drawing one of the figures with a very, very slight rotation, which completely screwed up its ability to identify it.
I’m not clear on whether you took this bit from their docs into account:
The system was NOT trained on upside down images, or rotations and skews
beyond a simple right-to-left flip. In addition, the system was not trained on any curved lines, only straight line objects.
That is, I’m not clear whether the steps you’re describing include training on rotations or not.
rather than you merely thinking it did because you could rephrase your intuitive, commonsense reasoning in the model’s terminology
No, I gave you one specific prediction that PCT makes: higher-level controllers operate over longer time scales than low-level ones. This prediction is not a part of any other model I know of. Do you know of another model that makes this prediction? I only know of models that basically say that symptom substitution takes time, with no explanation of how it occurs.
This doesn’t have anything to do with whether I believe that prediction to be useful; the prediction is still there, the observation that people do it is still there, and the lack of explanation of that fact is still there, even if you remove me from the picture entirely.
You can e.g. summarize the chain of useful, critical insights that get me from “it’s a network of feedback controllers” to a useful model, so I know which part I’d be skeptical of and which parts assume the solution of problems I know to be unsolved, so I know where to direct my attention.
I can only do that if I understand specifically what it is you don’t get—and I still don’t.
For example, I don’t see why the existence of unsolved problems is a problem, or even remotely relevant, if all the other models we have have to make the same assumption.
From my POV, you are ignoring the things that make PCT useful: namely that it actually predicts as normal, things that other current behavioral models have to treat as special cases or try to handwave out of existence. It’s not that PCT is “simpler” than stimulus-response or “action steps” models, it’s that it’s the simplest model that improves on our ability to make correct predictions about behavior.
Your argument seems to be, “but PCT requires us to gather more information in order to make those predictions”. And my answer to that is, “So what? Once you have that information, you can make way better predictions.” And it’s not that you could just feed the same information into some other model and get similar predictions—the other models don’t even tell you what experiments to perform to get yes-or-no answers.
To put it another way, to the extent that PCT requires you to be more precise or gather more information, it is doing so because that degree of actual uncertainty or lack of knowledge exists… and current experimental models disguise that lack of understanding behind statistics.
In contrast, to do a PCT experiment, you need to have a more-specific, falsifiable hypothesis: is the animal or person controlling quantity X or not? You may have to do more experiments in order to identify the correct “X”, but you will actually know something real, rather than, “47% of rats appear to do Y in the presence of Z”.
That is, I’m not clear whether the steps you’re describing include training on rotations or not.
But that’s a pretty basic transformation, and if they could handle it, they would have done so. In any case, the rotation was very slight, and was only one of many tests I gave it. It didn’t merely assign a slightly lower probability to the correct answer, it fell off the list entirely.
Consider how tiny the pictures are, this is not encouraging.
Your argument seems to be, “but PCT requires us to gather more information in order to make those predictions”. And my answer to that is, “So what? Once you have that information, you can make way better predictions.”
No, you misunderstand: my complaint is that PCT requires us to solve problems of equal or greater difficulty than the initial problem being solved. To better explain what I mean, I gave you the example with the literal tape-and-table Turing machine. Watch what happens when I make your same point, but in advocacy of the “Turing machine model of human behavior”.
“I’ve discovered a great insight that helps unify my research and better assist people with their problems. It’s to view them as a long, sectioned tape with a reader and state record, which [explanation of Turing machine]. This model is so useful because all I have to do is find out whether people have 1′s rather than 0′s in places 5000-5500 on their tape, and if they do, I just have to change state 4000 to erase rather than merely move state! This helps explain why people have trouble in their lives, because they don’t erase bad memories.”
See the problems with my version?
1) Any model of a human as a Turing machine would be way more complex than the phenomenon I’m trying to explain, so the insight it gives is imaginary.
2) Even given a working model, the mapping from any part of the TM model to the human is hideously complex.
3) “Finding someone’s 1′s and 0′s” is near impossible because of the complexity of the mapping.
4) The analogy between erasing memories and erasure operations is only superficial, and not indicative of the model’s strength.
5) Because I obviously could not have a TM model of humans, I’m not actually getting my insight from the model, but from somewhere else.
And points 1-5 are exactly what I claim is going on with you and PCT.
Nevertheless, I will confess I’ve gotten more interested in PCT, and it definitely looks scientific for the low level systems. I’ve read the first two Byte magazine articles and reproduced it in Matlab’s Simulink, and I’m now reading the third, where it introduces hierarchies.
My main dispute is with your insistence that you can already usefully apply real predictions from PCT at higher-level systems, where the parallels with feedback control systems appear very superficial and the conclusions seem to be reached with commonsense reasoning unaided by PCT.
Btw: my apologies, but somehow I accidentally deleted a part of my last reply before posting it, and my remark now resides only in my memory. It’s related to the same point I just made. I’ll put it here so you don’t need to reply a second time to that post:
To phrase it in terms of a feedback controller, I have to identify—again, in the rationalist sense, not just a pleasant sounding label—the reference being controlled. So, that means I have to specify all of the relevant things that affect my attaction level. Then, I have to find how the sensory data is transformed into a comparable format … Only then am I able to set up a model that shows an error signal which can drive behavior.
I still don’t see your point about this. Any model has to do the same thing, doesn’t it? So how is this a flaw of PCT?
No, a model doesn’t need to do the same thing. A purely neuronal model would not need to have the concept of “sexiness” and a comparator for it. Remember, the whole framing of a situation as a “romantic relationship” is just that: a framing the we have imposed on it to make sense of the world. It does not exist at lower levels, and so models need not be able to indentify such complex “invariants”.
I’m sorry, but I’m still utterly baffled by your comments, since your proposed “purely neuronal” model is more analogous to the Turing machine.
It sounds a bit like the part you’re missing is the PCT experimental design philosophy, aka the Test—a way of formulating and testing control hypotheses at arbitrary levels of the hierarchy. To test “sexiness” or some other high-level value, it is not necessary to completely specify all its lower-level components, unless of course the goal of your experiment is to identify those components.
We don’t need, for example, to break down how object invariance happens to be able to do an experiment where a rat presses a bar! We assume the rat can identify the bar and determine whether it is currently pressed. The interesting part is what other things (like food, mate availability, shock-avoidance, whatever) that you can get the rat to control by pressing a bar. (At least, at higher levels.)
I’m sorry, but I’m still utterly baffled by your comments, since your proposed “purely neuronal” model is more analogous to the Turing machine.
So? I agree that the “purely neuronal” model would be really complex (though not as complex as the Turing machine would be). I just brought it up in order to show how a model doesn’t “need to have a sexiness comparator anyway”, so you do have to justify the simplicity gained when you posit that there is one.
It sounds a bit like the part you’re missing is the PCT experimental design philosophy, aka the Test—a way of formulating and testing control hypotheses at arbitrary levels of the hierarchy. To test “sexiness” or some other high-level value, it is not necessary to completely specify all its lower-level components, unless of course the goal of your experiment is to identify those components.
But if you don’t specify all of the lower level components, then your controls explanation is just a restating of the problem, not a simplifying of it. The insight you claim you are getting from it is actually from your commonsense reasoning. Indeed, virtually every insight you “explain” by PCT, you got some other way.
We don’t need, for example, to break down how object invariance happens to be able to do an experiment where a rat presses a bar!
Sure, but that’s because you don’t need to account for the rat’s ability to identify the bar in a wide variety of contexts and transformations, which is the entire point of looking for invariants.
But if you don’t specify all of the lower level components, then your controls explanation is just a restating of the problem, not a simplifying of it. The insight you claim you are getting from it is actually from your commonsense reasoning.
Kindly explain what “commonsense reasoning” explains the “symptom substitution” phenomenon in hypnosis, and in particular, explains why the duration of effect varies, using any model but PCT.
While I can look up “symptom substitution”, I’ll to know more specifically what you mean by this. But I’d have to be convinced that PCT explains it first in a way that doesn’t smuggle in your commonsense reasoning.
Now, if you want examples of how commonsense reasoning leads to the same conclusions that are provided as examples of the success of PCT, that I already have by the boatload. This whole top-level post is an example of using commonsense reasoning but attributing it to PCT. For example, long before I was aware of the concept of a control system, or even feedback (as such) I handled my fears (as does virtually everyone else) by thinking through what exactly it is about the feared thing that worries me.
Furthermore, it is obvious to most people that if you believe obstacles X, Y, and Z are keeping you from pursuing goal G, you should think up ways to overcome X, Y, and Z, and yet Kaj here presents that as something derived from PCT.
While I can look up “symptom substitution”, I’ll to know more specifically what you mean by this.
Specifically, find a “commonsense” explanation that explains why symptom substitution takes time to occur, without reference to PCT’s notion of a perception averaged over time.
Googling “symptom substitution” lead me to a journal article that argued that people have tried and failed to find evidence that it happens...
That’s Freudian symptom substitution, and in any case, the article is splitting hairs: it says that if you stop a child sucking its thumb, and it finds some other way to get its needs met, then that doesn’t count as “symptom substitution”. (IOW, the authors of the paper more or less defined it into nonexistence, such that if it exists and makes sense, it’s not symptom substitution!)
Also, the paper raises the same objection to the Freudian model of symptom substitution that I do: namely, that there is no explanation of the time frame factor.
In contrast, PCT unifies the cases both ruled-in and ruled out by this paper, and offers a better explanation for the varying time frame issue, in that the time frame is governed by the perceptual decay of the controlled variable.
I’m not clear on whether you took this bit from their docs into account:
That is, I’m not clear whether the steps you’re describing include training on rotations or not.
No, I gave you one specific prediction that PCT makes: higher-level controllers operate over longer time scales than low-level ones. This prediction is not a part of any other model I know of. Do you know of another model that makes this prediction? I only know of models that basically say that symptom substitution takes time, with no explanation of how it occurs.
This doesn’t have anything to do with whether I believe that prediction to be useful; the prediction is still there, the observation that people do it is still there, and the lack of explanation of that fact is still there, even if you remove me from the picture entirely.
I can only do that if I understand specifically what it is you don’t get—and I still don’t.
For example, I don’t see why the existence of unsolved problems is a problem, or even remotely relevant, if all the other models we have have to make the same assumption.
From my POV, you are ignoring the things that make PCT useful: namely that it actually predicts as normal, things that other current behavioral models have to treat as special cases or try to handwave out of existence. It’s not that PCT is “simpler” than stimulus-response or “action steps” models, it’s that it’s the simplest model that improves on our ability to make correct predictions about behavior.
Your argument seems to be, “but PCT requires us to gather more information in order to make those predictions”. And my answer to that is, “So what? Once you have that information, you can make way better predictions.” And it’s not that you could just feed the same information into some other model and get similar predictions—the other models don’t even tell you what experiments to perform to get yes-or-no answers.
To put it another way, to the extent that PCT requires you to be more precise or gather more information, it is doing so because that degree of actual uncertainty or lack of knowledge exists… and current experimental models disguise that lack of understanding behind statistics.
In contrast, to do a PCT experiment, you need to have a more-specific, falsifiable hypothesis: is the animal or person controlling quantity X or not? You may have to do more experiments in order to identify the correct “X”, but you will actually know something real, rather than, “47% of rats appear to do Y in the presence of Z”.
But that’s a pretty basic transformation, and if they could handle it, they would have done so. In any case, the rotation was very slight, and was only one of many tests I gave it. It didn’t merely assign a slightly lower probability to the correct answer, it fell off the list entirely.
Consider how tiny the pictures are, this is not encouraging.
No, you misunderstand: my complaint is that PCT requires us to solve problems of equal or greater difficulty than the initial problem being solved. To better explain what I mean, I gave you the example with the literal tape-and-table Turing machine. Watch what happens when I make your same point, but in advocacy of the “Turing machine model of human behavior”.
“I’ve discovered a great insight that helps unify my research and better assist people with their problems. It’s to view them as a long, sectioned tape with a reader and state record, which [explanation of Turing machine]. This model is so useful because all I have to do is find out whether people have 1′s rather than 0′s in places 5000-5500 on their tape, and if they do, I just have to change state 4000 to erase rather than merely move state! This helps explain why people have trouble in their lives, because they don’t erase bad memories.”
See the problems with my version?
1) Any model of a human as a Turing machine would be way more complex than the phenomenon I’m trying to explain, so the insight it gives is imaginary.
2) Even given a working model, the mapping from any part of the TM model to the human is hideously complex.
3) “Finding someone’s 1′s and 0′s” is near impossible because of the complexity of the mapping.
4) The analogy between erasing memories and erasure operations is only superficial, and not indicative of the model’s strength.
5) Because I obviously could not have a TM model of humans, I’m not actually getting my insight from the model, but from somewhere else.
And points 1-5 are exactly what I claim is going on with you and PCT.
Nevertheless, I will confess I’ve gotten more interested in PCT, and it definitely looks scientific for the low level systems. I’ve read the first two Byte magazine articles and reproduced it in Matlab’s Simulink, and I’m now reading the third, where it introduces hierarchies.
My main dispute is with your insistence that you can already usefully apply real predictions from PCT at higher-level systems, where the parallels with feedback control systems appear very superficial and the conclusions seem to be reached with commonsense reasoning unaided by PCT.
Btw: my apologies, but somehow I accidentally deleted a part of my last reply before posting it, and my remark now resides only in my memory. It’s related to the same point I just made. I’ll put it here so you don’t need to reply a second time to that post:
No, a model doesn’t need to do the same thing. A purely neuronal model would not need to have the concept of “sexiness” and a comparator for it. Remember, the whole framing of a situation as a “romantic relationship” is just that: a framing the we have imposed on it to make sense of the world. It does not exist at lower levels, and so models need not be able to indentify such complex “invariants”.
I’m sorry, but I’m still utterly baffled by your comments, since your proposed “purely neuronal” model is more analogous to the Turing machine.
It sounds a bit like the part you’re missing is the PCT experimental design philosophy, aka the Test—a way of formulating and testing control hypotheses at arbitrary levels of the hierarchy. To test “sexiness” or some other high-level value, it is not necessary to completely specify all its lower-level components, unless of course the goal of your experiment is to identify those components.
We don’t need, for example, to break down how object invariance happens to be able to do an experiment where a rat presses a bar! We assume the rat can identify the bar and determine whether it is currently pressed. The interesting part is what other things (like food, mate availability, shock-avoidance, whatever) that you can get the rat to control by pressing a bar. (At least, at higher levels.)
So? I agree that the “purely neuronal” model would be really complex (though not as complex as the Turing machine would be). I just brought it up in order to show how a model doesn’t “need to have a sexiness comparator anyway”, so you do have to justify the simplicity gained when you posit that there is one.
But if you don’t specify all of the lower level components, then your controls explanation is just a restating of the problem, not a simplifying of it. The insight you claim you are getting from it is actually from your commonsense reasoning. Indeed, virtually every insight you “explain” by PCT, you got some other way.
Sure, but that’s because you don’t need to account for the rat’s ability to identify the bar in a wide variety of contexts and transformations, which is the entire point of looking for invariants.
Kindly explain what “commonsense reasoning” explains the “symptom substitution” phenomenon in hypnosis, and in particular, explains why the duration of effect varies, using any model but PCT.
While I can look up “symptom substitution”, I’ll to know more specifically what you mean by this. But I’d have to be convinced that PCT explains it first in a way that doesn’t smuggle in your commonsense reasoning.
Now, if you want examples of how commonsense reasoning leads to the same conclusions that are provided as examples of the success of PCT, that I already have by the boatload. This whole top-level post is an example of using commonsense reasoning but attributing it to PCT. For example, long before I was aware of the concept of a control system, or even feedback (as such) I handled my fears (as does virtually everyone else) by thinking through what exactly it is about the feared thing that worries me.
Furthermore, it is obvious to most people that if you believe obstacles X, Y, and Z are keeping you from pursuing goal G, you should think up ways to overcome X, Y, and Z, and yet Kaj here presents that as something derived from PCT.
Specifically, find a “commonsense” explanation that explains why symptom substitution takes time to occur, without reference to PCT’s notion of a perception averaged over time.
Googling “symptom substitution” lead me to a journal article that argued that people have tried and failed to find evidence that it happens...
That’s Freudian symptom substitution, and in any case, the article is splitting hairs: it says that if you stop a child sucking its thumb, and it finds some other way to get its needs met, then that doesn’t count as “symptom substitution”. (IOW, the authors of the paper more or less defined it into nonexistence, such that if it exists and makes sense, it’s not symptom substitution!)
Also, the paper raises the same objection to the Freudian model of symptom substitution that I do: namely, that there is no explanation of the time frame factor.
In contrast, PCT unifies the cases both ruled-in and ruled out by this paper, and offers a better explanation for the varying time frame issue, in that the time frame is governed by the perceptual decay of the controlled variable.