 50 years. It’s known now as “optimal control theory.” That’s why I found it so surprising that Dr. Kurtzer should be found subscribing to it – he has heard and I had thought long ago understood and agreed with my arguments, and now appears to have rejected them. I’d like to know why, and also I’d like to have my objections recorded and at least discussed in public.
Optimal control theory is basically a strategy for designing control systems that, for all I know, has virtues in general engineering applications, but is to my mind an extremely unlikely or even flatly wrong model of the behavior of any organism. It is based on deriving a specification for a “control” (what we in PCT would call an “output”) that will cause some external system to behave in a particular way – * open loop* . Even if feedback (as we define it in PCT) is involved in the form of eventual knowledge of the results of an action, the feedback is used as a basis for revising the model from which the output effects of the control are predicted, not as the primary variable under control as in classical control theory and PCT.
In order to predict the effect of a vector of outputs, the predictor must take into account (correctly) all the properties of the nervous system and muscles, the kinematics of the body, the dynamics of the interactions between the body and the physical world outside, the behavior of independent variables in the environment that can disturb the outcome as it is developing, and all the physical and chemical interactions that occur between the actual outputs of the organism and the final result that is to be achieved.

The authors of this paper acknowledge that there is great difficulty with the multiple ways in which an output can have a particular final effect. They note the ambiguity that arises when an attempt is made to trace cause and effect from the environment to a perturbation of a joint angle (shoulder in this case), since as they say there is an infinity of combinations of causes that would have the same effect. That fact makes for difficulties in designing an output “control” that will have just one particular effect. How can the predictor know, given only an experienced effect, which external cause is operating, so as to be able to compute an opposing action to cancel the unwanted effect? The correct answer is, “It can’t.”

Behind the optimal control approach is, I believe, a notion of control that grew up because engineering is basically a commercial enterprise. Because control systems are built by engineers to accomplish ends that their customers want to be accomplished, the focus is on what the control system produces to satisfy someone else’s desires. Therefore engineers call the variable being controlled the “output” of the controller, since it is the ultimate point of the design. The output of a cruise control in a car is the speed of the car, because that’s what the driver (not the controller) wants to be controlled. This, despite the fact that the only output an actual cruise control device can produce by itself is displacement of a linkage to a throttle. It can’t even sense a headwind or tailwind or the upslope or downslope of the road or a soft tire or a dragging brake. Talk about ambiguity!

In optimal control theory, it is said that the system controls its behavior, planning its actions just so and thereby producing the desired result. If you think of the desired result simply as a consequence of a carefully adjusted behavior, it makes sense to think of control as control of action. Control the action just right, and the desired result will follow.

Of course that is all perfectly correct, in an exactly reproducible environment free of unanticipated disturbances, with actions being carried out by precisely adjustable actuators which never suffer changes in their calibration, energy supplies, or physical integrity. However, it is a pipe dream in the world in which organisms must learn to survive using their own inherited equipment.

In a cruise control, what is actually controlled is not the speed of the car, but a sensory signal representing the speed. If the sensor changes its calibration, the cruise control will maintain the same sensed speed, not the same actual speed. If the sensor is reading high, the actual speed will be too low. Only a mythical or hypothetical cruise control can sense the calibration of its own speed sensor. Real ones can’t.

Every practical control system works this way in the real world. What is controlled is not the actuator output, the visible behavior, but the sensory input. If a thermostat’s sensor becomes too sensitive to air temperature, the room will be colder at the same setting of the adjustment lever. If the gyrocompass starts reading too far west of north, the airplane’s autopilot will faithfully steer a course too far east of north. If a putative Mars Lander’s perception of its orbit is expressed, accidentally, in the wrong units – say English rather than metric – it will never be (and never was) heard from again.

Living control systems, and most nonliving ones, control their sensory inputs, not their motor outputs.

The authors seem to have appreciated this because they speak in their abstract of the “intelligent manipulation of sensory feedback.” But in the world of optimal control theory, feedback is not from the system’s output to its own input, but from the sensory input to the output action. The effect is fed back from the input of the system to the observer of the system. So now the model depends on converting a sensory input effect into the right motor output, which makes it even less believable as a theory of organismic behavior.

The whole problem arises from choosing the wrong point of view from which to see a control process. Optimal control is described as seen by the engineer building the system, not as the system itself would see it. The system itself can know nothing of the external world but what its sensors tell it; it can control nothing but what its sensors report to be happening. Behavior of a living control system is the control of perception, not action.

I could go on about the felicitous properties of hierarchical multidimensional classical control, but I think the foregoing points are enough to explain my frustration. I think there is room for discussion here, if anyone would show up to discuss anything. Is that ever going to happen? At the age of 85, I can’t wait too long to find out.

Best,

Bill P.

(Gavin Ritz 2011.10.27.15.15NZT)

[From Kenny Kitzke (2011.10.26)]

I agree Kenny it’s a well put powerful
argument and thoroughly convincing, to me and you.

Tomorrow
is my 68th birthday. I don’t really celebrate birthdays any more but I
must tell you that your explanation below was so convicting that I sense you
have taught me something profound and valuable about science, myself and my
behavior. I guess that is a gift with significant and lasting value for a
old engineer like me. You are appreciated in this man’s sojourn in life.

···

[From Bill Powers again --]

Living control systems, and most nonliving ones, control their sensory inputs,
not their motor outputs.

Behavior of a living control system is the control of perception, not action.

You would not believe how hard to is to convince
anyone of these two statements. There is something stuck in the perspectives of
us that seems to force us away from this perspective. In business I find that
type of thinking as supply side thinking.

I had long discussion with one of chairman of the
cybernetics society on the validity of the axioms of using Shannon’s Information
theory (for the record it’s total conjecture). I took him through many
winding roads of discourse and I believed proved logically that the argument of
information is conjecture.

In the end his final comments were this (believe
it or not), anybody can tell you that information (in a biological organisms)
is in its signals. (yes that was his final answer). The dialogue made no difference
at all, none. Now thinking back there was no purpose to the dialogue. Other
than me trying to disturb his control of perception.

There is something very profound about PCT in
that the very nature of it is Russian doll like. The concept of the Control of
Perception is a very hard thing to absorb because our very thinking and language
and knowledge is a control of perception. (I think, I’m not sure).

Regards

Gavin

[From Bill Powers (2011.10.27.0902 MDT)]

[From Kenny Kitzke
(2011.10.26)]

Kenny, a very happy birthday to you, and for both your sake and mine I
hope to say that quite a few times more.

Congratulations on becoming the decent thoughtful sincere and passionate
person that you are, Kenny. That’s more than most people manage to
accomplish in a lifetime.

Your experiences with teaching PCT are a little different from mine,
mainly because the people I deal with generally come to me specifically
to learn about it. Even if it upsets some of their beliefs, they expect
that and manage to get through it because behind it all is a genuine
interest in science. This self-selection makes my job easier.

I have received a pretty decent reply from one of the main proponents of
“optimal control theory”, and quite possibly this will serve as
oil on the waters – at least I’ll treat it as such until proven
otherwise.

Best,

Bill P.

[From Rick Marken (2011.10.27.0830)]

Bill Powers (2011.10.27.0902 MDT)--

I have received a pretty decent reply from one of the main proponents of
"optimal control theory", and quite possibly this will serve as oil on the
waters -- at least I'll treat it as such until proven otherwise.

Could you share it with us?

Best

Rick

···

--
Richard S. Marken PhD
rsmarken@gmail.com
www.mindreadings.com

[From Bill Powers (2011.10.27.0935 MDT)]

Rick Marken (2011.10.27.0830) --

>BP: I have received a pretty decent reply from one of the main proponents of
> "optimal control theory", and quite possibly this will serve as oil on the
> waters -- at least I'll treat it as such until proven otherwise.

RM: Could you share it with us?

I have asked permission; if I get it, I'll copy all posts to the group. Otherwise I'll just summarize.

Bill P.

[From Rick Marken (2011.10.28.1230)]

Bill Powers (2011.10.27.0935 MDT)--

>BP: �I have received a pretty decent reply from one of the main
> proponents of "optimal control theory"...

RM: Could you share it with us?

BP: I have asked permission; if I get it, I'll copy all posts to the group.
Otherwise I'll just summarize.

Thanks. It looks like we already got the first installment. Of course,
now the really interesting question is why Isaac attached himself to
this "optimal control" puppy after presumably having learned how
living control systems actually work (control of perception and all
that). But I do look forward to reading your discussion with Scott, if
it continues.

I did try again to understand the Nature article. I think I did
understand the first experiment, anyway. See if I got it right. I
think what they found was that for two different arm perturbations
(torque disturbances), both of which produced the same shoulder
displacement but different elbow displacements, were associated with
different firing rates in efferent neurons associated only with
producing compensatory shoulder torque. Apparently this is evidence
to them that "fast feedback responses" (whatever the heck those are; I
guess it's the motor firings) result from "integrating information
from both shoulder and elbow". This description of their model is
quite vague but I think I see their intuition: somehow the lower
firing rate to the shoulder when the elbow is also perturbed must
result from the fact that the perturbation to the elbow is being
taking into account (by integrating information from shoulder and
elbow). Is that about it?

If I'm understanding this correctly then II think this result is
predicted rather nicely by your little man model, where, as I recall,
a higher level system is controlling a perception derived from both
elbow and shoulder angle and controls that perception using two lower
level outputs to the shoulder and elbow. Sorry, I forget the details
but isn't this neurophysiological result indeed predicted by your
little man model? Indeed, I don't see what other model -- other than a
hierarchical control of input -- could account for this result (If I
understand it correctly). I wonder why they think this result is
consistent with optimal control theory. What do you think?

Best regards

Rick

···

--
Richard S. Marken PhD
rsmarken@gmail.com
www.mindreadings.com

[From Bill Powers (2011.10.29.0850 MDT)]

Rick Marken (2011.10.28.1230) --

RM: I did try again to understand the Nature article. I think I did
understand the first experiment, anyway. See if I got it right. I
think what they found was that for two different arm perturbations
(torque disturbances), both of which produced the same shoulder
displacement but different elbow displacements, were associated with
different firing rates in efferent neurons associated only with
producing compensatory shoulder torque. Apparently this is evidence
to them that "fast feedback responses" (whatever the heck those are; I
guess it's the motor firings) result from "integrating information
from both shoulder and elbow". This description of their model is
quite vague but I think I see their intuition: somehow the lower
firing rate to the shoulder when the elbow is also perturbed must
result from the fact that the perturbation to the elbow is being
taken into account (by integrating information from shoulder and
elbow). Is that about it?

BP: Hard to know when it's put into words like that. Applying torques that act around specific joints should disturb only the control system associated with that joint. That's a bit hard to do with an elbow joint because of reaction torques that would affect the shoulder, too. Is the disturbing torque servo connected so it grasps both the upper arm and forearm, and can move as the elbow changes position (not angle) as the shoulder angle changes? I don't see how there could be a sudden disturbance of elbow angle that wouldn't also cause the shoulder angle to change. But maybe they figured that out. And did the servo really just apply a position-independent torque, or did it force the joint to a different angle by applying however much torque was needed?

If there is a higher-order control system controlling a variable that is a function of both joint angles, there will be some disturbance of the higher-order variable simply because the first system can't control perfectly. This will especially be the case if the organism isn't trying to keep the joints at specific angles and the loop gain is low.

There is also the problem of muscles that span two joints, as in the case of the biceps and triceps. A muscle used in keeping the elbow angle constant may have a branch at the other end (biceps brachii) that tends to move the upper arm relative to the body, affecting the shoulder angle and disturbing control systems that use other muscles to control shoulder angles or rotations.

As I have modeled the "reach" direction of hand movement, it is accomplished by changing the internal elbow angle twice as much as the shoulder angle in the same plane. The controlled perceptual variable is 2*Elbow + Shoulder. When that sum is held constant at any given reference level, the reach distance is held constant. So affecting only the elbow angle would disturb the reach control system. It would also disturb the system that controls the line-of-sight hand position on a spherical surface with a constant reach radius, which requires only shoulder rotations. These two control systems are what remove the ambiguity of information that the optimal control people and their relatives worry about.

There are two modes of control that can be involved in controlling hand position in space. If vision is involved, control can be very precise, but it's slower because higher-order systems are involved, as well as different sensory modalities and longer signal paths. Kinesthetically, the same variables can be constructed from joint angle and muscle length sensor information, and would be faster but less precise because the sensory discrimination is much lower. Both kinds of control could act in parallel, with visual control dominating when the eyes are open so the kinesthetically controlling systems would never see significant error. I don't know if visual control was involved in the experiment. I guess I should see if I can look at the web page. I subscribe to Nature so I should be able to.

We also have to realize that torque disturbances can be quickly nullified by changes in muscle tension due to the tendon reflex. The tendon control system keeps the sensed tension in a tendon constant at the reference level specified by higher systems. If the application of torque tends to move the arm, any position controlling systems would resist, but if the reference tension didn't change, the tendon reflex would make the limb segment compliant to the applied torque. The tendon reflex would come into play if pressure on the skin is involved, because skin pressure also inhibits motor neurons, which is how we control the amount of pressure we apply to objects.

I don't see any way to understand this experiment without constructing working models and comparing what they do with what the subjects do. Rather big job, especially since the model has to include full physical dynamics.

Best,

Bill P.

[From Rick Marken (2011.10.30.1010)]

Bill Powers (2011.10.29.0850 MDT) --

RM: I did try again to understand the Nature article. I think I did
understand the first experiment, anyway. See if I got it right. ..

BP: Hard to know when it's put into words like that. Applying torques that
act around specific joints should disturb only the control system associated
with that joint. That's a bit hard to do with an elbow joint because of
reaction torques that would affect the shoulder, too. Is the disturbing
torque servo connected so it grasps both the upper arm and forearm, and can
move as the elbow changes position (not angle) as the shoulder angle
changes? I don't see how there could be a sudden disturbance of elbow angle
that wouldn't also cause the shoulder angle to change. But maybe they
figured that out. And did the servo really just apply a position-independent
torque, or did it force the joint to a different angle by applying however
much torque was needed?...

We also have to realize that torque disturbances can be quickly nullified by
changes in muscle tension due to the tendon reflex...

I don't see any way to understand this experiment without constructing
working models and comparing what they do with what the subjects do. Rather
big job, especially since the model has to include full physical dynamics.

RM: I knew that a model was needed (it always is) but it sounds like
there are far deeper methodological problems here than just the lack
of a model. It looks like what we have here is a very poorly designed
and conceived experiment that looks real scientific because it uses
trendy neurophysiological measures. I'm not sure it's such a bad thing
that PCT was not mentioned as a theory that seem behavior as the
control of "fast feedback".

Best

Rick

···

--
Richard S. Marken PhD
rsmarken@gmail.com
www.mindreadings.com

[From Kenny Kitzke
(2011.10.26)]

Gavin, no one understands any better than I do how difficult it is to convey PCT to business executives. I organized an Upside-Down Leader Forum with five very successful CEO’s in the Pittsburgh region. Why Upside-Down? Two reasons: 1) they are Christian leaders and anything but the greedy capitalists some like to classify as business men and 2) they understand that the often perplexing behavior of owners, customers, competitors and employees are the result of them controlling their input perceptions; not their observable output actions.

The first reason worked fine and we shared many beneficial beliefs about how responsible business leaders control their perceptions and positively influence their stakeholders. Despite a simple and gradual introduction to PCT (even the rubber band experiment that helped open my eyes), no one found it useful. In fact, my refusal to back away from teaching this Upside-Down understanding of human behavior seemed to disturb them enough that the Forum eventually folded.

I blamed myself for awhile as a poor teacher and advocate for PCT. There was resistance to learning a superior theory of psychology when whatever they believed and controlled for worked far better than what their peers believed and practiced. They saw no added value in my PCT methodology in their leadership and were too busy to spend their time on something they did not think they needed. Were all the human resource experts and consultants wrong and Kenny the PCTer right? They were skeptical and theiir ears were closed. Well, perhaps this is just my way of perceiving my lack of results as not really due to my lack of self-worth.

With my life waning, I have pretty much given up on changing the world. I take my joy in assisting one person at a time who is willing to learn and consider a better way to live combining the bible and PCT.

I am totally bored and disgusted with debating those with strongly held beliefs (often gathered anecdotally) whether their personal theory is about human behavior, science, health, education, economics, politics, religion, etc., Time is too precious to me for doing that. Just the misconceptions about correlation and cause in the daily news and scientific journals, even by supposedly educated experts, is enough to ruin my spirit…if I would allow it.

I sense you are frustrated by seeing experts take what happens sometimes in some circumstances to explain generalities in business or life. I too was feisty in my younger days about the porridge of unsupported claims by supposedly knowledgeable and sincere men of renown. With age, and perhaps with greater wisdom, I have chosen to spend my time on controlling my own perceptions about other human issues with a different purpose. If this freedom and peace also happens to you in time, I hope you will recall that I got there first, in part because of the profound merit of PCT!

In a message dated 10/26/2011 10:37:39 P.M. Eastern Daylight Time, garritz@XTRA.CO.NZ writes:

···

(Gavin Ritz 2011.10.27.15.15NZT)

[From Kenny Kitzke
(2011.10.26)]

I agree Kenny it’s a well put powerful argument and thoroughly convincing, to me and you.

Tomorrow is my 68th birthday. I don’t really celebrate birthdays any more but I must tell you that your explanation below was so convicting that I sense you have taught me something profound and valuable about science, myself and my behavior. I guess that is a gift with significant and lasting value for a old engineer like me. You are appreciated in this man’s sojourn in life.

 [From Bill Powers again --]



Living control systems, and most nonliving ones, control their sensory inputs, not their motor outputs.

Behavior of a living control system is the control of perception, not action.
You would not believe how hard to is to convince anyone of these two statements. There is something stuck in the perspectives of us that seems to force us away from this perspective. In business I find that type of thinking as supply side thinking.
I had long discussion with one of chairman of the cybernetics society on the validity of the axioms of using Shannon    ’s Information theory (for the record it’s total conjecture). I took him through many winding roads of discourse and I believed proved logically that the argument of information is conjecture.
In the end his final comments were this (believe it or not), anybody can tell you that information (in a biological organisms) is in its signals. (yes that was his final answer). The dialogue made no difference at all, none. Now thinking back there was no purpose to the dialogue. Other than me trying to disturb his control of perception.
There is something very profound about PCT in that the very nature of it is Russian doll like. The concept of the Control of Perception is a very hard thing to absorb because our very thinking and language and knowledge is a control of perception. (I think, I’m not sure).

Regards

Gavin