[Humanist] 31.346 different from the sum of its parts
Humanist Discussion Group
willard.mccarty at mccarty.org.uk
Sun Oct 8 08:32:34 CEST 2017
Humanist Discussion Group, Vol. 31, No. 346.
Department of Digital Humanities, King's College London
Submit to: humanist at lists.digitalhumanities.org
Date: Sat, 7 Oct 2017 21:04:55 +0200
From: Tim Smithers <tim.smithers at cantab.net>
Subject: Re: 31.339 different from the sum of its parts
In-Reply-To: <be023080-c0d7-84c5-aea9-516383989187 at mccarty.org.uk>
"If we put into parallel a biological organism such as
ourselves and a computing machine, which rewrites its own
code depending on events at a higher level, even exterior to
the machine, where is the difference?"
This is a tough question, and I wouldn't claim I'm qualified
to answer it. Others have attempted to, however. Maturana
and Varela's Autopoiesis is, for example, an attempt to
distinguish between living systems and other kinds of
(non-living) systems. It figured prominently in the early
years of Artificial Life.
Maturana and Varela (M&V) explain that ...
"An autopoietic machine is a machine organized (defined as a
unity) as a network of processes of production
(transformation and destruction) of components which: (i)
through their interactions and transformations continuously
regenerate and realize the network of processes (relations)
that produced them; and (ii) constitute it (the machine) as
a concrete unity in space in which they (the components)
exist by specifying the topological domain of its
realization as such a network." (Ref , p 78)
And argue that living systems are autopoietic systems, saying
"What is distinctive about them [living systems] ... is
that their organization is such that their only product is
themselves, with no separation between producer and product.
The being and doing of an autopoieic unity are inseparable,
and this is their specific mode of organization." (Ref 
They contrast autopoietic systems with allopoietic systems,
Allopoiesis is the process whereby a system produces
something other than the system itself.
Computer systems don't produce themselves, they are designed
and built to produce other things. They are allopoietic
systems, like all other Human made systems (so far).
Thus, according to M&V, we see the difference you ask about in
the way Humans and Computers are organised, and in what they
produce. Self-changing, or rewriting code, are not things
that necessarily makes them different or the same.
Since we're talking about Computers, here's a little more M&V
that I think further illustrates the difference.
"It is interesting to note that the operational closure of
the nervous system tells us that it does not operate
according to either of the two extremes: it is neither
representational nor solipsistic. ... In other words, the
nervous system does snot ''pick up information'' from the
environment, as we often hear. On the contrary, it brings
forth a world by specifying what patterns of the environment
are perturbations and what changes trigger them in the
organism. The popular metaphor of calling the brain an
''information-processing device'' is not only ambiguous but
patently wrong." (Ref , p 169)
There are, and have been, other attempts to answer your
question, or that can be used to try to. One that contrasts
with M&V's, by presenting ideas that do not so clearly
separate us, humans, from the kinds of computer systems we
build and use, is Robert Rosen's Anticipatory Systems theory
. Rosen, a mathematical biologist, argues that we are
model making and using systems, and argues against the
Cybernetic view of systems, including living systems, as being
hierarchies of feedback systems, a la William Powers , for
example. [Rosen, by the way, presents what is for me one of
the best definitions of the modelling relation. Chapter 3, p
I like M&V's analysis and way of understanding the kinds of
systems we are, as living systems -- autopoietic -- and the
kinds of system computers are -- allopoietic. I think M&V
help to show us how to look for the differences too, by
carefully building up from well founded basic notions that
afford understandings of biological realities, rather than
trying to see ourselves and other things in terms of what we
can design and build. Computers only look something like us
because we look upon ourselves and think we see things that
look like computers. It's hard not. Brains were once
described as being like electro-mechanical telephone
exchanges, only smaller (and wetter), until (mainframe)
computers came along, that is. Before that, brains were
thought to be miniature hydraulic systems. I like to imagine
that early hominid tool users and makers (two to three million
years ago) thought that inside their heads must be a community
of tiny stone tool makers and users. How else could they go
about devising the tools they made and used?
 Humberto R Maturana & Francisco J Varela, 1973, 1980.
Autopoiesis and Cognition: the Realization of the Living,
 Humberto R Maturana & Francisco J Varela, 1987. The
Tree of Knowledge, the biological roots of human
understanding, Boston: New Science Library.
 Robert Rosen, 1985. Anticipatory Systems, Oxford:
Pergamon Press Ltd.
 William T Powers, 1973. Behavior: The control of
perception. Chicago: Aldine de Gruyter.
> On 06 Oct 2017, at 08:47, Willard McCarty <willard.mccarty at mccarty.org.uk> wrote:
> However, in response to Tim Smithers' response to me: following Claude Bernard's work, going back to Hippocrates, on the environment within organisms (milieu intérieur), a question. If we put into parallel a biological organism such as ourselves and a computing machine, which rewrites its own code depending on events at a higher level, even exterior to the machine, where is the difference? I'm not saying there isn't any, rather asking for clarity.
> On 06/10/2017 07:16, Humanist Discussion Group wrote:
>> Humanist Discussion Group, Vol. 31, No. 339.
>> Department of Digital Humanities, King's College London
>> Submit to: humanist at lists.digitalhumanities.org
>> Date: Thu, 5 Oct 2017 13:24:15 +0200
>> From: Tim Smithers <tim.smithers at cantab.net>
>> Subject: Re: 31.335 different from the sum of its parts?
>> In-Reply-To: <20171005051657.8F2CC7EC9 at s16382816.onlinehome-server.info>
>> Dear Willard,
>> This may well be a distraction from what you really ask.
>> Machines, including computers, are, I think, best understood
>> as level hierarchies, and not as ecosystems. Complicated
>> machines, like computers, are designed and built this way.
>> Here ...
>> "... A level consists of a medium that is to be processed,
>> components that provide primitive processing, laws of
>> composition that permit components to be assembled into
>> systems, and laws of behavior that determine how system
>> behavior depends on the component behavior and the structure
>> of the system. ..." (p 95)
>> These words are taken from
>> The Knowledge Level by Allen Newell, 1982
>> PDF available here:
>> This paper is, I think, an example of good writing about how
>> computers work as machines. It is a foundational paper in AI,
>> though it's never been very widely known, let alone well
>> understood in AI.
>> Using his level analysis of the computer as a machine, Newell
>> introduces a new concept of knowledge: as a capacity for
>> rational action. This formed the starting point for work on
>> Knowledge Modelling and Knowledge Management that came out of
>> AI in the 1980s and 1990s. As a concept of knowledge it
>> differs strongly from the classical notion of knowledge as
>> "verifiable true belief," used by others who developed
>> (competing) approaches to Knowledge Management. A similar
>> level-based approach is used to design and building database
>> systems, and David Marr used a level hierarchy closely related
>> to Newell's, as a basis for understanding vision. (A no
>> longer current theory of vision today.)
>> There's no talk of ecosystems here, nor of "the whole is more
>> than the sum of its parts," or even "the whole is different
>> from the sum of its parts." Levels do hide the details and
>> complicatedness of some of the machine functioning, thus
>> allowing us to understand and treat what the machine does, and
>> can be made to do, in ways completely abstracted from these
>> details and complications. This, I would say, is what makes
>> something a machine, and it necessarily involves combining
>> components, components that themselves can properly be
>> considered as machines. Machines are hierarchically composed
>> of machines to make different machines. This is essentially
>> the same story W Brian Athur presents in his book "The Nature
>> of Technology what it is and how it evolves" (2009).
>> An important difference between machines and ecosystems, I
>> think, is that in machines (composed of machines) functional
>> dependency is unidirectional, whereas in ecosystems,
>> functional dependency is often bidirectional. In machines,
>> such as computers, the proper working of a machine (at some
>> level) depends upon the proper working of the machines that
>> compose it, but the working of these component machines do not
>> depended upon the proper working of the machine they compose.
>> Not usually, at least. And if they do, it usually means the
>> machines is badly designed, or that something has gone wrong.
>> The interesting thing about ecosystems is that they are not
>> composed this way. Component parts do inter-depend to work,
>> sometimes as pairs, but also in networks. This is, of course,
>> what makes ecosystems harder to study and understand, and what
>> gives rise to the kinds of complex behaviour sometimes
>> described using phrase like "the whole is more than the sum of
>> its parts."
>> One last thing. The thoroughly confusing effect of this
>> phrase, on our understanding of things like ecosystems, is not
>> "the whole," it's "the sum." The idea that the combining of
>> parts involves some sort of summation notion, even only by
>> analogy, goes against how we see the way the world is put
>> together, when we really look, and come to understand it.
>> Summation is, I would say, completely the wrong notion here.
>> So, it's hardly surprising that we find complexity
>> complicated. Ecosystems display compositions of
>> inter-dependent nonlinear functionality, not summation, which
>> is a linear unidirectional affair.
>> Now. If we network computers together, what do we get?
>> Ecologies? Perhaps? But not ecologies much like we might be
>> ecologies, I'd suggest. Networking computers may give us
>> ecologies of machines. We, like other living things, appear
>> to be ecologies made of ecologies, not ecologies made of
>> machines. It's only if we insist on seeing natural things as
>> machines that ecologies might seem to be made of machines, or,
>> worse, to think that brains are computers.
>> Best regards,
>>> On 05 Oct 2017, at 07:16, Humanist Discussion Group <willard.mccarty at mccarty.org.uk> wrote:
>>> Humanist Discussion Group, Vol. 31, No. 335.
>>> Department of Digital Humanities, King's College London
>>> Submit to: humanist at lists.digitalhumanities.org
>>> Date: Wed, 4 Oct 2017 09:20:20 +0100
>>> From: Willard McCarty <willard.mccarty at mccarty.org.uk>
>>> Subject: the sum of the parts
>>> Robert Jervis, in System Effects: Complexity in Political and Social
>>> Life (Princeton, 1997) and Frank Golley, in The History of the Ecosystem
>>> Concept: More than the Sum of the Parts (Yale, 1993), argue, as Jervis
>>> writes, that "If we are dealing with a system, the whole is different
>>> from, not greater than, the sum of the parts." He cities work across
>>> several disciplines, pointing to biology as the starting point of many
>>> scholars who have reached this conclusion. What about the disciplines of
>>> Our machine, comprised of numerous 'black boxes' whose inner dynamic
>>> workings are in principle unknowable, would seem to me an example worth
>>> our consideration. It was explicitly designed as such an 'ecosystem',
>>> though in the language of human neurophysiology (von Neumann 1945). Its
>>> user-interface is obviously not more than but different from all the
>>> operations which sum to it. (Indeed, from an engineering perspective,
>>> those operations are clearly more than what they sum to.) Golley writes
>>> that "There was an exact moment of birth" for the concept of an
>>> ecosystem, "when the English ecologist Arthur Tansley created the word
>>> and presented it in a technical paper" in 1935. Here's the passage:
>>>> THE ECOSYSTEM
>>>> Clements' earlier term "biome" for the whole complex of organisms
>>>> inhabiting a given region is unobjectionable, and for some purposes
>>>> convenient. But the more fundamental conception is, as it seems to
>>>> me, the whole system (in the sense of physics), including not only
>>>> the organism-complex, but also the whole complex of physical factors
>>>> forming what we call the environment of the biome - the habitat factors
>>>> in the widest sense. Though the organisms may claim our primary
>>>> interest, when we are trying to think fundamentally we cannot
>>>> separate them from their special environment, with which they form
>>>> one physical system.
>>>> It is the systems so formed which, from the point of view of the
>>>> ecologist, are the basic units of nature on the face of the earth....
>>>> These ecosystems, as we may call them, are of the most various kinds
>>>> and sizes.
>>> (Tansley, "The Use and Abuse of Vegetational Concepts and Terms",
>>> Ecology 16.3, p. 299)
>>> There is the historical question when we extend Robin Gandy's
>>> "confluence of ideas in 1936", i.e. "the almost simultaneous appearance
>>> in 1936 of several independent characterizations of the notion of
>>> effective calculability" (in The Universal Turing Machine, ed. Herken),
>>> among which was Turing's, to the systems-thinking of the above. But
>>> there's also the question of computer systems as ecologies
>>> that include and perhaps now come close to defining us.
>>> Who has written along such lines?
>>> Willard McCarty (www.mccarty.org.uk/), Professor emeritus, Department of
>>> Digital Humanities, King's College London; Adjunct Professor, Western
>>> Sydney University and North Carolina State University; Editor,
>>> Interdisciplinary Science Reviews (www.tandfonline.com/loi/yisr20)
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> Willard McCarty (www.mccarty.org.uk/), Professor emeritus, Department of
> Digital Humanities, King's College London; Adjunct Professor, Western
> Sydney University and North Carolina State University; Editor,
> Interdisciplinary Science Reviews (www.tandfonline.com/loi/yisr20)
> Unsubscribe at: http://www.dhhumanist.org/Restricted/listmember_interface.php
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