# What happened to cybernetics (was RE: The reality of "information")

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**Category:** CSG2009\
**Created:** [April 17, 2009, 7:45pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291 "2009-04-17T19:45:58Z")\
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**Author:** ![Arthur\_Dijkstra1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/a/b9bd4f/32.png) [@Arthur\_Dijkstra1](http://discourse.iapct.org/u/Arthur_Dijkstra1)\
**Post date:** [April 17, 2009, 7:45pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/1 "2009-04-17T19:45:58Z")

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Dear Bill,

With great interest I am trying to catch up on these interesting  
posts.

Can you please elaborate a bit more on what you say about  
cybernetics and Ashby in the following part:

Determining channel capacity, as you say, is a pretty simple  
proposition – no metaphysics needed. But information theory introduces  
metaphysics, and that is where IT and I part company. The concept that information  
is a reduction in uncertainty comes from confusing an equation used to describe  
a phenomenon with the phenomenon itself. I saw this happen in cybernetics, with  
Ashby’s “Law of Requisite Variety.” The whole concept of uncertainty  
in physics or in casinos is metaphysics. The fact that we sometimes say we are  
“uncertain” about something has no meaning outside our private  
experiences. It doesn’t mean that there is something in nature called  
uncertainty and we are sensing it. And reducing uncertainty can be accomplished  
by many means, including getting a good night’s sleep or regaining one’s  
self-confidence (justifiably or not).

Thanks,

Arthur Dijkstra

> **···**
>
> **Van:** Control Systems  
> Group Network (CSGnet) [[mailto:CSGNET@LISTSERV.ILLINOIS.EDU](mailto:CSGNET@LISTSERV.ILLINOIS.EDU)] **Namens** Bill  
> Powers  
> **Verzonden:** donderdag 16 april 2009 18:39  
> **Aan:** CSGNET@LISTSERV.ILLINOIS.EDU  
> **Onderwerp:** Re: The reality of “information”
> 
> [From Bill Powers  
> (2009.04.16.0819 MDT)]
> 
> Rick Marken (2009.04.15.2200)]
> 
> Martin Taylor:
> 
> > The exact  
> > same environmental situation can be perceived and controlled in a  
> > literally  
> > infinite number of different ways.
> 
> RM:  
> That seems to rule out the idea that perception is a process of  
> communicating to the mind what is actually out there in the  
> environment. If the same environmental situation can be perceived in  
> an infinite number of ways, the there is no information to be  
> transmitted about it. Information theory assumes that there is a  
> message to be transmitted and received. The message might be a binary  
> sequence like 1011010. There are 7 bits of information to be  
> transmitted in this message. If the received message is 1011010 then  
> we can say that 7 bits of information have been transmitted. If there  
> is noise in the transmission channel then the message received might  
> be 10x101x; only 5 bits were transmitted successfully. In this  
> situation, measuring the amount of information carried by a  
> transmission channel makes sense and it might even have practical  
> value; it can tell us how many times a message should be repeated over  
> a channel so that we can be sure it was received successfully.
> 
> # BP: I think you’re getting close to something here. Electrical engineers, or most people (like me) when they’re being engineers, are naive realists. We assume that the soldering iron is really there, that the circuit components are really what they appear to be, and so on. And the communications engineer assumes that the dots and dashes the telegrapher is sending are really in the sequence that appears to be happening. Shannon’s job at Bell Labs was to figure out how faithfully, and how fast, that sequence could be transmitted via some particular channel to its destination. Fidelity is determined by comparing the message that was sent against the message that was received. To define information transfer, or determine channel capacity, you have to know both. If you receive a message that says “Mary had a libble limb”, for all you know that is exactly the message that was transmitted, and the channel capacity was not exceeded. But if the original message was “Mary hab a labble lamb,” the message was not transmitted faithfully, regardless of what you expected the original to be. To know what the channel capacity is you have to have a way of knowing what is really Out There – what message was really sent. Determining channel capacity, as you say, is a pretty simple proposition – no metaphysics needed. But information theory introduces metaphysics, and that is where IT and I part company. The concept that information is a reduction in uncertainty comes from confusing an equation used to describe a phenomenon with the phenomenon itself. I saw this happen in cybernetics, with Ashby’s “Law of Requisite Variety.” The whole concept of uncertainty in physics or in casinos is metaphysics. The fact that we sometimes say we are “uncertain” about something has no meaning outside our private experiences. It doesn’t mean that there is something in nature called uncertainty and we are sensing it. And reducing uncertainty can be accomplished by many means, including getting a good night’s sleep or regaining one’s self-confidence (justifiably or not). Here is a quote from a Wiki article: [http://en.wikipedia.org/wiki/Information\_entropy](http://en.wikipedia.org/wiki/Information_entropy)
> 
> _Shannon’s entropy represents an absolute limit on the best possible lossless  
> compression of any communication, under certain constraints: treating messages  
> to be encoded as a sequence of independent and identically-distributed random  
> variables, Shannon’s source coding theorem shows that, in the limit, the  
> average length of the shortest possible representation to encode the messages  
> in a given alphabet is their entropy divided by the logarithm of the number of  
> symbols in the target alphabet.  
> A fair coin has an entropy of one bit. However, if the coin is not fair, then  
> the uncertainty is lower (if asked to bet on the next outcome, we would bet  
> preferentially on the most frequent result), and thus the Shannon entropy is  
> lower. Mathematically, a coin flip is an example of a Bernoulli trial, and its  
> entropy is given by the binary entropy function. A long string of repeating  
> characters has an entropy rate of 0, since every character is predictable. The  
> entropy rate of English text is between 1.0 and 1.5 bits per letter,[1] or as  
> low as 0.6 to 1.3 bits per letter, according to estimates by Shannon based on  
> human experiments.[2] ._ ==============================================================================
> 
> BP:  
> My immediate reaction to the first sentence is to start looking for exceptions  
> to this wild generalization. What do you mean, the “best possible lossless  
> compression of any communication?” Who says you have exhausted all the  
> possibilities ever known or that will ever be known? You can do this only by  
> defining some small universe with only a few possibilities so you can be sure  
> nothing has been left out – and this is exactly what information theory does.
> 
> That is why Shannon has to say “in a given alphabet”. As soon as he  
> said that, I knew two things: (1) information theory is not about the real  
> world, and (2) neither Shannon nor anyone else had any idea of the size of the  
> alphabet needed to encode all possible messages.
> 
> Channel capacity is a physical property of the transmission channel itself –  
> it does not change when you change alphabets. For example what is the message  
> you get if you call someone on the telephone and there is no answer? It doesn’t  
> matter what alphabet you expect the answer to be written or spoken in: no  
> answer gives you the information that nobody is answering that telephone. You  
> don’t know why, but there are endless possibilities, including a mass murder, a  
> fire, or a fickle friend. Considering all the things that might account for the  
> lack of an answer, it is clearly impossible to find any finite alphabet in  
> which every answer could be encoded. So information in the sense of knowledge  
> about the world is not the same thing as Shannon information. Channel capacity  
> does not tell you how much information the world has to give us, or how fast it  
> is generating that information.
> 
> An interesting thing happened on the way to the internet. Here’s another  
> reference, clearly somewhat dated:
> 
> [[http://www.skepticfiles.org/cowtext/comput~1/9600info.htm](http://www.skepticfiles.org/cowtext/comput~1/9600info.htm)
> 
> # ]([http://www.skepticfiles.org/cowtext/comput~1/9600info.htm](http://www.skepticfiles.org/cowtext/comput~1/9600info.htm))And some quotes from it:
> 
> ```auto
> The roughly 3000-Hz available in the telephone bandwidth poses few
> 
> ```
> 
> problems
> 
> ```auto
> for 300 bps modems, which only use about one fifth of the
> 
> ```
> 
> bandwidth. A full
> 
> ```auto
> duplex 1200 bps modem requires about half the available bandwidth,
> 
> ```
> 
> transmitting simultaneously in both directions at 600 baud and using
> 
> ```auto
> phase
> 
> ```
> 
> modulation to signal two data bits per baud. “Baud rate”
> 
> ```auto
> is actually a
> 
> ```
> 
> measure of signals per second. Because each signal can represent
> 
> ```auto
> more than
> 
> ```
> 
> one bit, the baud rate and bps rate of a modem are not necessarilly the
> 
> ```auto
> same.
> 
> ```
> 
> In the case of 1200 bps modems, their baud rate is actually 600 (signals
> 
> ```auto
> per
> 
> ```
> 
> second) and each signal represents two data bits. By multiplying
> 
> ```auto
> signals per
> 
> ```
> 
> second with the number of bits represented by each signal one determines
> 
> ```auto
> the
> 
> ```
> 
> bps rate: 600 signals per second X 2 bits per signal = 1200 bps.
> 
> ```auto
> 
> ```
> 
> In moving up to 2400 bps, modem designers decided not to use more
> 
> ```auto
> bandwidth,
> 
> ```
> 
> but to increase speed through a new signalling scheme known as
> 
> ```auto
> quadrature
> 
> ```
> 
> amplitude modulation (QAM).
> 
> ```auto
> 
> ```
> 
> In QAM, each signal represents four data bits. Both 1200 bps and
> 
> ```auto
> 2400 bps
> 
> ```
> 
> modems use the same 600 baud rate, but each 1200 bps signal carries two
> 
> ```auto
> data
> 
> ```
> 
> bits, while each 2400 bps signal carries four data bits:
> 
> ```auto
> 600 signals per second X 4 bits per signal = 2400 bps.
> 
> ```
> 
> _- - - - - - -  
> -_
> 
> ```auto
> 
> ```
> 
> ```auto
> 
> ```
> 
> ```auto
> *ECHO-CANCELLATION*
> 
> ```
> 
> ```auto
> 
> ```
> 
> ```auto
> *This method solves the problem of overlapping transmit and receive*
> 
> ```
> 
> ```auto
> *channels.*
> 
> ```
> 
> ```auto
> *Each modem's receiver must try to filter out the echo of its own*
> 
> ```
> 
> ```auto
> *transmitter*
> 
> ```
> 
> ```auto
> *and concentrate on the other modem's transmit signal. This presents*
> 
> ```
> 
> ```auto
> *a*
> 
> ```
> 
> ```auto
> *tremendous computational problem that significantly increases the*
> 
> ```
> 
> ```auto
> *complexity*
> 
> ```
> 
> ```auto
> *-- and cost -- of the modem. But it offers what other schemes*
> 
> ```
> 
> ```auto
> *don't:*
> 
> ```
> 
> ```auto
> *simultaneous two-way transmission of data at 9600 bps.*
> 
> ```
> 
> ```auto
> 
> ```
> 
> ```auto
> *The CCITT "V.32" recommendation for 9600 bps modems includes*
> 
> ```
> 
> ```auto
> *echo-*
> 
> ```
> 
> ```auto
> *cancellation. The transmit and receive bands overlap almost*
> 
> ```
> 
> ```auto
> *completely, each*
> 
> ```
> 
> ```auto
> *occupying 90 percent of the available bandwidth. Measured by*
> 
> ```
> 
> ```auto
> *computations per*
> 
> ```
> 
> ```auto
> *second and bits of resolution, a V.32 modem is roughly 64 times more*
> 
> ```
> 
> ```auto
> *complex*
> 
> ```
> 
> ```auto
> *than a 2400 bps modem. This translates directly into added*
> 
> ```
> 
> ```auto
> *development and*
> 
> ```
> 
> ```auto
> *production costs which means that it will be some time before V.32 modems*
> 
> ```
> 
> ```auto
> *can*
> 
> ```
> 
> ```auto
> *compete in the high- volume modem market.*
> 
> ```
> 
> ```auto
> 
> ```
> 
> =================================================================  
> BP:  
> … and now we have dial-up modems that run at 56000 bits per second by  
> compressing the message before transmission and decompressing the received  
> message. Net-Zero and Juno, I read, can compress text (in the server) to 4% of  
> its original size and achieve another factor of 25.
> 
> A last quote from [http://en.wikipedia.org/wiki/Modem](http://en.wikipedia.org/wiki/Modem):
> 
> ================================================================================
> 
> ### List of dialup speeds
> 
> # Note that the values given are maximum values, and actual values may be slower under certain conditions (for example, noisy phone lines).[4] For a complete list see the companion article List of device bandwidths. Connection Bitrate Modem 110 baud 0.1 kbit/s Modem 300 (300 baud) (Bell 103 or V.21) 0.3 kbit/s Modem 1200 (600 baud) (Bell 212A or V.22) 1.2 kbit/s Modem 2400 (600 baud) (V.22bis) 2.4 kbit/s Modem 2400 (1200 baud) (V.26bis) 2.4 kbit/s Modem 4800 (1600 baud) (V.27ter) 4.8 kbit/s Modem 9600 (2400 baud) (V.32) 9.6 kbit/s Modem 14.4 (2400 baud) (V.32bis) 14.4 kbit/s Modem 28.8 (3200 baud) (V.34) 28.8 kbit/s Modem 33.6 (3429 baud) (V.34) 33.6 kbit/s Modem 56k (8000/3429 baud) (V.90) 56.0/33.6 kbit/s Modem 56k (8000/8000 baud) (V.92) 56.0/48.0 kbit/s Bonding Modem (two 56k modems)) (V.92) 112.0/96.0 kbit/s [5] Hardware compression (variable) (V.90/V.42bis) 56.0-220.0 kbit/s Hardware compression (variable) (V.92/V.44) 56.0-320.0 kbit/s Server-side web compression (variable) (Netscape ISP) 100.0-1000.0 kbit/s
> 
> # BP: Entropy is not easy to define. A good discussion is in [http://www4.ncsu.edu/unity/lockers/users/f/felder/public/kenny/papers/entropy.html](http://www4.ncsu.edu/unity/lockers/users/f/felder/public/kenny/papers/entropy.html)Here is a quote:
> 
> _If I were able to measure the complete, microscopic state of the air  
> molecules then I would know all the information there is to know about the  
> macroscopic state. For example, if I knew the position of every molecule in the  
> room I could calculate the average density in any macroscopic region. The  
> reverse is not true, however. If I know the average density of the air in each  
> cubic centimeter that tells me only how many molecules are in each of these  
> regions, but it tells me nothing about where exactly the individual molecules  
> within each such region are. Thus for any particular macrostate there are many  
> possible corresponding microstates. Roughly speaking, entropy is defined for  
> any particular macrostate as the number of corresponding microstates.  
> To recap: The microstate of a system consists of a complete description of the  
> state of every constituent of the system. In the case of the air this means the  
> position and velocity of all the molecules. (Going further to the level of  
> atoms or particles wouldn’t change the arguments here in any important way.)  
> The macrostate of a system consists of a description of a few, macroscopically  
> measurable quantities such as average density and temperature. For any  
> macrostate of the system there are in general many different possible  
> microstates. Roughly speaking, the entropy of a system in a particular  
> macrostate is defined to be the number of possible microstates that the system  
> might be in. (In the appendix I’ll discuss how to make this definition more explicit.)_==================================================================================
> 
> BP:  
> Since the number of possible microstates of the outside world is rather large,  
> about all that we can conclude is that the entropy of any macrostate is  
> infinite.
> 
> RM:
> 
> This is not the way I think perception works. Perception is  
> not a  
> channel that brings a message about the “true” state of the  
> environment into the brain. The “true” state of the environment could  
> be represented as a binary “message” like 1011010. But I don’t think  
> of this as a real message; it is just the state of a set of physical  
> variables. If what is perceived is, say, some linear combination of a  
> subset of the elements of this “message”, then it makes no sense (it  
> seems to me) to ask how much information about the state of the  
> environment is communicated by the perceptual signal. It’s just  
> doesn’t seem like a relevant question.
> 
> BP:  
> This is an important observation. If the taste of lemonade consists of  
> temperature, tartness, sweetness, and other sensations, the perception of  
> lemonade is not about some corresponding entity in the outside world. There is  
> no “message” about lemonade coming into the brain. Instead, the  
> perception is to the individual components as density is to the positions of  
> individual molecules. The world consists of microstates; perceptions are the  
> macrostates. One level of perception consists of the microstates of the next  
> level up, which relatively speaking consists of the macrostates. Obviously we  
> can’t go from the macrostates to the microstates, although by considering many  
> different macrostates derived from the same microstates outside, we can begin  
> to build a fuzzy picture of the microstates. And the control process, plus  
> reorgnaization, allows us to manipulate microstates in such a way as to give us  
> control of the macrostates without even knowing what the microstates are.
> 
> Well, that is metaphysics, too: it’s one level talking about other levels. I  
> think the most important point you make here is that we can’t consider  
> perceptual signals as “messages” passed to higher levels. The higher  
> levels take whatever inputs they want from the existing lower levels; they  
> create a new set of perceptions from some set of lower-perceptions, with the  
> “taking” being done by the recieving entity, not by some transmitting  
> entity. The lower levels do not decide what they want to say to the higher  
> levels. Yet the higher levels can tell the lower ones what they want to receive  
> from them.
> 
> Best,
> 
> Bill P.

---

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**Author:** ![Bill\_Powers1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/8e7dd6/32.png) [@Bill\_Powers1](http://discourse.iapct.org/u/Bill_Powers1)\
**Post date:** [April 17, 2009, 11:28pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/2 "2009-04-17T23:28:18Z")

</div>

[From Bill Powers (2009.04.17.1624 MDT)]

> AD: Dear Bill,
> 
> With great interest I am trying to catch up on these interesting  
> posts.
> 
> Can you please elaborate a bit more on what you say about cybernetics and  
> Ashby in the following part:

> > BP earlier:I saw this happen in  
> > cybernetics, with Ashby’s “Law of Requisite  
> > Variety.”

BP: I assume this is the passage that caught your eye. I was referring to  
the concept of requisite variety as a kind of measure of variability,  
which is related to uncertainty and the concept of information. Ashby  
maintained that the actions of a control system had to have at least as  
much “variety” as the environment to be controlled.

For the save of PCTers not acquainted with this law, here is a bit from

[  
http://en.wikipedia.org/wiki/Variety\_(cybernetics](http://en.wikipedia.org/wiki/Variety_(cybernetics))

> **···**
>
> At 09:45 PM 4/17/2009 +0200, Arthur Dykstra wrote:
> 
> ============================================================================
> 
> ### **The Law of Requisite Variety**
> 
> # If a system is to be stable the number of states of its control mechanism must be greater than or equal to the number of states in the system being controlled. Ashby states the Law as “only variety can destroy variety”[4]. He sees this as aiding the study of problems in biology and a “wealth of possible applications” . He sees his approach as introductory to Shannon Information Theory (1948) which deals with the case of “incessant fluctuations” or noise. The Requisite Variety condition can be seen as a simple statement of a necessary dynamic equilibrium condition in information theory terms c.f. Newton’s third law, Le Chatelier’s principle. Later, in 1970, Conant working with Ashby produced the Good Regulator theorem [5] which required autonomous systems to acquire an internal model of their environment to persist and achieve stability or dynamic equilibrium.
> 
> The idea in that last unfortunate paragraph has steered lots of people  
> into a blind alley.  
> While the law of requisite variety may in fact be true (I wouldn’t know),  
> it’s not sufficient for designing a stable control system, or even a  
> control system that controls. All it really says is that the control  
> system must have the same number of output degrees of freedom as the  
> environment to be controlled. It doesn’t even say they have to be the  
> same degrees of freedom! If the outputs of the control system can apply  
> forces to an object’s position in x, y, and z, and the environment  
> controlled can vary in angles rho, theta, and tau, the number of degrees  
> of freedom of the output is the same as the number of degrees of freedom  
> of the environment, but nothing in the environment will be controlled.  
> Ashby referred to matching the number of “states,” but that  
> means only that each output variable must have at least the same number  
> of discriminable states or magnitudes as the corresponding environmental  
> variable. It still doesn’t say the variables have to correspond in any  
> particular way. If you match only the number of states, the chances of  
> creating even a closed loop are pretty small.  
> Even if all those conditions are met, you still don’t have a control  
> system, much less a stable one. To have a control system, you need to  
> give it the ability to sense the state of the environment in each  
> independent dimension (a subject Ashby totally ignored, apparently), to  
> compare what is sensed with a reference condition, and to generate an  
> output that affects _the same variable that is sensed_ in such a way  
> that the difference between the sensory signal and the reference  
> magnitude is minimized and kept small despite unpredictable disturbances  
> of the environment. The law of requisite variety says nothing helpful  
> about those fundamental requirements. It’s one of those generalizations  
> that, while quite possibly true, is useless for designing or  
> understanding anything.
> 
> In “Design for a Brain” Ashby abandoned the best approach to  
> control theory and switched to a very bad version in which the variables  
> are discrete and enumerable. I think this is what gave rise to the  
> current fad called “modern control theory,” and that the  
> underlying principle he and his followers adopted is completely  
> impractical as a model of living systems (or the systems they control).  
> Ashby thought you could design a system so it would compute how much  
> action and what kind of action were needed to produce a desired result,  
> and then execute the action and get the result. He thought this would  
> provide instantaneous and perfect control, as compared to error-driven  
> systems which could not even in principle achieve EXACTLY zero error.  
> That is, of course, not physically possible for any real system no matter  
> how it’s designed, including the systems Ashby imagined. But systems of  
> the kind Ashby finally chose are illusory, because simply expressing the  
> variable magnitudes as small whole numbers by no means shows that any  
> real system would behave in that sort of infinitely precise instantaneous  
> steps. 2 - 2 is zero in the world of integers, but in the real world it’s  
> anywhere between -0.4999… and +0.4999… . When you add 1 to 1 in the  
> real world, you get something close to 2, but not right away. Everything  
> in the real world takes time to happen, and Ashby chose an approach in  
> which that simple fact is ignored.
> 
> All this is a great pity since Ashby was one of my early objects of  
> admiration, and it took me quite a while to realize that his acquaintance  
> with real control systems was rather sparse. I think he just had the bad  
> luck to have an insight that led him straight off the productive path on  
> which he started. If he had been any kind of engineer he might have  
> realized his mistake, but he was a psychiatrist and more of a hobbyist  
> than an engineer. And like many in cybernetics in the early days, he was  
> engaged in that very popular contest of seeing who could come up with the  
> most general possible statements. What a coup, to boil it all down to  
> “Only variety can destroy variety”! Wow! And what a bummer to  
> be topped by Boltzman, who shortened that terse generalization by two  
> whole words. saying “Variety absorbs variety.”
> 
> Not my kind of game.
> 
> Best,
> 
> Bill P.

---

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**Author:** ![Bill\_Powers1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/8e7dd6/32.png) [@Bill\_Powers1](http://discourse.iapct.org/u/Bill_Powers1)\
**Post date:** [April 17, 2009, 11:33pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/3 "2009-04-17T23:33:47Z")

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[From Bill Powers (2009.04.17.1731 MDT)]

Replying again to Arthur Dykstra 09:45 PM 4/17/2009 +0200:

Sorry, it wasn't Boltzman who said variety absorbs variety. It was Stafford Beer.

Best,

Bill P.

---

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**Author:** ![Arthur\_Dijkstra1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/a/b9bd4f/32.png) [@Arthur\_Dijkstra1](http://discourse.iapct.org/u/Arthur_Dijkstra1)\
**Post date:** [April 18, 2009, 9:21am UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/4 "2009-04-18T09:21:18Z")

</div>

Thanks Bill,

You enriched my view on Ashby’s law of req var. I have  
never found such a critical view on his work, did I look in the wrong place ?

May I ask you your view on Ashby’s concept of an  
ultrastable system which must keep the essential variables within physiological  
limits (in chapter 7 of Design for a brain) ?

I am trying to use these concepts including the Viable System  
Model for the description of a safety management system so your (and others of  
course) comments are very welcome.

Regards,

Arthur

Systems Group Network (CSGnet) [[mailto:CSGNET@LISTSERV.ILLINOIS.EDU](mailto:CSGNET@LISTSERV.ILLINOIS.EDU)] **Namens** Bill  
Powers  
**Verzonden:** zaterdag 18 april 2009 1:28  
“information”)

[From Bill Powers  
(2009.04.17.1624 MDT)]

AD: Dear Bill,  
With great interest I am trying to catch up on these interesting posts.  
Can you please elaborate a bit more on what you say about cybernetics and Ashby  
in the following part:

> BP earlier:I saw this happen in cybernetics, with Ashby’s  
> “Law of Requisite Variety.”

BP: I assume this is the passage that caught your eye. I was referring to the  
concept of requisite variety as a kind of measure of variability, which is  
related to uncertainty and the concept of information. Ashby maintained that  
the actions of a control system had to have at least as much  
“variety” as the environment to be controlled.

For the save of PCTers not acquainted with this law, here is a bit from  
[http://en.wikipedia.org/wiki/Variety\_(cybernetics](http://en.wikipedia.org/wiki/Variety_(cybernetics))

> **···**
>
> **Van:** Control  
> **Aan:** CSGNET@LISTSERV.ILLINOIS.EDU  
> **Onderwerp:** Re: What happened to cybernetics (was RE: The reality of  
> At 09:45 PM 4/17/2009 +0200, Arthur Dykstra wrote:
> 
> ============================================================================
> 
> ### The Law of Requisite Variety
> 
> # If a system is to be stable the number of states of its control mechanism must be greater than or equal to the number of states in the system being controlled. Ashby states the Law as “only variety can destroy variety”[4]. He sees this as aiding the study of problems in biology and a “wealth of possible applications” . He sees his approach as introductory to Shannon Information Theory (1948) which deals with the case of “incessant fluctuations” or noise. The Requisite Variety condition can be seen as a simple statement of a necessary dynamic equilibrium condition in information theory terms c.f. Newton’s third law, Le Chatelier’s principle. Later, in 1970, Conant working with Ashby produced the Good Regulator theorem [5] which required autonomous systems to acquire an internal model of their environment to persist and achieve stability or dynamic equilibrium.
> 
> The idea in that last unfortunate paragraph has steered lots of people into a  
> blind alley.  
> While the law of requisite variety may in fact be true (I wouldn’t know), it’s  
> not sufficient for designing a stable control system, or even a control system  
> that controls. All it really says is that the control system must have the same  
> number of output degrees of freedom as the environment to be controlled. It  
> doesn’t even say they have to be the same degrees of freedom! If the outputs of  
> the control system can apply forces to an object’s position in x, y, and z, and  
> the environment controlled can vary in angles rho, theta, and tau, the number  
> of degrees of freedom of the output is the same as the number of degrees of  
> freedom of the environment, but nothing in the environment will be controlled.  
> Ashby referred to matching the number of “states,” but that means  
> only that each output variable must have at least the same number of  
> discriminable states or magnitudes as the corresponding environmental variable.  
> It still doesn’t say the variables have to correspond in any particular way. If  
> you match only the number of states, the chances of creating even a closed loop  
> are pretty small.  
> Even if all those conditions are met, you still don’t have a control system,  
> much less a stable one. To have a control system, you need to give it the  
> ability to sense the state of the environment in each independent dimension (a  
> subject Ashby totally ignored, apparently), to compare what is sensed with a  
> reference condition, and to generate an output that affects _the same  
> variable that is sensed_ in such a way that the difference between the  
> sensory signal and the reference magnitude is minimized and kept small despite  
> unpredictable disturbances of the environment. The law of requisite variety  
> says nothing helpful about those fundamental requirements. It’s one of those  
> generalizations that, while quite possibly true, is useless for designing or  
> understanding anything.
> 
> In “Design for a Brain” Ashby abandoned the best approach to control  
> theory and switched to a very bad version in which the variables are discrete  
> and enumerable. I think this is what gave rise to the current fad called  
> “modern control theory,” and that the underlying principle he and his  
> followers adopted is completely impractical as a model of living systems (or  
> the systems they control). Ashby thought you could design a system so it would  
> compute how much action and what kind of action were needed to produce a  
> desired result, and then execute the action and get the result. He thought this  
> would provide instantaneous and perfect control, as compared to error-driven  
> systems which could not even in principle achieve EXACTLY zero error. That is,  
> of course, not physically possible for any real system no matter how it’s  
> designed, including the systems Ashby imagined. But systems of the kind Ashby  
> finally chose are illusory, because simply expressing the variable magnitudes  
> as small whole numbers by no means shows that any real system would behave in  
> that sort of infinitely precise instantaneous steps. 2 - 2 is zero in the world  
> of integers, but in the real world it’s anywhere between -0.4999… and  
> +0.4999… . When you add 1 to 1 in the real world, you get something close to  
> 2, but not right away. Everything in the real world takes time to happen, and  
> Ashby chose an approach in which that simple fact is ignored.
> 
> All this is a great pity since Ashby was one of my early objects of admiration,  
> and it took me quite a while to realize that his acquaintance with real control  
> systems was rather sparse. I think he just had the bad luck to have an insight  
> that led him straight off the productive path on which he started. If he had  
> been any kind of engineer he might have realized his mistake, but he was a  
> psychiatrist and more of a hobbyist than an engineer. And like many in  
> cybernetics in the early days, he was engaged in that very popular contest of  
> seeing who could come up with the most general possible statements. What a  
> coup, to boil it all down to “Only variety can destroy variety”! Wow!  
> And what a bummer to be topped by Boltzman, who shortened that terse  
> generalization by two whole words. saying “Variety absorbs variety.”
> 
> Not my kind of game.
> 
> Best,
> 
> Bill P.

---

<div class="post-metadata">

**Author:** ![BUSINESS\_GAVIN\_HERMA](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/2acd7d/32.png) [@BUSINESS\_GAVIN\_HERMA](http://discourse.iapct.org/u/BUSINESS_GAVIN_HERMA)\
**Post date:** [April 18, 2009, 11:46am UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/5 "2009-04-18T11:46:57Z")

</div>

(Gavin Ritz, 2009.04.18.23.31NZT)

Arthur

You are going up a cul de sac with VSM.

Let me suggest you map out your entire organizational  
business processes with the accountabilities “in what is called the swim lane  
method” use Visio for this. BPM (business process mapping) at least with  
give you a pictorial view of your organisations processes with the accountabilities  
attached to the processes.

This will at least give you a situational analysis  
of what you have and who is accountable, then you can fit your safely processes  
over that. Ie your “ends”.

So you have at least a picture of your  
situation and how you want it to look (ends), you can then devise your “means”.

I suggest in your means (you may have new  
roles) you specify those accountabilities for each role, ie its authorities. Called  
a TIRR Task Initiating Role Relationships (ie for cross functional roles). A safety  
officer may be able to tell the production manager to do something, stop something  
or whatever authority.

Good luck

Regards

Gavin

Thanks Bill,

You enriched my view on Ashby’s law of req var. I have  
never found such a critical view on his work, did I look in the wrong place ?

May I ask you your view on Ashby’s concept of an ultrastable  
system which must keep the essential variables within physiological limits (in  
chapter 7 of Design for a brain) ?

I am trying to use these concepts including the Viable System  
Model for the description of a safety management system so your (and others of  
course) comments are very welcome.

Regards,

Arthur

**Van:**  
Control Systems Group Network (CSGnet) [[mailto:CSGNET@LISTSERV.ILLINOIS.EDU](mailto:CSGNET@LISTSERV.ILLINOIS.EDU)] **Namens** Bill Powers  
**Verzonden:** zaterdag 18 april 2009  
1:28  
cybernetics (was RE: The reality of “information”)

[From Bill Powers (2009.04.17.1624 MDT)]

AD: Dear Bill,

With great interest I am trying to catch up on these interesting posts.

Can you please elaborate a bit more on what you say about cybernetics and Ashby  
in the following part:

> BP earlier:I  
> saw this happen in cybernetics, with Ashby’s “Law of Requisite  
> Variety.”

BP: I assume this is the passage that caught your eye. I was referring to the  
concept of requisite variety as a kind of measure of variability, which is  
related to uncertainty and the concept of information. Ashby maintained that  
the actions of a control system had to have at least as much  
“variety” as the environment to be controlled.

For the save of PCTers not acquainted with this law, here is a bit from

[http://en.wikipedia.org/wiki/Variety\_(cybernetics](http://en.wikipedia.org/wiki/Variety_(cybernetics))

> **···**
>
> **Aan:** CSGNET@LISTSERV.ILLINOIS.EDU  
> **Onderwerp:** Re: What happened to  
> At 09:45 PM 4/17/2009 +0200, Arthur Dykstra wrote:
> 
> ============================================================================
> 
> ### **The Law of Requisite Variety**
> 
> # If a system is to be stable the number of states of its control mechanism must be greater than or equal to the number of states in the system being controlled. Ashby states the Law as “only variety can destroy variety”[4]. He sees this as aiding the study of problems in biology and a “wealth of possible applications” . He sees his approach as introductory to Shannon Information Theory (1948) which deals with the case of “incessant fluctuations” or noise. The Requisite Variety condition can be seen as a simple statement of a necessary dynamic equilibrium condition in information theory terms c.f. Newton’s third law, Le Chatelier’s principle. Later, in 1970, Conant working with Ashby produced the Good Regulator theorem [5] which required autonomous systems to acquire an internal model of their environment to persist and achieve stability or dynamic equilibrium.
> 
> The idea in that last unfortunate paragraph has steered lots of people into a  
> blind alley.  
> While the law of requisite variety may in fact be true (I wouldn’t know), it’s  
> not sufficient for designing a stable control system, or even a control system  
> that controls. All it really says is that the control system must have the same  
> number of output degrees of freedom as the environment to be controlled. It  
> doesn’t even say they have to be the same degrees of freedom! If the outputs of  
> the control system can apply forces to an object’s position in x, y, and z, and  
> the environment controlled can vary in angles rho, theta, and tau, the number  
> of degrees of freedom of the output is the same as the number of degrees of  
> freedom of the environment, but nothing in the environment will be controlled.  
> Ashby referred to matching the number of “states,” but that means  
> only that each output variable must have at least the same number of  
> discriminable states or magnitudes as the corresponding environmental variable.  
> It still doesn’t say the variables have to correspond in any particular way. If  
> you match only the number of states, the chances of creating even a closed loop  
> are pretty small.  
> Even if all those conditions are met, you still don’t have a control system,  
> much less a stable one. To have a control system, you need to give it the  
> ability to sense the state of the environment in each independent dimension (a  
> subject Ashby totally ignored, apparently), to compare what is sensed with a  
> reference condition, and to generate an output that affects _the same variable that is sensed_ in such a  
> way that the difference between the sensory signal and the reference magnitude  
> is minimized and kept small despite unpredictable disturbances of the  
> environment. The law of requisite variety says nothing helpful about those  
> fundamental requirements. It’s one of those generalizations that, while quite  
> possibly true, is useless for designing or understanding anything.
> 
> In “Design for a Brain” Ashby abandoned the best approach to control  
> theory and switched to a very bad version in which the variables are discrete  
> and enumerable. I think this is what gave rise to the current fad called  
> “modern control theory,” and that the underlying principle he and his  
> followers adopted is completely impractical as a model of living systems (or  
> the systems they control). Ashby thought you could design a system so it would  
> compute how much action and what kind of action were needed to produce a  
> desired result, and then execute the action and get the result. He thought this  
> would provide instantaneous and perfect control, as compared to error-driven  
> systems which could not even in principle achieve EXACTLY zero error. That is,  
> of course, not physically possible for any real system no matter how it’s  
> designed, including the systems Ashby imagined. But systems of the kind Ashby  
> finally chose are illusory, because simply expressing the variable magnitudes  
> as small whole numbers by no means shows that any real system would behave in  
> that sort of infinitely precise instantaneous steps. 2 - 2 is zero in the world  
> of integers, but in the real world it’s anywhere between -0.4999… and  
> +0.4999… . When you add 1 to 1 in the real world, you get something close to  
> 2, but not right away. Everything in the real world takes time to happen, and  
> Ashby chose an approach in which that simple fact is ignored.
> 
> All this is a great pity since Ashby was one of my early objects of admiration,  
> and it took me quite a while to realize that his acquaintance with real control  
> systems was rather sparse. I think he just had the bad luck to have an insight  
> that led him straight off the productive path on which he started. If he had  
> been any kind of engineer he might have realized his mistake, but he was a  
> psychiatrist and more of a hobbyist than an engineer. And like many in  
> cybernetics in the early days, he was engaged in that very popular contest of  
> seeing who could come up with the most general possible statements. What a  
> coup, to boil it all down to “Only variety can destroy variety”! Wow!  
> And what a bummer to be topped by Boltzman, who shortened that terse  
> generalization by two whole words. saying “Variety absorbs variety.”
> 
> Not my kind of game.
> 
> Best,
> 
> Bill P.

---

<div class="post-metadata">

**Author:** ![Bill\_Powers1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/8e7dd6/32.png) [@Bill\_Powers1](http://discourse.iapct.org/u/Bill_Powers1)\
**Post date:** [April 18, 2009, 3:51pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/6 "2009-04-18T15:51:08Z")

</div>

[From Bill Powers (2009.04.18.0809 MDT)]

> Thanks Bill,
> 
> You enriched my view on Ashby�s law of req var. I have never found such a  
> critical view on his work, did I look in the wrong place  
> ?

Lots of people think Ashby’s work, particularly his later work on  
cybernetics, was wonderful. I went down a different path, developed the  
model that he abandoned, and concluded that he made the wrong choice,  
with what I see as unfortunate consequences for those who put much time  
and effort into following his reasoning.

When I first read Design for a Brain, I thought it was wonderful, too.  
The parts of the book in which negative feedback control was explained in  
relation to human behavior got me started on the path to PCT. I just sort  
of ignored the rest, which made little sense to me. But who knows? Maybe  
I’m the one who made the mistake. Others will have to decide that for  
themselves.

> May I ask you your view on  
> Ashby�s concept of an ultrastable system which must keep the essential  
> variables within physiological limits (in chapter 7 of Design for a  
> brain) ?

That was a brilliant idea and I adopted it in the mid-1950s; it solved a  
lot of problems about learning and adaptation. Later on, I read Daniel  
Koshland’s book on bacterial chemotaxis where a principle is laid out  
that shows how systematic learning can result from random variations ( a  
super-efficient form of natural selection), and put that together with  
Ashby’s idea to form what I now call “E-coli reorganization  
theory.” In my new book there are some respectably complex  
simulations of control systems getting themselves organized by this  
method.

> I am trying to use these  
> concepts including the Viable System Model for the description of a  
> safety management system so your (and others of course) comments are very  
> welcome.

Tell me something. Suppose you design a system for managing safety, and  
it doesn’t work as well as you want. You hire a consultant, and he  
reports to you that your system’s output actions don’t have enough  
variety to match the variety of the environment you’re trying to control.  
What does that tell you about how to make the system work  
better?

I have a strong impression that starting with Ashby, a lot of people  
found the logic of negative feedback control baffling, while the logic of  
the kind of organization Ashby proposed made good common sense. Ashby  
himself got the idea of negative feedback control pretty well, but only  
superficially; he never really explored systems of that sort, and drew  
some conclusions about them that were just wrong enough to throw him off  
the track.

One very wrong conclusion was that negative feedback control systems,  
being error-driven, necessarily controlled imperfectly, nowhere near as  
well as a system that could compute exactly the required action and carry  
it out. What he didn’t realize, simply because of limited knowledge about  
real error-driven control systems, is that the “imperfections”  
in control of this sort can be as small as one part per million, or even  
much less. I once built one that positioned a 300-pound carriage on its  
ways over a 20-inch range with an accuracy of one tenth of a wavelength  
of red light. Actually, most real control systems can achieve accuracies  
of a percent or two, which is plenty close for most of the control tasks  
anyone performs – how close to the center of your lane do you really  
have to keep your car? One inch would be better than necessary, and  
that’s about one percent of the lane width.

Also, not being an engineer, Ashby seemed to be under the impression that  
just because you can compute the required action perfectly (given a big  
enough and fast enough computer), a real system could produce it  
perfectly (and instantly). In fact, one reason that negative feedback  
control systems were invented was that computed-output systems are very  
crude in their actual performance, since they have no way to correct for  
unanticipated disturbances, changes in friction or other disturbances, or  
changes in the efficiency of their own output mechanisms. Negative  
feedback control systems are naturally able to maintain the same output  
results even in the face of novel disturbances and even if their output  
machinery loses a significant part of its effectiveness. That is why they  
work so much better, and are so much simpler and faster, than systems  
that work by computing what they need to do and then doing it.

The logic of the system Ashby finally settled on is appealing, especially  
to engineers. You analyze the system to see what the effect of some  
control input is on the system to be controlled. Given a sufficiently  
accurate model of the controlled “plant”, you can see exactly  
how any given control output, including magnitudes of input and rates of  
change and so on, affects the variables you want to control. Equations  
can be found that describe the causes and effects between the control  
input and the final effect. This part of the process is called  
“system identification.” The success of control will depend  
crucially on the accuracy of the equations.

Next, you decide what values of the variables in the plant you want to  
control, and how you want them to behave – the “trajectories”  
of the variables. Given the desired values and the trajectories, you can  
then use the inverses of the equations to calculate the values of the  
control variables that will generate the desired end-points (inverse  
kinematics) and the ways in which the control variables must change  
through time to generate the desired trajectories (inverse dynamics).  
Once you have completed those inverse calculations, all that remains is  
to manipulate the control variables in the way you have deduced, and the  
plant will then generate the desired results.

This is a rather complex procedure and involves some challenging  
mathematical computations. It requires extensive knowlege about the  
physics (and chemistry in some cases) of the plant. The conversion of the  
control variable into exactly the computed values of effects on the plant  
requires highly precise machinery (often the engineers have to cheat and  
use a negative feedback control system to generate precise enough  
effects). And since the actual effects will change from time to time  
because of disturbances and changes in the environment and wear and tear  
on the plant, a large fast computer is needed to update the model and  
repetitively recompute all the inverses.

However, computers are small and fast now, and machinery can be made  
quite precise, so there is no basic reason why this sort of system can’t  
be made to work. And it has the great advantage that it is understandable  
without adding anything much to 19th-century engineering knowlege. Anyone  
can understand how it works, even if not everyone could design such a  
system. The basic idea is very simple: you figure out what you have to do  
to get the result you want, and then you do it. Compute and  
execute.

Apparently, once a person has this architecture firmly in mind, nothing  
can dislodge it. And a negative feedback control system makes no sense at  
all in comparison.

The first thing that makes no sense is that the “control  
variable” is in the wrong place, and it’s called the  
“controlled variable.” Instead of being the variable that is  
used to do the controlling, it’s the variable that gets  
controlled.

The second puzzle is that the controller contains no model of the plant.  
The designer may have a model in mind – probably does – but when the  
controller is in operation it does not do any inverse calculations at all  
and makes no use of knowlege about how the plant works.

The third weird fact is that the controller can respond to unanticipated  
disturbances by adjusting its effects on the plant so as to counteract  
those disturbances – which it does not need to sense. And more than  
that, if a motor starts to lose torque because of age, or a load is  
placed on the plant, or the quality of fuel used in the plant changes,  
the action of the control system automatically changes in just the way  
needed to cancel 90, or 99, or if you wish 99.9% of the effects of these  
changes.

But the worst thing is that this controller mangles cause and effect. The  
variable that is controlled is also the variable that causes the action  
that is doing the controlling of that variable. Causation runs in a  
circle. Every effect in the control loop is part of its own cause. Normal  
19th-century thinking simply can’t handle this. Many cyberneticists speak  
with delight about “circular causation,” but few of them have  
any idea of what that really implies, or how it works.

To understand exactly what a negative feedback control system is and what  
it can do, you have to go farther into the details and properties of  
these systems than Ashby went. That’s what I did. I didn’t learn  
everything that control engineers learn, but I found shortcuts and built  
enough control systems to get a pretty clear idea of their properties.  
That’s how I came to realize that Ashby had bet on the wrong horse. When  
I finally came to that conclusion, I didn’t much like it. I felt  
disloyal.

“Requisite variety” is the kind of idea that people get when  
they don’t really understand a system but want to say something useful  
about it. That’s the impression I got about Ashby. He was looking for  
generalizations that seemed true and that didn’t require getting into  
details about control systems.

He would have done better to focus on the details before  
generalizing.

Best,

Bill P.

> **···**
>
> At 11:21 AM 4/18/2009 +0200, Arthur Dykstra wrote:
> 
> > Regards,  
> > Arthur
> > 
> > **Van:** Control Systems Group Network (CSGnet)  
> > [  
> > [mailto:CSGNET@LISTSERV.ILLINOIS.EDU](mailto:CSGNET@LISTSERV.ILLINOIS.EDU)] **Namens** Bill Powers  
> > **Verzonden:** zaterdag 18 april 2009 1:28  
> > **Aan:** CSGNET@LISTSERV.ILLINOIS.EDU  
> > **Onderwerp:** Re: What happened to cybernetics (was RE: The reality  
> > of “information”)
> > 
> > [From Bill Powers (2009.04.17.1624 MDT)]
> > 
> > At 09:45 PM 4/17/2009 +0200, Arthur Dykstra wrote:
> > 
> > AD: Dear Bill,
> > 
> > With great interest I am trying to catch up on these interesting  
> > posts.
> > 
> > Can you please elaborate a bit more on what you say about cybernetics and  
> > Ashby in the following part:
> > 
> > BP earlier:I saw this happen in cybernetics, with Ashby’s “Law  
> > of Requisite Variety.”
> > 
> > BP: I assume this is the passage that caught your eye. I was referring to  
> > the concept of requisite variety as a kind of measure of variability,  
> > which is related to uncertainty and the concept of information. Ashby  
> > maintained that the actions of a control system had to have at least as  
> > much “variety” as the environment to be controlled.
> > 
> > For the save of PCTers not acquainted with this law, here is a bit from
> > 
> > [  
> > http://en.wikipedia.org/wiki/Variety\_(cybernetics](http://en.wikipedia.org/wiki/Variety_(cybernetics))
> > 
> > ============================================================================
> > 
> > ### **The Law of Requisite Variety**
> > 
> > If a system is to be stable the number of states of its control mechanism  
> > must be greater than or equal to the number of states in the system being  
> > controlled. Ashby states the Law as “only variety can destroy  
> > variety”[4]. He sees this as aiding the study of problems in biology  
> > and a “wealth of possible applications” . He sees his approach  
> > as introductory to Shannon Information Theory (1948) which deals with the  
> > case of “incessant fluctuations” or noise. The Requisite  
> > Variety condition can be seen as a simple statement of a necessary  
> > dynamic equilibrium condition in information theory terms c.f. Newton’s  
> > third law, Le Chatelier’s principle.
> > 
> > Later, in 1970, Conant working with Ashby produced the Good Regulator  
> > theorem [5] which required autonomous systems to acquire an internal  
> > model of their environment to persist and achieve stability or dynamic  
> > equilibrium.
> > 
> > =============================================================================
> > 
> > The idea in that last unfortunate paragraph has steered lots of people  
> > into a blind alley.
> > 
> > While the law of requisite variety may in fact be true (I wouldn’t know),  
> > it’s not sufficient for designing a stable control system, or even a  
> > control system that controls. All it really says is that the control  
> > system must have the same number of output degrees of freedom as the  
> > environment to be controlled. It doesn’t even say they have to be the  
> > same degrees of freedom! If the outputs of the control system can apply  
> > forces to an object’s position in x, y, and z, and the environment  
> > controlled can vary in angles rho, theta, and tau, the number of degrees  
> > of freedom of the output is the same as the number of degrees of freedom  
> > of the environment, but nothing in the environment will be controlled.  
> > Ashby referred to matching the number of “states,” but that  
> > means only that each output variable must have at least the same number  
> > of discriminable states or magnitudes as the corresponding environmental  
> > variable. It still doesn’t say the variables have to correspond in any  
> > particular way. If you match only the number of states, the chances of  
> > creating even a closed loop are pretty small.
> > 
> > Even if all those conditions are met, you still don’t have a control  
> > system, much less a stable one. To have a control system, you need to  
> > give it the ability to sense the state of the environment in each  
> > independent dimension (a subject Ashby totally ignored, apparently), to  
> > compare what is sensed with a reference condition, and to generate an  
> > output that affects the same variable that is sensed in such a way  
> > that the difference between the sensory signal and the reference  
> > magnitude is minimized and kept small despite unpredictable disturbances  
> > of the environment. The law of requisite variety says nothing helpful  
> > about those fundamental requirements. It’s one of those generalizations  
> > that, while quite possibly true, is useless for designing or  
> > understanding anything.
> > 
> > In “Design for a Brain” Ashby abandoned the best approach to  
> > control theory and switched to a very bad version in which the variables  
> > are discrete and enumerable. I think this is what gave rise to the  
> > current fad called “modern control theory,” and that the  
> > underlying principle he and his followers adopted is completely  
> > impractical as a model of living systems (or the systems they control).  
> > Ashby thought you could design a system so it would compute how much  
> > action and what kind of action were needed to produce a desired result,  
> > and then execute the action and get the result. He thought this would  
> > provide instantaneous and perfect control, as compared to error-driven  
> > systems which could not even in principle achieve EXACTLY zero error.  
> > That is, of course, not physically possible for any real system no matter  
> > how it’s designed, including the systems Ashby imagined. But systems of  
> > the kind Ashby finally chose are illusory, because simply expressing the  
> > variable magnitudes as small whole numbers by no means shows that any  
> > real system would behave in that sort of infinitely precise instantaneous  
> > steps. 2 - 2 is zero in the world of integers, but in the real world it’s  
> > anywhere between -0.4999… and +0.4999… . When you add 1 to 1 in the  
> > real world, you get something close to 2, but not right away. Everything  
> > in the real world takes time to happen, and Ashby chose an approach in  
> > which that simple fact is ignored.
> > 
> > All this is a great pity since Ashby was one of my early objects of  
> > admiration, and it took me quite a while to realize that his acquaintance  
> > with real control systems was rather sparse. I think he just had the bad  
> > luck to have an insight that led him straight off the productive path on  
> > which he started. If he had been any kind of engineer he might have  
> > realized his mistake, but he was a psychiatrist and more of a hobbyist  
> > than an engineer. And like many in cybernetics in the early days, he was  
> > engaged in that very popular contest of seeing who could come up with the  
> > most general possible statements. What a coup, to boil it all down to  
> > “Only variety can destroy variety”! Wow! And what a bummer to  
> > be topped by Boltzman, who shortened that terse generalization by two  
> > whole words. saying “Variety absorbs variety.”
> > 
> > Not my kind of game.
> > 
> > Best,
> > 
> > Bill P.
> > 
> > No virus found in this incoming message.
> > 
> > Checked by AVG -  
> > [www.avg.com](http://www.avg.com/)
> > 
> > Version: 8.0.238 / Virus Database: 270.11.58/2062 - Release Date:  
> > 04/16/09 08:12:00

---

<div class="post-metadata">

**Author:** ![Fred\_Nickols1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/f/ad7895/32.png) [@Fred\_Nickols1](http://discourse.iapct.org/u/Fred_Nickols1)\
**Post date:** [April 18, 2009, 4:59pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/7 "2009-04-18T16:59:08Z")

</div>

[From Fred Nickols (2009.04.18.0958 MST)]

Boy! Bill's post below is a keeper. I don't know anyone who has dared challenge Ashby. Way to go, Bill!

> **···**
>
> --  
> Regards,
> 
> Fred Nickols  
> Managing Partner  
> Distance Consulting, LLC  
> nickols@att.net  
> www.nickols.us
> 
> "Assistance at A Distance"  
> &nbsp;&nbsp;  
> -------------- Original message ----------------------  
> From: Bill Powers \<powers\_w@FRONTIER.NET\>
> 
> >

---

<div class="post-metadata">

**Author:** ![Arthur\_Dijkstra](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/a/f9ae1b/32.png) [@Arthur\_Dijkstra](http://discourse.iapct.org/u/Arthur_Dijkstra)\
**Post date:** [April 18, 2009, 8:40pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/8 "2009-04-18T20:40:54Z")

</div>

Dear Bill:

AD:

I am trying to use these concepts including the Viable System  
Model for the description of a safety management system so your (and others of  
course) comments are very welcome.

BP:  
Tell me something. Suppose you design a system for managing safety, and it  
doesn’t work as well as you want. You hire a consultant, and he reports to you  
that your system’s output actions don’t have enough variety to match the  
variety of the environment you’re trying to control. What does that tell you  
about how to make the system work better?

AD:

That would be a very underspecified report and no help at all. I  
would ask him on what specific dimensions the system lacks variety. Then I  
could think of measures to amplify that specific system variety, or how to  
attenuate the environmental variety impacting the system, to recreate  
homeostasis. Every recursion of the system (VSM language) must have req var and  
this can be achieved by variety amplification and attenuation. I guess you are  
probably more familiar with these concepts than I am.

I am an airline pilot and the idea of as a crew matching the  
environmental variety to maintain essential variables (e.g. speed, altitude,  
direction) within limits feels as a useful model.

Thanks,

Arthur

Systems Group Network (CSGnet) [[mailto:CSGNET@LISTSERV.ILLINOIS.EDU](mailto:CSGNET@LISTSERV.ILLINOIS.EDU)] **Namens** Bill  
Powers  
**Verzonden:** zaterdag 18 april 2009 17:51  
“information”)

[From Bill Powers (2009.04.18.0809 MDT)]

> **···**
>
> **Van:** Control  
> **Aan:** CSGNET@LISTSERV.ILLINOIS.EDU  
> **Onderwerp:** Re: What happened to cybernetics (was RE: The reality of
> 
> At 11:21 AM 4/18/2009 +0200, Arthur Dykstra wrote:
> 
> Thanks Bill,  
> You enriched my view on Ashby’s law of req var. I have never found such a  
> critical view on his work, did I look in the wrong place ?
> 
> Lots of people think Ashby’s work, particularly his later work on cybernetics,  
> was wonderful. I went down a different path, developed the model that he  
> abandoned, and concluded that he made the wrong choice, with what I see as  
> unfortunate consequences for those who put much time and effort into following  
> his reasoning.
> 
> When I first read Design for a Brain, I thought it was wonderful, too. The  
> parts of the book in which negative feedback control was explained in relation  
> to human behavior got me started on the path to PCT. I just sort of ignored the  
> rest, which made little sense to me. But who knows? Maybe I’m the one who made  
> the mistake. Others will have to decide that for themselves.
> 
> May I ask you your view on Ashby’s concept of an  
> ultrastable system which must keep the essential variables within physiological  
> limits (in chapter 7 of Design for a brain) ?
> 
> That was a brilliant idea and I adopted it in the mid-1950s; it solved a lot of  
> problems about learning and adaptation. Later on, I read Daniel Koshland’s book  
> on bacterial chemotaxis where a principle is laid out that shows how systematic  
> learning can result from random variations ( a super-efficient form of natural  
> selection), and put that together with Ashby’s idea to form what I now call  
> “E-coli reorganization theory.” In my new book there are some  
> respectably complex simulations of control systems getting themselves organized  
> by this method.
> 
> I am trying to use these concepts including the Viable  
> System Model for the description of a safety management system so your (and  
> others of course) comments are very welcome.
> 
> Tell me something. Suppose you design a system for managing safety, and it  
> doesn’t work as well as you want. You hire a consultant, and he reports to you  
> that your system’s output actions don’t have enough variety to match the  
> variety of the environment you’re trying to control. What does that tell you  
> about how to make the system work better?
> 
> I have a strong impression that starting with Ashby, a lot of people found the  
> logic of negative feedback control baffling, while the logic of the kind of  
> organization Ashby proposed made good common sense. Ashby himself got the idea  
> of negative feedback control pretty well, but only superficially; he never  
> really explored systems of that sort, and drew some conclusions about them that  
> were just wrong enough to throw him off the track.
> 
> One very wrong conclusion was that negative feedback control systems, being  
> error-driven, necessarily controlled imperfectly, nowhere near as well as a  
> system that could compute exactly the required action and carry it out. What he  
> didn’t realize, simply because of limited knowledge about real error-driven  
> control systems, is that the “imperfections” in control of this sort  
> can be as small as one part per million, or even much less. I once built one  
> that positioned a 300-pound carriage on its ways over a 20-inch range with an  
> accuracy of one tenth of a wavelength of red light. Actually, most real control  
> systems can achieve accuracies of a percent or two, which is plenty close for  
> most of the control tasks anyone performs – how close to the center of your  
> lane do you really have to keep your car? One inch would be better than  
> necessary, and that’s about one percent of the lane width.
> 
> Also, not being an engineer, Ashby seemed to be under the impression that just  
> because you can compute the required action perfectly (given a big enough and  
> fast enough computer), a real system could produce it perfectly (and  
> instantly). In fact, one reason that negative feedback control systems were  
> invented was that computed-output systems are very crude in their actual  
> performance, since they have no way to correct for unanticipated disturbances,  
> changes in friction or other disturbances, or changes in the efficiency of  
> their own output mechanisms. Negative feedback control systems are naturally  
> able to maintain the same output results even in the face of novel disturbances  
> and even if their output machinery loses a significant part of its  
> effectiveness. That is why they work so much better, and are so much simpler  
> and faster, than systems that work by computing what they need to do and then  
> doing it.
> 
> The logic of the system Ashby finally settled on is appealing, especially to  
> engineers. You analyze the system to see what the effect of some control input  
> is on the system to be controlled. Given a sufficiently accurate model of the  
> controlled “plant”, you can see exactly how any given control output,  
> including magnitudes of input and rates of change and so on, affects the variables  
> you want to control. Equations can be found that describe the causes and  
> effects between the control input and the final effect. This part of the  
> process is called “system identification.” The success of control  
> will depend crucially on the accuracy of the equations.
> 
> Next, you decide what values of the variables in the plant you want to control,  
> and how you want them to behave – the “trajectories” of the  
> variables. Given the desired values and the trajectories, you can then use the  
> inverses of the equations to calculate the values of the control variables that  
> will generate the desired end-points (inverse kinematics) and the ways in which  
> the control variables must change through time to generate the desired  
> trajectories (inverse dynamics). Once you have completed those inverse  
> calculations, all that remains is to manipulate the control variables in the  
> way you have deduced, and the plant will then generate the desired results.
> 
> This is a rather complex procedure and involves some challenging mathematical  
> computations. It requires extensive knowlege about the physics (and chemistry  
> in some cases) of the plant. The conversion of the control variable into  
> exactly the computed values of effects on the plant requires highly precise  
> machinery (often the engineers have to cheat and use a negative feedback  
> control system to generate precise enough effects). And since the actual  
> effects will change from time to time because of disturbances and changes in  
> the environment and wear and tear on the plant, a large fast computer is needed  
> to update the model and repetitively recompute all the inverses.
> 
> However, computers are small and fast now, and machinery can be made quite  
> precise, so there is no basic reason why this sort of system can’t be made to  
> work. And it has the great advantage that it is understandable without adding  
> anything much to 19th-century engineering knowlege. Anyone can understand how  
> it works, even if not everyone could design such a system. The basic idea is  
> very simple: you figure out what you have to do to get the result you want, and  
> then you do it. Compute and execute.
> 
> Apparently, once a person has this architecture firmly in mind, nothing can  
> dislodge it. And a negative feedback control system makes no sense at all in  
> comparison.
> 
> The first thing that makes no sense is that the “control variable” is  
> in the wrong place, and it’s called the “controlled variable.”  
> Instead of being the variable that is used to do the controlling, it’s the  
> variable that gets controlled.
> 
> The second puzzle is that the controller contains no model of the plant. The  
> designer may have a model in mind – probably does – but when the controller  
> is in operation it does not do any inverse calculations at all and makes no use  
> of knowlege about how the plant works.
> 
> The third weird fact is that the controller can respond to unanticipated  
> disturbances by adjusting its effects on the plant so as to counteract those  
> disturbances – which it does not need to sense. And more than that, if a motor  
> starts to lose torque because of age, or a load is placed on the plant, or the  
> quality of fuel used in the plant changes, the action of the control system  
> automatically changes in just the way needed to cancel 90, or 99, or if you  
> wish 99.9% of the effects of these changes.
> 
> But the worst thing is that this controller mangles cause and effect. The  
> variable that is controlled is also the variable that causes the action that is  
> doing the controlling of that variable. Causation runs in a circle. Every  
> effect in the control loop is part of its own cause. Normal 19th-century  
> thinking simply can’t handle this. Many cyberneticists speak with delight about  
> “circular causation,” but few of them have any idea of what that  
> really implies, or how it works.
> 
> To understand exactly what a negative feedback control system is and what it  
> can do, you have to go farther into the details and properties of these systems  
> than Ashby went. That’s what I did. I didn’t learn everything that control  
> engineers learn, but I found shortcuts and built enough control systems to get  
> a pretty clear idea of their properties. That’s how I came to realize that  
> Ashby had bet on the wrong horse. When I finally came to that conclusion, I  
> didn’t much like it. I felt disloyal.
> 
> “Requisite variety” is the kind of idea that people get when they  
> don’t really understand a system but want to say something useful about it.  
> That’s the impression I got about Ashby. He was looking for generalizations  
> that seemed true and that didn’t require getting into details about control  
> systems.
> 
> He would have done better to focus on the details before generalizing.
> 
> Best,
> 
> Bill P.
> 
> Regards,  
> Arthur
> 
> **Van:** Control Systems Group Network (CSGnet) [[mailto:CSGNET@LISTSERV.ILLINOIS.EDU](mailto:CSGNET@LISTSERV.ILLINOIS.EDU)]  
> **Namens** Bill Powers  
> **Verzonden:** zaterdag 18 april 2009 1:28  
> **Aan:** CSGNET@LISTSERV.ILLINOIS.EDU  
> **Onderwerp:** Re: What happened to cybernetics (was RE: The reality of  
> “information”)
> 
> [From Bill Powers (2009.04.17.1624 MDT)]
> 
> At 09:45 PM 4/17/2009 +0200, Arthur Dykstra wrote:
> 
> AD: Dear Bill,  
> With great interest I am trying to catch up on these interesting posts.  
> Can you please elaborate a bit more on what you say about cybernetics and Ashby  
> in the following part:
> 
> BP earlier:I saw this happen in cybernetics, with  
> Ashby’s “Law of Requisite Variety.”
> 
> BP: I assume this is the passage that caught your eye. I was referring to the  
> concept of requisite variety as a kind of measure of variability, which is  
> related to uncertainty and the concept of information. Ashby maintained that  
> the actions of a control system had to have at least as much  
> “variety” as the environment to be controlled.
> 
> For the save of PCTers not acquainted with this law, here is a bit from  
> [http://en.wikipedia.org/wiki/Variety\_(cybernetics](http://en.wikipedia.org/wiki/Variety_(cybernetics))
> 
> ============================================================================
> 
> ### The Law of Requisite Variety
> 
> If a system is to be stable the number of states of its control mechanism must  
> be greater than or equal to the number of states in the system being  
> controlled. Ashby states the Law as “only variety can destroy  
> variety”[4]. He sees this as aiding the study of problems in biology and a  
> “wealth of possible applications” . He sees his approach as introductory  
> to Shannon Information Theory (1948) which deals with the case of  
> “incessant fluctuations” or noise. The Requisite Variety condition  
> can be seen as a simple statement of a necessary dynamic equilibrium condition  
> in information theory terms c.f. Newton’s third law, Le Chatelier’s principle.
> 
> # Later, in 1970, Conant working with Ashby produced the Good Regulator theorem [5] which required autonomous systems to acquire an internal model of their environment to persist and achieve stability or dynamic equilibrium.
> 
> The idea in that last unfortunate paragraph has steered lots of people into a  
> blind alley.
> 
> While the law of requisite variety may in fact be true (I wouldn’t know), it’s  
> not sufficient for designing a stable control system, or even a control system  
> that controls. All it really says is that the control system must have the same  
> number of output degrees of freedom as the environment to be controlled. It  
> doesn’t even say they have to be the same degrees of freedom! If the outputs of  
> the control system can apply forces to an object’s position in x, y, and z, and  
> the environment controlled can vary in angles rho, theta, and tau, the number  
> of degrees of freedom of the output is the same as the number of degrees of  
> freedom of the environment, but nothing in the environment will be controlled.  
> Ashby referred to matching the number of “states,” but that means  
> only that each output variable must have at least the same number of discriminable  
> states or magnitudes as the corresponding environmental variable. It still  
> doesn’t say the variables have to correspond in any particular way. If you  
> match only the number of states, the chances of creating even a closed loop are  
> pretty small.
> 
> Even if all those conditions are met, you still don’t have a control system,  
> much less a stable one. To have a control system, you need to give it the  
> ability to sense the state of the environment in each independent dimension (a  
> subject Ashby totally ignored, apparently), to compare what is sensed with a  
> reference condition, and to generate an output that affects the same variable  
> that is sensed in such a way that the difference between the sensory signal and  
> the reference magnitude is minimized and kept small despite unpredictable  
> disturbances of the environment. The law of requisite variety says nothing  
> helpful about those fundamental requirements. It’s one of those generalizations  
> that, while quite possibly true, is useless for designing or understanding  
> anything.
> 
> In “Design for a Brain” Ashby abandoned the best approach to control  
> theory and switched to a very bad version in which the variables are discrete  
> and enumerable. I think this is what gave rise to the current fad called  
> “modern control theory,” and that the underlying principle he and his  
> followers adopted is completely impractical as a model of living systems (or  
> the systems they control). Ashby thought you could design a system so it would  
> compute how much action and what kind of action were needed to produce a  
> desired result, and then execute the action and get the result. He thought this  
> would provide instantaneous and perfect control, as compared to error-driven  
> systems which could not even in principle achieve EXACTLY zero error. That is, of  
> course, not physically possible for any real system no matter how it’s  
> designed, including the systems Ashby imagined. But systems of the kind Ashby  
> finally chose are illusory, because simply expressing the variable magnitudes  
> as small whole numbers by no means shows that any real system would behave in  
> that sort of infinitely precise instantaneous steps. 2 - 2 is zero in the world  
> of integers, but in the real world it’s anywhere between -0.4999… and  
> +0.4999… . When you add 1 to 1 in the real world, you get something close to  
> 2, but not right away. Everything in the real world takes time to happen, and  
> Ashby chose an approach in which that simple fact is ignored.
> 
> All this is a great pity since Ashby was one of my early objects of admiration,  
> and it took me quite a while to realize that his acquaintance with real control  
> systems was rather sparse. I think he just had the bad luck to have an insight  
> that led him straight off the productive path on which he started. If he had  
> been any kind of engineer he might have realized his mistake, but he was a  
> psychiatrist and more of a hobbyist than an engineer. And like many in  
> cybernetics in the early days, he was engaged in that very popular contest of  
> seeing who could come up with the most general possible statements. What a  
> coup, to boil it all down to “Only variety can destroy variety”! Wow!  
> And what a bummer to be topped by Boltzman, who shortened that terse  
> generalization by two whole words. saying “Variety absorbs variety.”
> 
> Not my kind of game.
> 
> Best,
> 
> Bill P.
> 
> No virus found in this incoming message.  
> Checked by AVG - [www.avg.com](http://www.avg.com/)  
> Version: 8.0.238 / Virus Database: 270.11.58/2062 - Release Date: 04/16/09  
> 08:12:00

---

<div class="post-metadata">

**Author:** ![Bill\_Powers1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/8e7dd6/32.png) [@Bill\_Powers1](http://discourse.iapct.org/u/Bill_Powers1)\
**Post date:** [April 19, 2009, 1:43pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/9 "2009-04-19T13:43:08Z")

</div>

[From Bill Powers (2009.04.19.0-712 MDT)]

> AD:  
> I am trying to use these concepts including the Viable System Model for the description of a safety management system so your (and others of course) comments are very welcome.  
> BP:  
> Tell me something. Suppose you design a system for managing safety, and it doesn't work as well as you want. You hire a consultant, and he reports to you that your system's output actions don't have enough variety to match the variety of the environment you're trying to control. What does that tell you about how to make the system work better?
> 
> AD:  
> That would be a very underspecified report and no help at all. I would ask him on what specific dimensions the system lacks variety. Then I could think of measures to amplify that specific system variety, or how to attenuate the environmental variety impacting the system, to recreate homeostasis.

BP: Fine, but you need to know something about control systems to do all that successfully. Behind what you call "amplifying variety" is something much more specific: identifying all the variables that need to be controlled, and providing some means of affecting each of those variables. That's all that "requisite variety" means. And you need to develop some way to monitor the results to see if you're getting the result you want or something else. That's the rest of the control system. In fact, to find those variables and figure out how to control them doesn't require thinking about variety at all, though there's nothing to stop you from doing so if you wish, after you've solved all the real problems. As you say, variety is a rather underspecified concept.

Just trying to eliminate disturbances won't "recreate homeostasis," either. You can't eliminate all disturbances, especially in airplanes. What you need is an actual homeostatic system or as we call them here, a control system. And it had better not be just a homeostatic system; what you need is a RHEOstatic system (as Mrosovski calls them), better known as a hierachy of control systems in PCT circles. You wouldn't want an autopilot that could only keep you, homeostatically, at one heading, speed, and altitude. First you need to be able to maintain each important variable in a specific state, and then you need to be able to vary the state in which each variable is being controlled, so the lower-order control systems can be put into use by more general, higher-order control systems. The means of varying the homeostatic state is what we call a reference signal, and that is how higher-order systems can change what lower systems are doing without coming into conflict with them. The higher systems tell the lower ones what state to maintain, and leave the actual maintaining up to them. It's like the pilot entering the desired heading, airspeed, and altitude into the autopilot. He doesn't tell the autopilot how to manipulate the ailerons, elevators, and throttle -- he just tells it what result to achieve. If he tried to operate the controls he would be fighting the autopilot. There's a reason for making the autopilot cut out if the pilot starts using the controls himself. In living systems, that sort of micromanagement isn't allowed.

> Every recursion of the system (VSM language) must have req var and this can be achieved by variety amplification and attenuation. I guess you are probably more familiar with these concepts than I am.

No, actually I don't use those terms at all. What I do in designing control systems or models of them could probably be classified in such abstract terms, but it's not the abstract terms that do the heavy lifting. I design control systems and make them work, and never once even think about variety. So far that hasn't proved to be a serious omission.

> I am an airline pilot and the idea of a a crew matching the environmental variety to maintain essential variables (e.g. speed, altitude, direction) within limits feels as a useful model.

Perhaps that works for you, but I also recommend seeing how PCT looks to you as a model of those processes. You're making me wonder if we don't need yet another book, something like "How to use PCT in the real world."

Best,

Bill P.

> **···**
>
> At 10:40 PM 4/18/2009 +0200, Arthur Dykstra wrote:

---

<div class="post-metadata">

**Author:** ![Arthur\_Dijkstra](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/a/f9ae1b/32.png) [@Arthur\_Dijkstra](http://discourse.iapct.org/u/Arthur_Dijkstra)\
**Post date:** [April 19, 2009, 2:27pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/10 "2009-04-19T14:27:25Z")

</div>

Dear Bill,  
Thanks for your response. I agree that the operationalisation of all these  
concepts is a critical and difficult task. I just bought all your books and  
will explore how PCT and VSM can maybe be supplemental.  
To what extend can the PCT concept be transferred to an organisational  
environment like an airline ? Has the PCT concept explicitly been used to  
model the control structure of a company ? It would be helpful to read about  
this.  
Thanks for any suggestions or links.  
Arthur

-----Oorspronkelijk bericht-----  
[mailto:CSGNET@LISTSERV.ILLINOIS.EDU] Namens Bill Powers  
Verzonden: zondag 19 april 2009 15:43  
"information")

[From Bill Powers (2009.04.19.0-712 MDT)]

> AD:  
> I am trying to use these concepts including the Viable System Model  
> for the description of a safety management system so your (and  
> others of course) comments are very welcome.  
> BP:  
> Tell me something. Suppose you design a system for managing safety,  
> and it doesn't work as well as you want. You hire a consultant, and  
> he reports to you that your system's output actions don't have  
> enough variety to match the variety of the environment you're trying  
> to control. What does that tell you about how to make the system work

better?

> AD:  
> That would be a very underspecified report and no help at all. I  
> would ask him on what specific dimensions the system lacks variety.  
> Then I could think of measures to amplify that specific system  
> variety, or how to attenuate the environmental variety impacting the  
> system, to recreate homeostasis.

BP: Fine, but you need to know something about control systems to do  
all that successfully. Behind what you call "amplifying variety" is  
something much more specific: identifying all the variables that need  
to be controlled, and providing some means of affecting each of those  
variables. That's all that "requisite variety" means. And you need to  
develop some way to monitor the results to see if you're getting the  
result you want or something else. That's the rest of the control  
system. In fact, to find those variables and figure out how to  
control them doesn't require thinking about variety at all, though  
there's nothing to stop you from doing so if you wish, after you've  
solved all the real problems. As you say, variety is a rather  
underspecified concept.

Just trying to eliminate disturbances won't "recreate homeostasis,"  
either. You can't eliminate all disturbances, especially in  
airplanes. What you need is an actual homeostatic system or as we  
call them here, a control system. And it had better not be just a  
homeostatic system; what you need is a RHEOstatic system (as  
Mrosovski calls them), better known as a hierachy of control systems  
in PCT circles. You wouldn't want an autopilot that could only keep  
you, homeostatically, at one heading, speed, and altitude. First you  
need to be able to maintain each important variable in a specific  
state, and then you need to be able to vary the state in which each  
variable is being controlled, so the lower-order control systems can  
be put into use by more general, higher-order control systems. The  
means of varying the homeostatic state is what we call a reference  
signal, and that is how higher-order systems can change what lower  
systems are doing without coming into conflict with them. The higher  
systems tell the lower ones what state to maintain, and leave the  
actual maintaining up to them. It's like the pilot entering the  
desired heading, airspeed, and altitude into the autopilot. He  
doesn't tell the autopilot how to manipulate the ailerons, elevators,  
and throttle -- he just tells it what result to achieve. If he tried  
to operate the controls he would be fighting the autopilot. There's a  
reason for making the autopilot cut out if the pilot starts using the  
controls himself. In living systems, that sort of micromanagement  
isn't allowed.

> Every recursion of the system (VSM language) must have req var and  
> this can be achieved by variety amplification and attenuation. I  
> guess you are probably more familiar with these concepts than I am.

No, actually I don't use those terms at all. What I do in designing  
control systems or models of them could probably be classified in  
such abstract terms, but it's not the abstract terms that do the  
heavy lifting. I design control systems and make them work, and never  
once even think about variety. So far that hasn't proved to be a  
serious omission.

> I am an airline pilot and the idea of a a crew matching the  
> environmental variety to maintain essential variables (e.g. speed,  
> altitude, direction) within limits feels as a useful model.

Perhaps that works for you, but I also recommend seeing how PCT looks  
to you as a model of those processes. You're making me wonder if we  
don't need yet another book, something like "How to use PCT in the real  
world."

Best,

Bill P.

> **···**
>
> Van: Control Systems Group Network (CSGnet)  
> Aan: CSGNET@LISTSERV.ILLINOIS.EDU  
> Onderwerp: Re: What happened to cybernetics (was RE: The reality of  
> At 10:40 PM 4/18/2009 +0200, Arthur Dykstra wrote:

---

<div class="post-metadata">

**Author:** ![BUSINESS\_GAVIN\_HERMA](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/2acd7d/32.png) [@BUSINESS\_GAVIN\_HERMA](http://discourse.iapct.org/u/BUSINESS_GAVIN_HERMA)\
**Post date:** [April 19, 2009, 11:00pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/11 "2009-04-19T23:00:31Z")

</div>

[From Bill Powers (2009.04.19.0-712 MDT)]

(Gavin Ritz 2009.04.20.10.58NZT)

BP says" "Perhaps that works for you, but I also recommend seeing how PCT  
looks to you as a model of those processes. You're making me wonder if we  
don't need yet another book, something like "How to use PCT in the real  
world."

GR says: I would buy this book.

---

<div class="post-metadata">

**Author:** ![Fred\_Nickols1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/f/ad7895/32.png) [@Fred\_Nickols1](http://discourse.iapct.org/u/Fred_Nickols1)\
**Post date:** [April 19, 2009, 11:07pm UTC](http://discourse.iapct.org/t/what-happened-to-cybernetics-was-re-the-reality-of-information/12291/12 "2009-04-19T23:07:03Z")

</div>

[From Fred Nickols (2009.04.19.1606 MST)]  
&nbsp;&nbsp;

> From: Gavin Ritz \<garritz@XTRA.CO.NZ\>
> 
> [From Bill Powers (2009.04.19.0-712 MDT)]
> 
> (Gavin Ritz 2009.04.20.10.58NZT)
> 
> BP says" "Perhaps that works for you, but I also recommend seeing how PCT  
> looks to you as a model of those processes. You're making me wonder if we  
> don't need yet another book, something like "How to use PCT in the real  
> world."
> 
> GR says: I would buy this book.

FN says, "Me, too."

Regards,

Fred Nickols  
nickols@att.net