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| Gibe by Barie Fez-Barringten |
Artificial Intelligence Design Metaphor
[Managing the benefits and risks of architectural
artificial intelligence] (resolution)
by
Barie Fez-Barringten: “A real
architect”:
Florida license #:AR 0012705
www.bariefez-barringten.com
email:bariefezbarringten@gmail.com
Forward:
This is not the script for the movie called “Artificial
Intelligence” about AI Brian Addis (Brian Wilson Aldiss, a British writer,
anthologist, and critic,) says; I found we both agreed that AI, as they call
it, is not going to be achieved by present-day machines. 'Artificial
Intelligence' -- that makes it sound simple, but what you're really talking
about is artificial consciousness,
AC. And I don't think there's any way we can achieve artificial consciousness,
at least until we've understood the sources of our own consciousness. I believe
consciousness is a mind/body creation, literally interwoven with the body and
the body's support systems. Well, you don't get that sort of thing with a
robot."
It is reported that on working with
Stanley Kubrick and
Steven Spielberg on
Artificial Intelligence: AI (2001):] "Kubrick was obsessed by Pinocchio. He wanted David
to become a real boy. In a future world
of runaway global warming and awe-inspiring scientific advances, humans share
every aspect of their lives with sophisticated companion robots called
Mechas. But when an advanced prototype
robot child named David (Haley Joel Osment) is programmed to show unconditional
love, his human family isn't prepared for the consequences. Suddenly, David is a sovereign entity in a
strange and dangerous world. Befriended by a streetwise Mecha (Jude Law), David
embarks on a spectacular quest to discover the startling secret of his own
identity.
As a variation of idolatry, AI suffers from a tendency to
ascribe life to the inanimate ascribing “good” or “bad” characterizations.
Preface:
As I argue the benefits’ and risks’
of architectural axioms I condition one with the other even though the risk to building design application is minimal
and any consequences benign. I present this intertwined argument because such
dangers are currently on the minds of many in the AI community. To talk about
one without consideration of the other might seem presumptuous and naïve.
However, in my opinion as a licensed design professional, the benefits to an AI
user-context would far outweigh the risks. Whatever malfunctions and dangers
would only affect a specific well contained user and be easily controlled.
Worst case would be a cost of time and expense to repair and redo as is the
profession’s current practice.
Relevance:
The
resolution to my claims is that
architectural metaphoric axioms themselves
sufficiently manage the marginal risk [ff] of AI being a potential adversary limiting
the intelligence of machines and explaining the essential difference between
human intelligence and artificial intelligence. In my view architectural AI is best viewed as
a surrogate and not an adversary! While
architectural
metaphoric axioms contribute managing the risk [ff] of AI being a potential
adversary, it is left to society to debate whether machines have a
mind and
consciousness. Within this
context the challenge for AI managers is AI’s capacity to discern metaphors (humans
have the capacity and capability to make use and discern metaphors).
AI challenge is to abridge these architectural
metaphoric axioms into their platform’s programs and systems, when
they do this AI’s and architecture’s mutual
interactions will both be improved by metaphoric axioms and mange risk [ff].
To achieve this
goal I believe the AI community can regulate, legislate, monitor and license AI
and its architectural devices and thus engraft AI with sympathetic human
characteristics and concerns.
Abstract:
As AI and architecture mediate and control their mutual
interactions metaphoric axioms will have cognitive impact on both the
future of architecture and AI because there is common metaphor between natural
(NI) and artificial intelligence (AI). The inference
warrants that for both architectures’ (AI and building) , master builder is an
interdisciplinary, multi-crafted and multi-venue team, They are also both
arts since they wed intentional ideas to
craft and they both
make metaphors, the
commonality to all the arts.
While
“architect” actually means
master builder
and “architecture” the product of the
master
builder, this is historically identified with habitable buildings. The
warrant to the inference of the resolution is that the computer industries (and
virtual designers) have made a metaphor referring to the word “architecture”
with its conceptual design and fundamental operational structures of
computer systems. Already, IT and AI industry metaphorically
compare their sciences and art of selecting and interconnecting hardware
components to create computers that meet functional, performance and cost goals
with the ways and means traditional architects design buildings. There is an
interconectivity between the metaphor of computer’s
instruction set
architecture, or ISA,
machine language (or
assembly language),
Microarchitecture and system design.
Theoretically, I warrant that the
as the body and mind of AI has identified itself with “architecture”
there is an opportunity to use those links to apply and manage risks of AI to
building architecture. However, benign, risks include operating system
downtime, programming errors, inaccuracy in labeling and dimensions, misreading
building codes, local ordinances, misinterpreting FEMA regulations and
potential tampering with building security systems. . Further risks include
erroneous selection of material and building systems that may expose architects
to errors and omissions suits, so many of the general and specific axioms
guidelines can be uploaded into the AI architectural system. So with AI potential risk [ff] what can be the
impact of artificial intelligence on the future of building architecture?
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| Gibe by Barie Fez-Barringten |
Biographical note:
IBM FORTRAN 4
classes at Yale, Program planning for several Silicone Valley data companies
and Gulf Oil Corp computerized Project Management System (PMS) later published
by John Wiley and sons. Columbia University coursework in behavioral psychology
under Ralph Hefferline and others in voice/linguistics, Bachelor’s of Fine Arts
from Pratt Institute and Master of Architecture from Yale University where I
was mentored in metaphors and metaphysics by Dr. Paul Weiss. For research I founded the New York City
not-for–profit corporation called Laboratories for Metaphoric
Environments. In addition to authoring
over fifteen published monographs by learned journals I have spent 20 years in
Saudi Arabia and have written a book containing pen and ink drawings on
perceptions of 72 European cities.
Institutional affiliations:
Global University ;American Institute of
Architects; Florida Licensed Architect; Programming Chairperson for the Gulf
Coast Writers Association; National Council of Architectural Registration
Boards; Al-Umran association of Saudi Arabia, American Society of Interior
Designers; and founding president of Architects International Group of the
Mid-East.
Introduction:
Because artificial
intelligence is inherently axiomatic, interdisciplinary [aa] and metaphoric it
is uniquely suited to combine risk management and building architecture. Metaphoric axioms improve AI’s and
architecture’s interactions by likening it to architecture. As
AI architecture, the “strange” of AI
becomes linked to the “familiar” architecture and the two can be compared: AI
and architecture, they both can benefit from a metaphoric vocabulary. As most AI/IT
activities, they work through digital and mechanical devices, mainframes, hard
drives, processors, motherboards and chips, as well as application software,
firmware,
middleware, (which controls and co-ordinates
distributed systems)
, and system software (such as
operating systems) , which interface with hardware to provide the necessary
services for application software, these are all the body to the brain of
AI. To warrant my claim as other
disciplines these bodies are driven by some form of axioms (structured
vocabulary) however, about AI architectural work, there is presently little in
the way of axioms.
Historically, in
the early eighties, Silicone Valley data companies (I consulted such companies
in Sunnyvale between 1979 and 1981) scoured the market for soft information to
build proposed programs for computer aided design (CAD) intended to be driven
by design professionals to actually lay down graphic images instead of hand drafted
(pencil on paper) drawings. Having put
traditional draftsman out of the loop, and, developed “master specs” for
computerized specifications, the next step is now to reduce the expense of
design personal and extend the design capability and capacity.
Thirty years later
the design industry claims that what can be done for the design of
manufacturing plants, machine parts and assemblies may be applicable to
creating communities, environments, developments and specific buildings.
The resolution’s
presumed context is that it is not just limited to information
technology (IT) but a
presumption of
intelligence assuming
man can make something which can
think for
itself as today’s computer games, medical procedures, aircraft and military
devices The below examples show that when programmed, systems can make
judgments in a strange environment and metaphorically make the strange familiar
(metaphorically) and systematically design buildings. (Where design is intentionally originating
and
developing a plan for a product, structure, system, or component). The
impact of artificial intelligence on the future of architecture: practice,
process and products are that today there are “smart buildings” with internal
mechanical and electrical systems that respond to the specific behavioral
patterns of occupants.
Below you will
find potentials for the use of metaphoric architectural axioms where artificial
intelligence examples have been applied to designing
buildings without necessarily acting as an “architect”, where design is only
one architectural function. No more
than would we have diagnostic equipment and robotics perform sovereign surgery
on a doctor’s patient. Currently all other systems use protocols, parameters
and axiomatic frameworks, axioms and guidelines needed to facilitate artificial
diagnostics, analysis, and design of buildings at one or another level is the impact
of artificial intelligence on the future
of architecture.
To complete the case for the resolution that AI’s and
architecture’s mutual interactions will be improved and managed risks [ff] by
metaphoric axioms I have provided a short summary of the claims and
examples a of the 83 axioms I have authored in another much longer monograph
[T].
Leaving those
details of all the axioms for another essay suffice it to say that these axioms
are essential drivers of AI architectural activities.
As a predicate
this AI system can be used by the architectural profession to expand its use of
metaphors and services to manage the design process by interfacing with
clients, society, culture, contractors and building authorities and finally
selecting the appropriate axioms and managing the overall design process [aa].
These architectural metaphoric axioms will have an impact on the future of AI
and building architecture. Since a host
for the architectural metaphoric axioms is needed I warrant my inference that
even today’s architectural practice has changed, communicating between many disciplines
via the Internet. “The availability of
reliable, high-speed electronic connectivity enabled collaborative design
team’s function irrespective of physical distance. [V] This calls for new type
of design and simulation environment—one that facilitates automated searching
and locating of satisfying and optimizing parts, integration of selected parts
in an assembly, and simulation of the overall design that is distributed over
the Internet”.
An increasing
quantity of building applications of AI work is based on [W] “Building Information Modeling (BIM) generating and managing
building data during its life cycle”.
AI neither
promises uncontrolled sovereign operations, inventions, creativity, and
innovative design but instead it promises to operate within the parameters and
limits designed by man and if it could innovate, invent and create it would
only do so with either specific geometry or geometric axioms. However said,
Science fiction writers extrapolate the potential of AI beings aimed at
ultimately destroying their creators. This metaphor to Frankenstein is to our
culture as intimidating as is other unsavory results of cloning. Examples to the inferences where already
industrial design for automobiles, aircraft and boats use design applications
to meet aerodynamic, seismic, wind, structural loads, etc. These already
account for the strength of materials, if given, or can optimally select
materials based on its library of manufactured products. In addition [U]
virtual building environments (VBE) are now producing graphic scenarios to
estimate, plan, buy and build; already artificial intelligence is having an
impact of on the future of architecture.
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| Gibe by Barie Fez-Barringten |
Examples and concerns applying AI to building design.
Without concerns
for risks the practical and the esoteric applications of AI to the built
environment is often the result of metaphoric inventive processes, shocks and
imaginative invention such as [M]
ANTS which is an innovative example of an AI application to design buildings. “The Autonomic Nanotechnology Swarm (ANTS)
is a generic mission architecture consisting of miniaturized, autonomous,
self-similar, reconfigurable, addressable components forming structures. The
components/structures have wide spatial distribution and multi-level
organization. This ‘swarm’ (metaphor) behavior is inspired (metaphoric
association) by the success of social insect colonies where within their
specialties, individuals outperform generalists and with sufficiently efficient
social interaction and coordination, groups of specialists outperform groups of
generalists. [M] (Multi-disciplinary)
Axiomatically, the type of information that
is preserved in the traditional built environment is organized-complexity:
precisely the type of information that defines living systems themselves. Thus,
the traditional built environment consists of evolved and discovered solutions
(schemata) that make our life easier and more meaningful” [N].
That having been
said as ACTS combines design and
construction “Research in
construction automation at the University of Reading led to the formulation of
a computer-integrated, component-based construction system. [Q}
The Reading Building System was rationalized
for automation following a systematic study of the construction processes
involved in the design and erection of a variety of building types, especially
high-tech offices. Computer-aided design (CAD) packages were written that used
Parts Set components as primitives and that offered flexibility in design that was
so often lacking in earlier approaches to system building. At the same time, a
family of automation aids was developed to manipulate the parts that were
modeled in the CAD
In the Netherlands
[S]
“Artificial Design focuses on the application
in architecture and design of the algorithmic approach to art being developed
at the Institute of Artificial Art
Amsterdam. Once a style has been defined
the tool can suggest any desired
number of alternative designs for a given document. The Department of Artificial Architecture develops programs which generate random
specifications of 3-dimensional objects. Each of these programs employs a
"visual grammar" to define an infinite set of structures, and then
draws random samples from this space”.
“The
science of design usually conceives of AI as a set of tools for structuring the
process, or planning, or optimizing. [R]
This further warrants that “ Rarely does the computer explore a
space of designs, and in doing so, it is generally following a set of precise
rules, so the machine is doing little else than repeating a series of
mechanical steps, faster than a human could. Creativity is usually considered
to lie outside the realm of what computers can do”. Evolutionary Design (ED), the creation of designs by computers using
evolutionary methods is a new research area with an enormous potential”.
To manage some of
the risk [ff] using existing metaphoric
architectural axioms manufactured buildings, pre-engineered steel buildings,
mobile homes, decks, kitchens, lighting, structures which are just some of the
examples of pre-designed programs allows
user to input variables to receive a design result. There are both similarities and differences
between human natural intelligence and artificial intelligence which are
metaphorically associated with the concerns of people and their
aspirations to shape the post-industrial society. Metaphorical fears that
people and not machines shape society adopted from the critics of the
industrial and information revolution. In a way this is risk mitigation by
reducing adopting metaphors that make the strange familiar and limit the
unknowns.
However, on closer
examination, reality and fiction are different since artificial intelligence is
authored by humans (the imagined fear is that what was created by man could
turn against man when the AI capability to design, redesign and rebuild goes
awry). Especially in building design, I argue that since there is a difference
between the imagined, possible the reality of the probable is marginal,
isolated, minuscule and therefore contained.
The challenge to
the AI community is to contain runaway
metaphorical thinking, where the public
looks to close down human capacity for social innovation and sustainability.[5] Military, design, engineering, accounting,
medical, scientific, manufacturing and education are just some of the fields
already augmenting artificial intelligence with human management.
As AI, Metaphor is
one of the tools of a [1] 'knowledge
society' and to 'human-centered'
technologies and systems. One the attributes of anything artificial is that it
is stagnant, engrafted and reflective of its creator, it does not have its own
free will at least not that beyond what has been given by its designers. While humans change and adopt the artificial
remains as it was unless it also has the ability to rebuild, adopt and change.
This scope, range and amplitude of this capacity are likewise conditioned by
its creator. Like a work of architecture, machine, weapons and medical equipment, self analysis, reprogramming and change are
built-in. Dividing the discipline's metaphors between technical [hh] and conceptual can improve AI’s and architecture’s mutual interactions.
The brain can be simulated. Hans Moravec,
Ray Kurzweil and others have argued that it is technologically feasible
to copy the brain directly into hardware and software, and that such a
simulation will be essentially identical to the original.
[K] "The appropriately programmed
computer with the right inputs and outputs would thereby have a mind in exactly
the same sense human beings have minds. Searle counters this assertion with
his
Chinese room argument, which asks us
to look
inside the computer and try to find where the "mind"
might be.
The
resolution to my claims is that AI’s and
architecture’s mutual interactions will be improved by metaphoric axioms is
supported by claims, inferences and warrants as AI’s and architecture’s mutual
interactions will not only manage marginal risks but be improved by metaphoric
axioms which will have an impact on the future of architecture and AI
field.
Philosophers and scientists concerned with ethics, morals
and sociopolitical agreements critically challenge [J] the limits of
intelligent machines
while proponents of
architectural metaphoric axioms recreate the capabilities of the human
mind. These philosophers
and scientists question if there is an essential difference between human
intelligence and artificial intelligence. They wonder can a machine have a
mind and
consciousness. There is already a difference in perception between
scholars and practitioners. Since both humans and machines perceive
their environment and take actions they maximize their chances of success and
manage risks while they likewise wonder if machines have a similar human
capacity and capability to discern metaphors.
“The field
(artificial intelligence) was
founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—can be so
precisely described that it can be simulated by a machine.[2] Can the
artificial find the range of unpredictable, whimsical, and historical stored in
the human be replicated. While for one it may be replicated but what about the
trillions of other possibilities and potentials in humans not inherent in the
artificial, as man, so does AI manage risks. [3]
“Roughly
speaking, AI is the attempt by computer scientists to model or simulate
intelligent behavior on computers” This in and of itself is metaphoric,
where one thing is stated in terms of the other. The intelligent behavior is
the commonplace/commonality to both the human and the machine.
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| Gibe by Barie Fez-Barringten |
We seem to want to
make machines like us because we are the commonality. If we cannot clone
mankind we can clone our body similar to the ancients who strove to be
immortalized and as man so does AI manage risks.
The mind-machine metaphor, central to AI,
appears in jurisprudence as well. Sometimes it is explicit, as in Jerome Frank's
image of the judicial slot machine: Judging is seen as a process wherein cases
are fed into the hopper of the machine, a crank is turned, and justice is
dispensed at the output. [3] The field of artificial intelligence is
interesting to a student of metaphor, because it was explicitly founded upon a
metaphor - several of them, in fact.
In the 1950s, a
group of scientists decided to try to provide the computer with intelligence.
Their goal seemed attainable due to a common metaphorical identification of the
computer with a brain. [4] From their efforts emerged the field of artificial
intelligence, or AI. As I thought about the basic, or root metaphors of AI, I
realized that they took a form resembling a classical syllogism, a mode of argument that forms the core of the body of Western
logical thought. Aristotle defined syllogistic logic, and his formulations were
thought to be the final word in logic; they underwent only minor revisions in
the subsequent 2,200 years: one of the axioms driving the relationship
is that the computer is a brain, the premise in a syllogism containing the minor term, which will form
the subject of the conclusion.
“Thinking is computing, [Y] concluding
that if we provide the computer with sophisticated programs, it will develop a
mind similar to human minds. [4], in
risk free circumstances. Artificial systems and the biological ones are similar
for their dynamicity, because they cope with the new situations in a way that
is controlled and creative at the same time. [H]. In the case of architectural design this can only leads to
safer, healthier and “greener’ buildings.
[5] There is a body of study
comparing AI to metaphors as I did in 1967 comparing architecture to metaphors.
[C]. There is ample discussions on the analogies, symbolisms and metaphors
linking machines and minds, computers and humans , and artificial intelligence
with natural intelligence it is therefore beneficial to apply the science,
claims and axioms about metaphors. [D]. But what about axioms derived by
social, psychological, philosophical, cognitive scientist? In other works [T] I have derived 83 axioms
which I could apply both here have only discussed the ones with major
comparative value. As they did with AI we did with architecture and are using
these axioms and findings to compare human and machines. For example [7] humans
are able to generate metaphors by describing an operation in an unfamiliar way
and thus able to make what was already somewhat known dominant.
The generative metaphor is the name for a
process of symptoms of a particular kind of seeing-as, the “meta-pherein” or
“carrying –over” of frames or perspectives from one domain of experience to
another. This process he calls generative which many years earlier WJ Gordon
called the Metaphoric Way of Knowing
[E] and 2.1 Paul Weiss called “associations” [F]. Both humans and computers can
generate dead metaphors where
one really does not contain any fresh
metaphor insofar as it does not really “get thoughts across”; [8] “language
seems rather to help one person to construct out of his own stock of mental
stuff something like a replica, or copy,
of someone’s else’s thoughts”.
Man’s natural
culture is a product of man-made, unnatural things, that instead of culture
shaping the computer it is the computer (artificial intelligence) that shapes
the culture. At first, culture creates
the machines then the artificial intelligence modifies the culture. Then new
modified culture creates new machines, etc.
[9] The affect of the metaphor on other metaphors with all its links and
consequences is manifest in the conduit [8]
which leads to one after the other and a continuation of the first.
On the one hand AI can result in
prescriptive design vs.
abnormal,
different,
irregular,
occasional,
rare, sometime, and
unusual design solutions with such projects as CFS truss
system[cc], Arup/cultural society[ee]
and emergence [ee].
Emergence
[ee] is an important new concept in artificial intelligence, information
theory, digital technology, economics, climate studies, material science and
biometric engineering. It is a
development which is set to inform not only the construction of buildings, but
also the composition of new materials. As a new science, coupled with material
and technological innovations, it is set to enter architecture into a new phase
of transition including new material processes and technologies that enable the
production of complex architectural forms and effects. Mathematics of emergence underlies advanced
manufacturing processes, how it is incorporated in the design process by
scientists developing new materials, by mass market and niche product
manufacturers, by engineers and by architects.
The new science
demands new strategies for design, strategies that have a remarkable similarity
to the evolutionary design development and optimization processes of nature. It
involves the intersection of a broad scope of disciplines including advanced
structural and biomimetic engineering, the mathematics of morphogenesis and
computer science with particular respect to artificial life and evolutionary computation,
in order to set forth an operative notion of emergence for architectural design [aa] .
Axiom Digest
Within the
parameters of risk management [ff] these axioms are self-evident principles
that can be accepted on face-value as a true basis for argument since they have
already been proven and described by the noted referent for each. Here they are
postulates (or inferences) without their warrants. As such each is noted as to
source and location for reference gleaned from “Metaphor and
Thought” [6] (footnoted as 1._._ throughout).There are additional
references noted below. The footnotes are sub-axioms meant to both support the
axiom while also being useful as an independent principle. The below axioms are
predominantly derived from “Metaphors and
Thought” [6] by Andrew Ortony, earlier
mentoring by Dr. Paul Weiss and are in addition to over forty years of work
about my stasis to architecture as art
being that “architecture as the making
of metaphors” (please see background [C] below after the monograph for
your information).
Axioms are self-evident
principles that I have deduced out of Ortony’s
Metaphor and Thought [6]
and accept as true without proof as the basis for future arguments; a postulates
or inferences including their warrants
(which I have footnoted as 1._._ throughout). These axioms are in themselves
clarification,
enlightenment, and
illumination removing ambiguity where the derivative reference (Ortony)
has many applications. Hopefully, these can be starting points from
which other statements can be logically derived. Unlike
theorems, axioms cannot be derived by principles of
deduction as I wrote:
"The metametaphor
theorem" published by Architectural Scientific Journal, Vol.
No. 8; 1994 Beirut Arab University. [gg] The below axioms define
properties for the domain of a specific theory which eve loved out of
the stasis defending
architecture as an
art and in that sense, a
"postulate” and "assumption" . Thusly, I presume to
axiomatize a system of knowledge to show
that these claims can be derived from a small, well-understood set of sentences
(the axioms).
Furthermore, in
his book titled
The Book of Architecture
Axioms Gavin Terrill wrote:
“Simplify essential complexity; diminish accidental
complexity; You're negotiating more often than you think ;It's never too early to think about performance and
resiliency testing; Fight repetition; Don't Control, but Observe and Architect as Janitor”. In
“Axiomatic design in the customizing home
building industry published by
Engineering, Construction and Architectural
Management; 2002;vol 9; issue 4;page 318-324 Kurt Psilander wrote that “
the developer would
find a tool very useful that systematically and reliably analyses customer
taste in terms of functional requirements (FRs). Such a tool increases the
reliability of the procedure the entrepreneur applies to chisel out a concrete
project description based on a vision of the tastes of a specific group of
customers. It also ensures that future agents do not distort the developer's
specified FRs when design parameters are selected for the realization of the
project. Axiomatic design is one method to support such a procedure. This tool
was developed for the manufacturing industry but is applied here in the housing
sector. Some hypothetical examples are presented”. Aside from
building-architect’s axioms claiming that “form follows function”; “follow
manufacturer’s requirements and local codes and ordinances”, “AIA standards for
professional practice” architectural axioms are few and far between. Each has
been summarized, paraphrased and translated into architectural terms. Because
of the speed and memory capacity it is not far fetched that an AI architectural
system could receive, analyze and match requirements with codes, ordinances and
industry standards which will impact the future of both building and AI architecture.
Compendium of Axioms
The first axiom
permits all the others in that it claims that ideas and concepts are the reality
of what we create. These images are also the commonality linking our impression
with facts on the ground. [10] Novel
images and image metaphors are conceptual and not the works themselves, but
their mental images. “All metaphors are
invariant with respect to their cognitive topology, that is, each metaphorical
mapping preserves image-schema structure:” Likewise when we look at
the geometrical formal parts of an AI architectural metaphor we note those
common elements where fit, coupling and joints occur.
We remember that
which exemplified the analogous match.
This observation of the metaphor finds that the commonality, commonplace
and similarity are the chief focus of the metaphor. Humans and mechanized
readers both may note either the obscure or subtle as the way two horizontal
axes of the land and then a building are wed by their commonality of
horizontality affecting the future of both architectures.
Natural
Intelligence (NI) and AI note the 90 degree angles and shape that slide into
one another. AI and NI and note the way like metals, clips and angles fit; the
way ceiling ducts are made to fit between structures and hung ceiling, etc.
While it is less
possible for AI to spontaneously imagine the way AI could relate the human form
to a building when humans circulate through its halls, rooms and closets its accommodation
to our needs and necessities; to our self preservation and the maintenance of
the building become apparent.
Both can map the
building structure to humans by finding the one commonality amongst all the
others. Very often we will hear someone (user) say this place is” me”. The
common image has been located and the fit made. The way to arrive at generic-level schemes
for some knowledge structure is to extract its image; its image-schematic
structure is the Invariance Principle.
Obviously this is best done by architecture’s human inhabitant; this is called
the Generic’s Specific Structure. It
is an extremely common mechanism for comprehending the general from the
specific. So what you can deduce for part you can assume is true of the whole. The
human architect controls the mechanical and artificial; however, they both must
share their intelligence where the artificial
analyses and presents it findings to man for further action. Whether a
human can preprogram an AI devise to perceive the infinite number of human
“fit” characteristics seems formidable. As today, much depends on the return on
investment and the capacity of creators to program the device, the programmer,
scientist and operator will only do what is efficient and necessary. You may call
it the biggest bang for the buck axiom,
where humans may falter and awake to a new paradigm where AI devices are
designed to always succeed. It is any of
the three levels of [aa] Axioms
contextual forms.
Plausible
accounts [10] rather than
scientific results are why we have conventional metaphors and why conceptual
systems contain a preference for one set of metaphorical mappings over another.
An artificial intelligence establishes its own vocabulary which once
comprehended become the way in which we experience its’ product’s finding. Its
discrepancies and fits seek the first and all the other similar elements while
humans judge consistency, integrity and aesthetics of AI. The two have their respective roles. The human
monitors, manages and controls wile the AI system performs anticipated
intelligent operations leaving the human to find variances and reprogram. In
this way AI in general and the application in particular evolves and impacts
both architectures
Metaphor is the
main mechanism through which humans comprehend abstract concepts and perform
abstract reasoning. Whether it is one or
thousands public cultures is influenced, bound and authenticated by its’
metaphors. Not withstanding “idolatry” the metaphors are the contexts of life’s
dramas and as our physical bodies are read by our neighbors finding evidence
for inferences about social, political and philosophical claims about our
culture and its place in the universe.
For humans much
subject matter, from the most mundane to the most abstruse scientific theories,
can only be comprehended via metaphor However, AI capacity is limited only by
its
microprocessor
chips and RAM. Metaphor is fundamentally conceptual, not
linguistic, in nature.
Human’s free will,
whim, natural functions and being the original indigenous native inhabitants
characterize man over his artificial creations. Left to its own AI would create
a world of possible machine parts, systems and structures well suited for artificial
intelligent life.
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| Gibe by Barie Fez-Barringten |
Metaphorical
language is a surface manifestation of conceptual metaphor.
As language is to speech so is
output to AI where each has a content and inner meaning of the whole as well as
each of its parts. As each word, each attachment, plain, material, structure
had first been conceived to achieve some purpose and fill some need. Hidden
from the reader is the inner psychology, social background, etc of the man when
speaking and the programming deign and contacting process from the reader of a
building metaphor. As in completing an argument the reader perceives the
inferences with its warrants and connects the evidence of the seen to the
claims to make the resolution of the whole, all of which are surmised from the
surface.
Though much of our
conceptual system is metaphorical a significant part of it is non-metaphorical.
Metaphorical understanding is grounded in non-metaphorical understanding. AI is well suited to the architectural science
of the strength of materials, mathematics, structures, indeterminate beams,
truss design, mechanical systems, plumbing systems, electricity, cladding,
finishes, lighting, etc. as are each understood metaphorically and their
precepts applied metaphorically. But often random selections, trials and
feasibility are random and rather in search of the metaphor without knowing
whether it is or is not a metaphor and fit to be part of the metaphor at hand.
AI will not know the relevant commonality. It may select some commonality but
chances are it will be irrelevant and as incongruous as often are language
translations selecting incongruous phrases and usages. It is for such a risk
that human management and monitoring may be required.
On the other hand
we may select one or another based on non-metaphorical, empirical test and
descriptions of properties. We then try to understand the metaphor in the
selection, its commonality, how it contributes to the new application, how it
has properties within itself which are alone strange and unrelated yet when coupled
with the whole or part of the created metaphor contributes to metaphor. Metaphor allows humans to understand a
relatively abstract or inherently unstructured subject matter in terms of a
more concrete or at least more highly structured subject matter. Like the onomatopeics
metaphors mappings of conceptions override the overt spoken and descriptive,
and rely much more on mnemonics (something intended to assist the memory, as a
verse or formula). Peculiar to the human, assistance comes from something much
more primordial (constituting a beginning; giving origin to something derived
or developed; original; elementary: primordial forms of
life) to the person’s or societies experiences. Again, it is for such a
risk that human management and monitoring may be required, an architectural
design may warrant human invasiveness into the process.
However, once completed these become the matrix
(encyclopedic) of schemas (in argument; the warrants {where a warrant is a
license to make an inference and as such must have reader's agreement}
supporting the inferences (mappings) where in the metaphor becomes real).
In this way the reader maps, learns and personalizes the
strange into the realm of the familiar. The reader does so by the myriad of
synaptic connections he is able to apply to that source.
Hence humans translate their conceptions from philosophy,
psychology, sociology, etc into two dimensional scaled drawings and then to
real life full scale multi dimensions convention consisting of conventional
materials, building elements the task of upload axioms to AI would take a
lifetime of dedicated specialist [aa].
Well suited to AI as maps are the result of cartographers
rendering existing into a graphics for reading so is mapping to the reading of
metaphors where the reader renders understanding from one source to another.
Doing so mentally and producing a rendition of understanding (as a pen and ink
of a figure) not as a graphic but a conceptual understanding. The best risk management is when reader sees in a critical way the
existing culling through and encyclopedia of referents to make the true
relationship; the mapping which best renders the reality; the relationship
which informs and clarifies as the map the location, configuration and
characteristic of the reality. As the cartographer seeks lines, symbols and
shadings to articulate the reality so the reader choices of heretofore
unrelated and seemingly unrelated are
found to have and essence common to both the reality and the rendition so that
the metaphor can be repeated becoming the readers new vocabulary . In fact architects do the opposite as graphic
renditions are made of synapses between amorphic and seemingly desperate
information. This relationship between axiom and performance assure for program
conformity and reliability.
Yet the process of mapping is no less intense as architect
review the matrix of conditions, operation , ideal and goals of the thesis to
find similarities and differences , commonalities, and potential for one to
resonate with another to make a “resolution” on the experience of a cognitive
mapping which becomes the metaphor, parte and overwhelming new reality. The new
reality is the target of the source and finally can be read. In the case of the birth of an infant metaphor
readers may find a wide variety of source information which is germane to their
own experience.
Before the public ever sees the constructed metaphor Building
Officials, manufactures, city planners, owners, estimators, general contactors,
specialty contractors, environmentalist, neighbors and community organization
first read the drawings and map their observations to their issues to form a
slanted version of the reality. Human manager can easily monitor this variance
and modify the performance. Their
mappings are based on the warrants which are their licensed to perform. Each
warrant will support a different mapping (inference) and result in its own
metaphor. In effect each will see a kind of reality of the proposed in the
perspective of their peculiar warrant, where license is permission from
authority to do something. It is assumed if one gets permission it has met the
conditions, operations, ideal and goals of the proposed metaphor. As risk is
managed by other professions, operations and systems mapping is critical at
this read to assure that the architect’s rendering of the program is faithful
to the cognitive, lawful, physical and legal realities.
It s like a map
which gets tested by scientist, navigators , pilots and engineers before they
build a craft to use the map, or set out on a journey using the map. Before the
contracts start committing men and material the metaphor must map and be the
metaphor meeting all expectations.
As there is metaphor between natural (NI)
and artificial intelligence (AI) in
cognitive linguistics, conceptual
metaphor, or cognitive metaphor,
refers to the understanding of one idea, or
conceptual domain, in
terms of another, for example, understanding
quantity in terms of
directionality (e.g.
"prices are rising"). A conceptual domain can be any coherent
organization of human experience.
The regularity with which different languages employ the
same metaphors, which often appear to be perceptually based, has led to the
hypothesis that the mapping between conceptual domains corresponds to neural
mappings in the brain.
Each mapping (where
mapping is the systematic set of correspondences) that exist is between
constituent elements of the source and the target domain. [I] Many elements of target concepts come from
source domains and are not preexisting. To know a conceptual metaphor is to
know the set of mappings that applies to a given source-target pairing. The
same idea of mapping between source and target is used to describe
analogical reasoning
and inferences) is a fixed set of ontological (relating to essence or the
nature of being) correspondences between entities in source domain and entities
in target domain.
There is a list of
over 100 schemas in many categories about basic human behavior, reactions and
actions. These schemas are the realms in which the mappings takes place much
the same as the inferences in arguments have warrants and link evidence to claims
so do these schemas, architects carry-over their experiences with materials,
physics, art, culture, building codes, structures, plasticity, etc. to form
metaphor. Identifying conditions, operations, ideals and goals are combined to
form plans, sections and elevations which are then translated in to contract
documents. Later the contractors map this metaphor based on their schemes of
cost, schedule and quality control into schedules and control documents.
Humans interact
with their environments based on their physical dimensions, capabilities and limits.
[F]
The field of
anthropometric (human
measurement) has unanswered questions, but it's still true that human physical
characteristics are fairly predictable and objectively measurable. Buildings
scaled to human physical capabilities have steps, doorways, railings, work
surfaces, seating, shelves, fixtures, walking distances, and other features
that fit well to the average person.
[F]
Humans also interact with their environments based on
their sensory capabilities. The fields of human perception systems, like
perceptual psychology and
cognitive psychology, are not exact sciences, because human information processing
is not a purely physical act, and because perception is affected by
cultural factors, personal preferences, experiences, and expectations, so human
scale in architecture can also describe buildings with sightlines, acoustic
properties, task lighting, ambient lighting, and spatial grammar that fit well
with human senses. However, one important caveat is that human perceptions are
always going to be less predictable and less measurable than physical
dimensions.
For humans mappings
are not arbitrary, but grounded in the body and in every day experience and
knowledge. Mapping and making metaphors are synonymous. The person and not the
work make the metaphor. Without the body and the experience of either the
author or the reader nothing is being made. The thing does not have but the
persons have the experiences. As language, craft, and skills are learned by
exercise, repetition and every day application so are mappings.
Mappings are not
subject to individual judgment or preference: but as a result of making seeking
and finding the commonality by practice.
Humans learn to associate, create and produce by years of education and
practice while users have a longer history approaching and mapping for use and
recognition. Yet new metaphors are difficult to assimilate without daily use
and familiarity. AI overcomes this and stores limited memory in RAM. A
conceptual system contains thousands of conventional metaphorical mappings
which form a highly structured subsystem of the conceptual system.
Over the year’s society,
cultures, families and individuals experience and store a plethora of mapping
routines which are part of our mapping vocabulary. There are two types of mappings: conceptual
mappings and image mappings; both obey the Invariance Principle. “A. Image
metaphors are not exact “look-alikes” ;many sensory mechanisms are at work,
which can be characterized by Langacker’s focal adjustment (selection,
perspective, and abstraction); B. images and Image-schemas are continuous; an
image can be abstracted/schematized to various degrees; and C. image metaphors
and conceptual metaphors are continuous; conceptual metaphorical mapping
preserves image-schematic structure (Lakoff 1990) and image metaphors often
involve conceptual aspects of the source image. (“All metaphors are invariant
with respect to their cognitive topology, that is, each metaphorical mapping
preserves image-schema structure:”
Likewise when we
look at the geometrical formal parts of an architectural metaphor we note those
common elements where fitting, coupling and joints occur), again this
simultaneity of ideas and image operating in tandem where we see and know an
idea simultaneously; where the convention of the architectural space and the
metaphor of the conception converge. Such an axiom is the commonality between
man and machine, AI and human architecture and AI mechanism and its manager.
For both AI and humans the invariance principle offers the
hypothesis that
metaphor only maps components of meaning from the source language that remain
coherent in the target
context. The components of meaning that remain coherent in the
target context retain their
"basic
structure" in some sense, so this is a form of
invariance.
For humans there will be all sorts
of incongruities, similarities and differences.
Both humans and AI can experience onomatopoeic metaphors that are onomatopoeic (grouping of words that imitates
the sound it is describing, suggesting its source object, such as
"click", "bunk", "clang", "buzz",
"bang", or animal noises such as "oink", "moo",
or "meow") ? In this case an assemblage instead of a sound. As a non-linguistic it has impact beyond
words and is still a metaphor. Then a metaphor is much more than the sum of its
parts and is beyond any of its constituent constructions, parts and systems,
its very existence a metaphor. The cost to convey inconsistencies, variables
and nuances of human life can be formidable.
Elegant
architectural metaphors are those in which the big idea and the smallest of
details echo and reinforce one another manifest in paraphrasing where “people ascertain the deep metaphor that
underlies one or more surface metaphors by filling in terms of an implicitly
analogy”. [11] It is the “filling
in” wherein the [L] synapse (a region where nerve impulses are transmitted and
received, encompassing the axon terminal of a neuron that releases
neurotransmitters in response to an impulse) takes place.
The difference
between the indirect uses of metaphor verses the direct use of language to
explain the world. . In some circles this is referred to tangential thinking,
that approaching a subject from its edges without getting to the point.
[12] Users can
accept works which are vague, inane, and non-descript, evasive, and
disorienting as between micro and macro metaphors and the way they can inform
one another as the form of design may refer to its program, or a connector may
reflect the concept of articulation as a design concept. Both machines and
people have this capability, however the unpredictable human range is far more
diverse and original. The macro metaphor
drives the micro while they both inform one another.
Metaphors work by “reference to analogies that are known to
relate to the two domains”. In other words there is apriori knowledge of
these before they are spoken and when heard they are immediately found. [13]
Metaphors are formed in the human discovery of the obvious where one analogy
begets another which may or may not be relevant but be interesting enough to
explore and find a new referent. AI may receive, store and associate these to
its existing but has only its artificial collective repertoire. Hover, as
Microsoft spell-check it can learn, assimilate and recreate.
A” problem of the metaphor concerns the
relations between the word and sentence meaning, on the one hand, and speaker’s
meaning or utterance meaning, on the other” [14] “Whenever we talk about the metaphorical meaning of a word, expression,
or sentence, we are talking about what a speaker might utter it to mean, in a
way it that departs from what the word, expression or sentence actually means”. Without apparent rhyme of reason metaphors
of all arts have a way of recalling other metaphors of other times and places.
‘Human
cognition is fundamentally shaped by various processes of figuration”. “The
ease with which many figurative utterances are comprehended are has often been attributed to the constraining influence
of the context” ………..Including [15] “the
common ground of knowledge, beliefs, and attitudes recognized as being shared
by speakers and listeners (architects and users(clients, public) As
speakers architects, designers and makers “can’t help but employ tropes in
every day conversation (design) because they conceptualize (design) much of
their experience through the figurative schemes of metaphor (design). A metaphor involves a nonliteral use of
language”. [16] A non-literal use of language means that what is said is for
affect and not for specificity.
Minimizing risk,
metaphor is an abbreviated simile and to appreciate similarities and analogies
which is called “appreciation”. [17] In
psychology “appreciation” (Herbert
(1898) was a general term for those mental process whereby an attached
experience is brought into relation with an already acquired and familiar
conceptual system (Encoding, mapping, categorizing, inference, assimilation and
accommodation, attribution, etc).
Metaphors build an image in the (AI
system) mind, that is to say we (AI) “appreciate” what we already know. I have
always contended that we do not learn anything we already do not know. We learn
in terms of already established knowledge and concepts. We converse reiterating
what we presume the other knows, otherwise the other party would not
understand. The other party understands only because he already knows. In this
way humans and machines are alike. Early stages of AI architectural application
with architectural metaphoric axioms is best executed on commercial, industrial
projects with little interior detail and which can be closely monitored. The
risk of failure or mis-design my be simply mitigated after the completion but
before submittal to building officials for code reviewed.
The risks are
fairly minimal since there are already phases in the design process which
firewall the errors being transferred from one stage of development to the
other. This in and of itself minimizes risk; Along with AI/BIM checking risk
will be controlled.
The architect who assembles
thousands of bits of information ,
resifts and converts form words to
graphics and specification documents communicates the new proposed (the strange
new thing) in terms of the known and familiar.
The first
recipients are the owner, building officials; contractors must read seeking
confirmations of known and confirm its adherence to expectations. After its
construction the users read familiar signs, apparatus, spaces, volumes, shapes
and forms. The bridge carries over from one to another what is already known
.Even the strange that becomes familiar are both known but not in the current
relationship. For example when we apply a technology used on ships to a
building or a room which is commonly associated with tombs as a bank, etc. Both
are generally known but not in that specific context. We could not appreciate
it if it were not known .It is what Weiss calls commonalities and is the selection between commonalities and
differences that makes a metaphor. About understanding and discerning between
what is” true in fact” and “true in the model”. Since the gathering,
assimilation and observation of human contributions is often exx43nstiol this
is best done by humans to humans in teams known by some architects as
“squatting”. [bb]
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| Gibe by Barie Fez-Barringten |
Prototype theory is a mode of graded
categorization
in
cognitive science, where some members of a category are more central than
others
. For example, when asked to
give an example of the concept furniture,
chair is more frequently cited
than, say, stool.” [18]
“Metaphors are generally used to describe
something new by references to something familiar not just in conversation, but
in such diverse areas as science and psychotherapy. For both men and
machines metaphors are not just nice, they are necessary. They are necessary for casting abstract
concepts in terms of the apprehendable, as we do, for example, when we
metaphorically extend spatial concepts and spatial terms to the realms of
temporal concepts and temporal terms.
Metaphor is reasoning using abstract characters whereas reason by
analogy is a straight forward extension of its use in commonplace reasoning. [19] All
this to say and as if there was a choice that architects have a choice where to make a new building by analogy
or by metaphor. Analogies may be the
ticky-tacks, office building, church, school building, fire station analogies
to a first model verses an abstraction of a program into a new prototype. Is
the analogy any less a work of architecture?
Or do we
only mean that works of architecture are works of art when they make
abstractions? Humans are able to design
by metaphor whereas an artificial intelligence designs by analogy. [M] “In processing analogy, people
implicitly focus on certain kinds of commonalities and ignore others”. Noting these things an industry was created
called the “housing industry’ churning out analogies rather than individual
metaphors, leaving the metaphor to the context or theme of the development. It
is famous architects who are mostly famous because they made metaphors and from
them analogies were drawn. The analogous phenomenon has resulted in the
nineteenth century Sears offering pre-designed and package barns ready to ship
form Wisconsin to any where by mail order. Pre-engineered metal being and
manufactured homes are all part of the analogous scheme of reasoning the built
environment. Users have access to either and are able to shift perceptions. In
commonplace users wanting to be fed by metaphorical architecture go to Disney,
European, or urban entertainment and recreation centers.
Las Vegas thrives on what I call "metaphoric analogies”
abstractions of analogous building types. It is that synapse which attracts and
beguiles the visitor hungry for authenticity and reality. Living in analogous
urban replicas city dweller migrated to the suburbs in search of the metaphor
of “a man’s home is his castle”.
Today this metaphor has become an analogy as the metaphor
proliferates and analogies are transferred from one to another state and
country. We may be told a “cell is like a factory” which gives us a
framework for analogy and similarity. [19] An analogy is a kind of highly selective similarity where we focus
on certain commonalities and ignore others. The commonality is no that they are
both built out of bricks but that they both take in resources to operate and to
generate their products. On
the creative and architect’s side: “the central idea is that an analogy is a
mapping of knowledge from one domain (the base) into another (the target) such
that a system of relations that holds among the base objects also holds among
the target objects”. On the user’s side in interpreting an analogy, people seek
to put objects of the base in one-to-one correspondence with the objects of the
targets as to obtain the maximum structural match”. Confronting a Bedouin
village of tents a westerner faced with apparent differences looks for
similarities. “The corresponding
objects in the base and target need not resemble each other; rather object
correspondences are determined by the like roles in the matching relational
structures.” Cushions for seats, carpets for flooring, stretched fabric for
walls, roof, and cable for beams and columns, etc. “Thus, an analogy is a way of aligning and
focusing on rational commonalities independently of the objects in which those
relationships are embedded.” However,
there may be metaphors at work as well as the user reads the tent’s tension
cable structure, banners and the entire assemblage in a “romantic” eclectic
image of Arabness, metaphors beyond the imperial but of the realm of the
abstract and inaccurate. Managing the process by quality checking the
information from the fist domain minimizes risk assuring that analogy will be
correct.
“Central to the mapping process is the
principle of “systematicity: people prefer to map systems of predicates
favored by higher-order relations with inferential import (the Arab tent),
rather that to map isolated predicates. The systematicity principle reflects a
tacit preference for coherence and inferential power in interpreting analogy”. Metaphors
work by applying to the principle (literal) subject of the metaphor a system of
“associated implications” [20] characteristic
of the metaphorical secondary subject. These implications are typically
provided by the received “commonplaces” (ordinary; undistinguished or
uninteresting; without individuality: a commonplace
person.) About the secondary
subject ‘The success of the metaphor rests on its success in conveying to the
listener (Reader) some quieter defines respects of similarity or analogy
between the principle and secondary subject, “human and AI design by
translating concepts into two dimensional graphics that which ultimately imply
a multidimensional future reality.
“Dubbing” (invest with any name, character, dignity,
or title; style; name; call) and “epistemic
access” (relating to, or involving knowledge; cognitive.), “when dubbing is
abandoned the link between language and the world disappears”. [21]
Architectural metaphors are all
about names, titles, and the access to that the work provides for the reader to
learn and develop. At its best the vocabulary of the parts and whole of the
work is an encyclopedia and cultural building block.
The work
incorporates the current state of man’s culture and society which is an open
book for the reader. The freedom of both
the creator and reader to dub and show is all part of the learning experience
of the metaphor. As a good writer
“shows” and not “tells” so a good designer manifests configurations without
words.
However objective,
thorough and scientific; the designer, the design tools and the work gets dubbed
with ideas (not techne) we may call style, personality, and identity above and
beyond the program and its basic design (techne). It is additional controls,
characterizations and guidelines engrafted into the form not necessarily
overtly and expressly required. Dubbing
may occur in the making of metaphors as a way in which the design itself is
conceived and brought together. Dubbing may in fact be the process which
created the work as an intuitive act.
[22] Consider new concepts as being
characterized in terms of old ones (plus logical conjunctives)” [E] As William J. Gordon points out we make the
strange familiar by talking about one thing in terms of another.
[22] “Knowledge”
would not itself be conceptual or be expressed in the medium of thought, and
therefore it would not be cognitively structured, integrated with other
knowledge, or even comprehended. Hence, it would be intellectually
inaccessible”. In other words we would not know that we know. Where knowing is
the Greek for suffer, or experience. This was the Greek ideal proved in
Oedipus; “through suffering man learns”; we know that we know. Therefore, when
we observe that architecture makes metaphors we mean that we know that we know
that works exists and we can read authors messages. We learn the work and
improve the more artificial intelligence impacts the future of architecture.
While architectural metaphoric axioms are proactive the context is benign and
does not pose the catastrophic calamity doomsday- sayers prophesied. Still, it
is good to know that Axioms provide the checks and balances to a successful and
safe AI performance.
Postscript: Aesthetics, human to machine admixture and AI as complex
design tool
Today it is
possible for AI to design complex structures making possible the use of
materials and structures heretofore uneconomical, too costly and time consuming
to ever be considered, for example the steel light weight truss system [cc] of a conventional roof .
Not withstanding
the work of Afrred I Tauber’s Elusive
Synthesis: Aesthetics and Science
and considering the five senses of human experience defining aesthetics at best
warrants a negotiated and interdependency between man and his AI system. What
can be systemically or specifically
programmed will never reconstruct the human that directly senses and
then with a sixth sense makes some
illogical but yet pleasing redirection to himself feel, experience and
enjoy the environment. Aesthetics is a guiding principle in matters of artistic
beauty and taste, metaphor is the warrant to taste and is used to form works of
art and architecture. Aesthetics is also reasoning matters having to do with
understanding perceptions. While AI tools may be designed to replicate man’s
abilities to navigate, perceive, and judge the environment, AI cannot enjoy the
experience as one man (or the collective of all men).Then the AI device still
refers back to its creator to make sense of the events. It is to this extent
that AI thinking can intelligently, without the normative sense feedback, be
involved in aesthetic experience, judgment and consciousness. It is its
limitation of total sovereignty, autonomy and independence of AI.
It is likewise
questionable, as a design device, to replace human designers as the affects the
quality of the aesthetics of the design outcomes. But there is
no doubt that the AI designer can change the paradigms of design
outcomes where time, space and cost would otherwise be prohibited and therefore
could potentially expand the, scope , breadth and depth of programs to fully
design green buildings, solve
environmental issues, optimize, use of space, materials and use
materials in new ways.
Multi-disciplinary
access from arts, sciences, philosophies are economical and feasible with
enough capacity and devises so that buildings and their systems can include the
sculptors aesthetics for shapes and forms, the musicians ear for lyrical,
harmony and the poets sense of rhyme, sense and inference, Not to mention
behavior psychologist parameters of sequences and impacts of color, spaces, and
distances, etc. AI design will also facilitate client, user and occupant
participation in the design process. So while AI can perceive and act on signs
of the senses the artificial is not natural and has no natural understanding of
the senses. Aesthetically, as “beauty is in the eyes of the beholder” the AI
does “be” but not “behold”. In fact,
since the world in which man inhabits us actually design more and not less control of our habitations, that is while we wish our habitations to be
designed more humanely than machine, meaning that ideally it would be designed
by us. “Us” being natural man augmented by a device but not managed by that
device. We do not desire the aesthetic of machines. As example we don’t want to live in a
factory, industrial park or warehouse. Even living in a space capsule can only
be for limited times as it is devoid of nature. It is nature and free will
which artificial lacks. AI is not a sinister possibility but an opportunity to
optimize the efficiency of nature in human terms. Human architects both compose
the program and manage to reify its contents from words to diagrams and
diagrams to two dimensional graphics and three dimensional models to reify and
bring- out (educate) the user’s mind and fulfillment of unspoken and hidden
needs. Needs which may or may not have been programmed and intended; the
metaphor is the final resolution until it is built and used.
Then it is subject
to further tests of time, audience, trends, social politics, demographic
shifts, economics, and cultural changes. The aesthetics of the process and the
product are indigenous to natural man metaphor and a can be metaphorically
assimilated by artificial intelligence architects.
Conclusion:
The risks which AI
architectural axioms mitigate are benign, local and parochial to the profession
and pose little danger to the general public. However, as a model and safe to
develop it may be the proving ground and fist small step to bolster public
confidence to consider applying AI to other applications which pose more of a risk
public welfare.
Citations listed alphabetically:
Boyd, Richard; 1.14.0
Conrad, Ulrich; 1.3
Fraser, Bruce; 1.10.0
Gentner, Dedre; 1.13.0
Gibbs,
Jr., Raymond W.; 1.9.0
Glucksberg,
Sam; 1.12.0
Jeziorski, Michael; 1.13.0
Kuhn, Thomas S.; 1.15.0
Keysar,
Boaz; 1.12.0
Lakoff, George;
1.4
Mayer,
Richard E.; 1.17.0
Miller,
George A.; 1.11.0
Nigro, Georgia;
1.5.0
Ortony, Andrew; 1.0
Oshlag,
Rebecca S.; 1.18.0
Petrie,
Hugh G; 1.18.0
Pylyshyn, Zeon W.; 1.16.0
Reddy,
Michael J.; 1.2
Rumelhart, David E.; 1.7.0
Sadock, Jerrold M.; 1.6.0
Schon, Donald A.; 1.1
Searle, John R.; 1.8.0
Sternberg,
Robert J.; 1.5.0
Thomas
G. Sticht; 1.19.0
Tourangeau,
Roger; 1.5.0
Weiss, Paul; 1.4.11
Footnotes:
1. From http://www.springer.com/computer/artificial/journal/146
quote of New Visions of the
Post-Industrial Society, Int. Conf. July 1994).
2. The
Dartmouth proposal is
based on the central idea of
Pamela McCorduck's “
Machines That
Think”. She writes: "
I like to think of artificial intelligence
as the scientific apotheosis of a venerable cultural tradition." (
McCorduck 2004, p. 34)
"Artificial intelligence in one form or
another is an idea that has pervaded Western intellectual history, a dream in
urgent need of being realized.
“(McCorduck 2004, p. xviii)
"Our
history is full of attempts—nutty, eerie, comical, earnest, legendary and
real—to make artificial intelligences, to reproduce what is the essential
us—bypassing the ordinary means. Back and forth between myth and reality, our
imaginations supplying what our workshops couldn't, we have engaged for a long
time in this odd form of self-reproduction." (
McCorduck 2004, p. 3) She traces the desire back to its
Hellenistic roots and calls it the urge to "forge the Gods."
(
McCorduck 2004, p. 340-400) and Main article:
Philosophy of artificial intelligence
Artificial intelligence, by claiming to be able to recreate
the capabilities of the human
mind, is both a challenge and an inspiration for
philosophy. Are there limits to how intelligent machines can be? Is
there an essential difference between human intelligence and artificial
intelligence? Can a machine have a
mind and
consciousness?
While
anything known is programmable into an artificial man-made device it will only
be as good as the AI team and limited by what their momentary mind and
conscious dictated. As man’s mind and conscious is infinite, dynamic and
subject to external (higher power) influences the AI device and system must
constantly rely upon its creator team for updates and reconfigurations,
reconfigurations on the basis of their new assessments and evaluations.
3. Mind, Machine, and Metaphor an Essay on
Artificial Intelligence
and Legal Reasoning Alexander E. Silverman Westview Press
4. Artificial intelligence -
metaphor or oxymoron?
http://www.thefreelibrary.com/Artificial+intelligence+-+metaphor+or+oxymoron
4.1 Warren
Blumenfeld,
Pretty Ugly (
New York New
York, state, United States
New York, Middle Atlantic state of the United
States. It is bordered by Vermont, Massachusetts, Connecticut, and the Atlantic
Ocean (E), New Jersey and Pennsylvania (S), Lakes Erie and Ontario and the
Canadian province of: Perigee Books, 1989.)
4.2
Brad Darrach (1921-1997) was a journalist who wrote
primarily for Time Inc. magazines including Time,
Life, People and Sports Illustrated” and "Meet Shaky, The First Electronic
Person." (Life, November 20, 1970, pp.58B-68.)
4.3 Hubert Lederer
Dreyfus (born October 15, 1929) in Terre
Haute, Indiana is a professor of philosophy at the University of California,
Berkeley, & Stuart Dreyfus, Mind Over Machine. (New
York: Free Press, 1986.)
4.4 Marvin Minsky,
"Artificial Intelligence." (Scientific American, September,
1966, pp.246-260.)
4.6 Barbara
Wallraff, "The Literate Computer." (Atlantic Monthly, January, 1988,
pp. 64-71.)
4.7 West & L.
Travis, "The Computational Metaphor
and Artificial Intelligence." (AI Magazine, 12, (1), 1991, pp.64-79.)
4.8 Dr. Raymond
Gozzi, Jr., is Associate Professor in the Television-Radio Department at
Ithaca College
5.
Metaphor and Artificial Intelligence: A Special Double Issue of metaphor and Symbol Edited by John A.
Barnden, Mark G. Lee Published by: Psychology Press
Publication Date: 1st March 2001 ISBN: 978-0-8058-9730-2 this special issue arose out of a
symposium on metaphor and artificial intelligence in which the main orientation
was computational models and psychological processing models of metaphorical
understanding. The papers in this issue discuss:
*implemented computational systems for handling different aspects of metaphor
understanding;
*how metaphor can be accommodated in accepted logical representational
frameworks;
*psychological processes involved in metaphor understanding; and
*the cross-linguistic cognitive reality of conceptual metaphors.
6. Metaphor and Thought:
Second Edition
Edited by Andrew Ortony: School of
Education and social Sciences and
Institute for the learning
Sciences: North Western University
Published by Cambridge University
Press
First pub: 1979
Second pub: 1993
7. Generative metaphor: A perspective on
problem-setting in social policy: by Donald A. Schon
8. The conduit metaphor: A case of frame
conflict in our language about language: by Michael J. Reddy.
9. Programs and Manifestoes on
20th-Century Architecture about Glasarchitektur Ulrich Conrad'
10. The contemporary theory of metaphor by
George Lakoff
11. Metaphor, induction, and
social policy: The convergence of macroscopic and microscopic views by
Robert J. Sternberg, Roger Tourangeau, and Georgia Nigro
12. Figurative speech and linguistics by Jerrold M. Sadock
13. Some problems with the emotion of literal meanings by David E.
Rumelhart
14 Metaphor by John R. Searle
15 Process and products in making sense of tropes by Raymond W. Gibbs, Jr.
16. Interpretation of novel metaphors by Bruce Fraser
17. Images and models, similes and metaphors by George A. Miller
18. How metaphors work by Sam Glucksberg and Boaz Keysar
19. The shift
from metaphor to analogy in Western science by Dedre Gentner and Michael
Jeziorski
20 Metaphor and
theory change: What is” metaphor” a metaphor for? By Richard Boyd
21. Metaphor
in science by Thomas S. Kuhn
22. Metaphorical imprecision and the “top down”
research strategy by Zeon W. Pylyshyn who is Board of Governors Professor
of Cognitive Science at Rutgers Center for Cognitive Science. He is the author
of Seeing and Visualizing: It's Not
what You Think (2003) and Computation
and Cognition: toward a Foundation for Cognitive Science (1984), both
published by The MIT Press, as well as over a hundred scientific papers on
perception, attention, and the computational theory of mind.
Metaphor and Education is the final
section:
(Readers may wish to review my
monograms on Schools and Metaphors (Main Currents in Modern Thought/Center for
Integrative Education Sep.-Oct. 1971, Vol. 28 No.1, New Rochelle, New York
and The Metametaphor of architectural
education", (North
Cypress, Turkish University. December, 1997)
23. The instructive metaphor: Metaphoric
aids to students’ understanding of science by Richard E. Mayer
24. Metaphor and learning by Hugh G
Petrie and Rebecca S. Oshlag
25. Educational uses of metaphor by
Thomas G. Sticht
 |
| Axonometric drawn freehand by Barie Fez-Barringten |
References:
A. Artificial intelligence (
AI)
is the
intelligence
of machines and the branch of
computer science
which aims to create it. Textbooks define the field as "the study and
design of
intelligent agents,"
[1]
where an intelligent agent is a system that perceives its environment and takes
actions which maximize its chances of success.
John McCarthy, who coined the term in 1956,
defines it as "the science and engineering of making intelligent
machines."
B. Information technology (
IT), as defined by the
Information
Technology Association of America
(ITAA), is "the study, design, development, implementation, support or
management of computer-based
information systems,
particularly software applications and computer hardware." IT deals with
the use of electronic
computers and
computer software to
convert,
store,
protect,
process,
transmit, and
securely retrieve information.
C. The first lectures "Architecture
as the Making of Metaphors" were organized and conducted by Barie
Fez-Barringten near the Art and
Architecture building at the Museum
of Fine Arts Yale University 11/02/67 until 12/04/67. The guest speakers
were: Paul Weiss, William J. Gordon, Christopher Tunnard, Vincent Scully, Turan
Onat, Kent Bloomer, Peter Millard, Robert Venturi, Charles Moore, Forrest
Wilson, and John Cage.
During a prior series
of colloquia at Yale on art, Irving Kriesberg [C]
[4] had spoken about the characteristics of painting as a metaphor. It seemed
at once that this observation was applicable to architecture, to design of
occupiable forms. An appeal to Paul Weiss drew from him the suggestion that we
turn to English language and literature in order to develop a comprehensive,
specific, and therefore usable definition of metaphor. But it soon became
evident that the term was being defined through examples without explaining the
phenomenon of the metaphor; for our purposes it would be essential to have
evidence of the practical utility of the idea embodies in the metaphor as well
as obvious physical examples. Out of this concern grew the proposal for a
lecture series wherein professional and scholars would not only bring forward the
uses of metaphor but would also produce arguments against its use.
The beginning was
steeped in deductive reasoning since there was no new information pertaining to
metaphors. This included analyzing and explaining the syllogism:
- Art is the
making of metaphors
- Architecture is
an art
- Therefore
architecture is the making of metaphors.
Till now I did
nothing to reason why art is the making of neither metaphors nor why
architecture is an art. Since 1967 I proceeded to analyze the presumptions and
find its many applications. This new information by Andrew Ortony first
published in 1979, provides information to support inductive reasoning and to this end each axiom is its own warrant
to the inferences of the above syllogism and the answer to question of why
metaphor is the stasis to any of the syllogism’s claims and implications. As
architecture is an art because, like all the arts, it too makes metaphors, it
is the metaphor which likewise relates architecture, design and planning to artificial
intelligence: they both are likewise both metaphors and metaphoric. Metaphor, in that “artificial” informs us
about its intelligence (that it is neither human nor familiar) and intelligence
in that it is made by man’s hand. It is a man made learning, reasoning,
understanding processor which makes the strange familiar and reasons one thing
in terms of another. It is not a referent for a person, or a life-form but
something inhuman and mechanical.
Without a name, application and by itself as a metaphor it is strange
and yearns to be made familiar.
D. The Computational Metaphor and
Artificial Intelligence: A Reflective Examination of a Theoretical False work
by David M. West, Larry E. Travis
Considers questions of metaphor in
science and the computational metaphor in AI. Specifically, three issues: the
role of metaphor in science and AI, an examination of the computational
metaphor, and an introduction to the possibility and potential value of using
alternative metaphors as a foundation for AI theory.
E. Metaphorical way of knowing
by William J.J Gordon: Gordon began formulating the Synectics
method in 1944 with a series ... (Cambridge), ... Gordon in his book The Metaphorical Way of Learning and
Knowing, Synectics asks
participants to solve problems by thinking in analogies--to identify ways in
which one pattern or situation is like or similar to another totally unrelated
pattern or situation. Synectics uses comparisons such as analogies and
metaphors to stimulate associations. Developed by George M. Prince. Gordon was
one of the original speakers at the Yale lecture series.
F. Paul Weiss: Born in 1901, Paul Weiss has made major contributions
to several branches of philosophy, as well as to teaching and scholarly
publishing. Alfred North Whitehead remarked: "The danger of philosophical teaching is that it may become dead-alive,
but in Paul Weiss's presence that is impossible". Weiss is widely
believed to be America's greatest living speculative metaphysician, but he has
also made notable philosophical contributions to the discussion of sports, the
arts, religion, logic, and politics. Professor Weiss has been highly productive:
his Being and Other Realities (1995)
was hailed as one of his most exciting books, and as this volume goes to press
he is hard at work on yet another major treatise. The distinguished Library of
Living Philosophers, founded in 1938, is devoted to critical analysis and
discussion of some of the world's greatest living philosophers. Weiss (b.1901)
is arguably America's greatest living speculative metaphysician, as well as a
noteworthy philosophical contributor to the discussion of sport, the arts,
architecture, religion, logic, and politics. He was my mentor when I began this
research. Before his death at 101 years of age completed a book called "Emphatics,"
about the use of language. Dr. Weiss
worked in the branch of philosophy known as metaphysics, which addresses
questions about the ultimate composition of reality, including the relationship
between the mind and matter. He was particularly interested in the way people
related to each other through symbols, language, intonation, art and music. Emphatics,
(2000), which considers how ordinary experience stands in some dynamic
relationship with a second dimension, which provides focus, interruption,
significance or grounds.
"
G. Surrogates,"
published by Indiana University Press. Weiss says that: “A surrogate is "a
replacement that is used as a means for transmitting benefits from a context in
which its’ user may not be a part”. Architecture’s metaphors bridge from the
program, designs and contractors a shelter and trusted habitat. The user enters
and occupies the habitat with him having formulated but not articulated any its
characteristics. Yet it works. “It makes sense, therefore, to speak of two
sides to a surrogate, the user side and the context side (from which the user
is absent or unable to function). “ Each of us uses others to achieve a benefit
for ourselves. “We have that ability”. “None of us is just a person, a lived
body, or just an organism.
We are all three
and more. We are singulars who own and express ourselves in and through them.
In my early twenties I diagrammed a being as “”appetite”, “desire” and “mind”. I
defined each and described there interrelationships and support of one another.
Metaphor is one and all of these and our first experiences of sharing life with
in to what are outside of us. Likewise we can speak of the way architects use
AI to augment their capability and capacity to innovate and complete projects.
Metaphors are
accepted at face value and architecture is accepted at face value. Weiss:” It
is surely desirable to make a good use of linguistic surrogates” “ A common
language contains many usable surrogates with different ranges, all kept within
the limited confines that an established convention prescribes” It is amazing how that different people can
understand one another and how we can read meaning and conduct transaction with
non-human extents, hence architecture. As AI, architecture is such a “third
party” to our experience yet understandable and in any context. In his search
for what is real Weiss says he has explored the large and the small and the
relationships that realities have to one another. Accustomed to surrogates
architecture is made by assuming these connections are real and have benefit.
Until they are built and used we trust that they will benefit the end user.
H. Metaphor and AI: Statistic Relevance and Cognitive Role. A
Study on the Verb "guidare" (to drive) by Simona Musco, Università
degli Studi della Calabria, 2005-06. What is the way man understands metaphor?
The principal question is about the
possibility of the existence of physical systems different from man that is
able to reproduce the same phases that take to the comprehension of a metaphor.
The tentative is that to prove the thesis of an “embodied” language, in which metaphors
take an important place. For long time, in fact, there has been a wrong theory
about metaphor, considered only for its aesthetic value in the language,
not important for the acquisition of new knowledge.
“Then I’ve tried to demonstrate that there
are artificial systems that can acquire knowledge by themselves, without the
implementation of specific programs. Before this, I’ve analyzed some earlier
tentative of naturalization of mind, with some examples of systems created for
the analysis of natural language. Their lack was to be either symbolic or able
to learn, while the right way is to analyze an artificial system that is both
symbolic and able to learn. I’ve done this on the basis of the studies that
Elisabetta Gola has done on the verb "vedere" (to see), but doing on
my own an analysis of another verb, "guidare" (to drive). During the
experiment I’ve given to the system some data to learn, on the basis of which
it has to find regularities that are so not taught but literally learnt. It’s
the same system that creates its own rules, by casting how it has learnt on
what it doesn’t know yet, trying to disambiguate it. Thanks to this it has been
denied another false believing about language: there are not simply some rules
we have to follow and on the basis of which to create texts, these rules have
always to face with the new linguistic situations to which man has to adapt
himself. So, the artificial systems and the biological ones are similar for
their dynamicity, because they cope with the new situations in a way that is
controlled and creative at the same time.
K. This version is from
Searle (1999), and is also quoted in
Dennett 1991, p. 435. Searle's original formulation was "
The appropriately programmed computer really
is a mind, in the sense that computers given the right programs can be
literally said to understand and have other cognitive states." (
Searle 1980, p. 1). Strong AI is defined similarly by
Russell &
Norvig (2003, p. 947): "The
assertion that machines could possibly act intelligently (or, perhaps better,
act as if they were intelligent) is called the 'weak AI' hypothesis by
philosophers, and the assertion that machines that do so are actually thinking
(as opposed to simulating thinking) is called the 'strong AI' hypothesis “ from Searle's
Chinese Room argument:
Searle 1980,
Searle 1991;
Russell &
Norvig 2003, pp. 958-960;
McCorduck 2004, pp. 443-445 and
Crevier 1993, pp. 269-271.
L. Synapse is metaphor where
two are joined together as the
side-by-side association of homologous paternal and maternal chromosomes during
the first prophase of meiosis. How this happens is as biblical as: “faith is the substance of things hoped for,
the evidence of things not seen”
where our mental associations are themselves the metaphor, the evidence of
the works we do not actually see. We
see the metaphor, we read its extent, we synapse, analogies and metaphorize
absorbing its information, contextualizing and as much as possible and
resurrecting its reasons for creation.
The architectural metaphor only speaks through its apparent shape, form,
volume, space, material, etc that the concepts which underlie each are known to
the user as they would to a painting, poem, or concerto.
M. NASA; Goddard Space Flight Center; http://ants.gsfc.nasa.gov/ArchandAI.html
Official:
Steven Curtis; Website
Curator:
James Daniel; Last
Updated: April 2008.
The President's
Vision for Space Exploration initiated the transformation of NASA's
extraordinary capabilities. The goals of the new vision include advancement of
U.S. scientific, security, and economic interests through a robust space
exploration program which includes the goal of human exploration of planetary
surfaces.
The Vision requires innovative
multi-function structures, minimal resource use, and development of stand-alone
and human-interfaced robotic capabilities. Our team has responded by developing
ART (Addressable Reconfigurable Technology), as near-term Tetrahedral Walkers and
Manipulators for lunar reconnaissance (ALMA/ALI) and as a more advanced mobile
infrastructure for lunar exploration and exploitation (LARA) with applicability
wherever extreme mobility is required on Earth.
Future
ART structures will be capable of true autonomy using bi-level intelligence
combining autonomic and heuristic aspects, acting as part of an Autonomous
Nanotechnology Swarm (ANTS).
The Autonomous Nanotechnology Swarm (ANTS)
Architecture is well suited to remote space or ground operations. It is being
implemented on a near term basis, using Addressable Reconfigurable Technology
(ART). In the future, Super Miniaturized ART (SMART) will form highly
reconfigurable networks of struts, acting as 3D mesh or 2D fabric to perform a
range of functions on demand.
The
ANTS approach harnesses the effective skeletal/ muscular system of the frame
itself to enable amoeboid movement, effectively ‘flowing’ between morphological
forms”. ANTS’ structures would thus be capable of forming an en tire mobile
modular infrastructure adapted to its environment.
The ANTS
architecture is metaphorically inspired by the success of social insect
colonies, a success based on the {axiom} division of labor within the colony in
two key ways: [principle of axiom [T]} First, within their specialties,
individual specialists generally outperform generalists. [Principle of axiom
[T]} Second, with sufficiently efficient social interaction and coordination,
the group of specialists generally outperforms the group of generalists. Thus
systems designed as ANTS are built from potentially very large numbers of
highly autonomous, yet socially interactive elements. The architecture is
self-similar in those elements and sub-elements of the system may also be
recursively structured as ANTS on scales ranging from microscopic to
interplanetary distances” These are both metaphoric and multidisciplinary
applications of axioms and AI methodology. AI Architecture is not the making of
metaphors but self translating the design into a finally built product.
N. Architecture: Biological Form and Artificial
Intelligence.; Nikos A. Salingaros (*) and Kenneth G. Masden II (**) ; University
of Texas at San Antonio; (*) Department of Mathematics ; (**) College of
Architecture; A revised version of this paper, with illustrations, is published
in The Structurist, No. 45/46 (2006), pages 54-61. An organism
that exists in a symbolic abstracted domain is not totally alive, since there
is nothing to ground it to the real world. It is more like a computer,
executing an algorithm but not participating in the external world. This entity
resides partially or entirely within its own model of an artificial world. One
may go further and suggest that such an organism is not intelligent. As stated
by Brooks:
"It is hard to draw the line at what
is intelligence, [O] and
what is environmental interaction. In a sense it does not really matter
which is which, as all intelligent systems must be situated in some
world or other if they are to be useful entities. The key idea from
intelligence is: 'Intelligence is determined by the dynamics of
interaction with the world'. [P]
[O] Intelligence, according to
Ditionary.com is the capacity for
learning, reasoning, understanding, and similar forms of mental activity;
aptitude in grasping truths, relationships, facts, meanings, etc. Since
metaphor in intrinsic to this definition the field of artificial intelligence
is inherently metaphoric. And, since anything artificial is man-made by some
techne it too, as any art, is metaphoric formalizing something by a skill. P. Rodney
A. Brooks, Cambrian Intelligence (Cambridge, Massachusetts: MIT Press,
1999).
Q. Applications of
Artificial Intelligence Techniques to Component-Based Modular Building Design” by
C. Bridgewater, (Prof., Dept. of
Civ. Engrg., Imperial Coll. of Sci. Technol. and Medicine, South Kensington,
London, SW7 2BU, England.) and
B. L. Atkin, (Prof., Dept. of Constr.
Mgmt. & Engrg., Univ. of Reading, Whiteknights, Reading RG6 2AZ, England.)
Journal of Computing
in Civil Engineering, Vol. 8, No. 4, October 1994, pp. 469-488, (
doi 10.1061/(ASCE)0887-3801(1994)8:4(469))
R. Commonwealth Scientific and
Industrial Research Organization (CSIRO), Building, Construction and
Engineering, PO Box 56, Highett, Victoria, 3190, Australia. [R] “The development of standardized
product and process models for the building and construction industry has now
reached a stage where collaborative design is feasible.
The challenge
comes from the appropriate adoption of emerging technologies to support
advanced data interoperability at different levels of granularity.
Interoperability is the enabling mechanism that allows information to be
exchanged between collaborative systems. The process covers the information
flow from a CAD system to the code checking system. It contains the events and
activities taking place within each separate CAD and compliance checking system
and through the communication channels between the two systems”.
S.
Algorithmic Architecture Institute of Artificial Art Amsterdam: Parklaan 55
3722 BD Bilthoven The Netherlands
a.
Eric Vreedenburgh and Remko Scha: "The Artificial City." In: Flip ten
Cate (ed.): De Vrije Ruimte. Nieuwe Strategieën voor de Ruimtelijke
Ordening. Amsterdam: Stichting Ontwerpen voor Nederland, 1998, pp. 154-155.
[In Dutch.]
b.
Remko Scha: "Towards Architecture of Chance." In: Hans Konstapel,
Gerard Rijntjes and Eric Vreedenburgh (eds.): De Onvermijdelijke Culturele
Revolutie. (Den Haag: Stichting Maatschappij en Onderneming, 1998), pp.
105-114. [In Dutch.]
c. Jos de Bruin
and Remko Scha: "Algoritmische architectuur is toegepaste
toevalskunst."
Automatisering Gids, April 25, 2003, p. 17.
 |
| Freehand axonometric for calender by Barie Fez-Barringten |
T. Other monographs by Barie fez-Barringten
1.
Deriving the Multidiscipline
axioms from Metaphor and Thought [1]
2.
Metaphor and Cognition
3.
The science supporting the stasis to
architecture being an art [I]:
4.
Language of
metaphors applied to multidiscipline architecture
5.
“Metaphor’s interdisciplinary
Axioms
6.
Metaphoric Axioms for Micro disciplinary Architecture
7.
Complex Structure: art and architecture stasis
8.
Metaphor axioms of art, architecture and aesthetics
9.
Aesthetic
principles of metaphor, art and architecture
10. The
Six Principles of Art’s & Architecture’s Technical and Conceptual Metaphors
11. Framing
the art [A] vs. architecture argument
12. Metaphoric
Evidence
U. VBE
global network: VTT Technical Research Centre of Finland: Copyright © VTT 2006 Virtual
Building Environments (VBE) II project is a pivotal opportunity for Finnish
Real Estate and Construction Cluster (RECC) to establish an international
competitive advantage in the design, construction and operation of buildings.
Virtual Buildings
are digital representations of buildings that can be used for visualizing,
analyzing and managing various aspects of buildings throughout their life-cycle;
starting from the early design and ending to the demolition of the buildings.
The use of Virtual Buildings is already providing competitive advantages to
some RECC organizations.
VBE is referring
to a group of software applications that, as a group, define a building, its
parts, its behavior and its performance. It facilitates the manipulation and
storage of data that are used in the planning, design, construction and
operation of a building. It makes it possible to conduct experiments on the
building or with its parts, without first erecting the building or its parts.
The VBE is being
used as a general title in this project reflecting the situation where ICT
modeling is exhaustively used for the building process throughout their
lifecycle.
The main goal of
the project initiative is the use of VBE technologies in RECC. Consequently,
the initiative has several additional goals that will affect how the industry
is likely to operate in the future. These range from effects on industry
processes to enabling industry software interoperability, and from educating
professionals to providing help on real life industry projects.
V. Distributed
routine design over the internet with cooperating mdm agents
Pages:
209
by Mustafa Taner Eskil Michigan State
University as advised by: Jon Sticklen Michigan State
University: Published in 2004 by: Michigan
State University
East Lansing,
MI, USA Year of
Publication: 2004
ISBN:0-496-91545-2, Order Number:AAI3158940
W. One theory claims that Professor Charles M. Eastman at
Georgia Institute of Technology coined the
term. This theory is based on a view that the term
Building Information
Model is basically the same as
Building Product Model, which
Professor Eastman has used extensively in his book and papers since the late
1970s. ('Product model' means 'data model' or 'information model' in
engineering.)
Nevertheless, it
is agreed upon that the term was popularized by Jerry Laiserin as a common name for a digital representation
of the building process to facilitate exchange and interoperability of
information in digital format. According to him and others the first
implementation of BIM was under the
Virtual Building concept by
Graphisoft's
ArchiCAD,
in its debut in
1987.
Typically BIM uses
three-dimensional, real-time, dynamic building modeling software to increase
productivity in building design and construction. The process produces the
Building Information Model (also abbreviated BIM), which encompasses building
geometry, spatial relationships, geographic information, and quantities and
properties of
building
components.
X. AI & Society; Journal
of Knowledge, Culture and Communication
ISSN: 0951-5666 (print version)
ISSN: 1435-5655 (electronic version)
Journal no. 146
Springer London
Y.
HTTP://WWW.COMPUTERHOPE.COM IS COPYRIGHTED 1998-2009. . the first electrical
binary programmable computer analogy was to the adding machine called the Z1 originally
created by Germany's Konrad Zuse in his parent’s living room between
1936 and 1938
Z. (Ray
Kurzweil "The Age of Spiritual Machines" and Hans Moravec's
"Robot: Mere Machine to Transcendent Mind”.” The Singularity" is a
phrase borrowed from the astrophysics of black holes. The phrase has varied
meanings; as used by Vernor Vinge and Raymond Kurzweil, it refers to the idea
that accelerating technology will lead to superhuman machine intelligence that
will soon exceed human intelligence, probably by the year 2030. The results on
the other side of the "event horizon," they say, are unpredictable. We'll
try anyway.
aa. Axiom’s contextual forms
Three levels of axioms matching
three levels of AI disciplines which influence AI architectures.
- Multidiscipline: Macro most general where the
metaphors and axioms and metaphors used by the widest and diverse AI
disciplines, users and societies. All of society, crossing culture,
disciplines, professions, industrialist arts and fields as mathematics and
interdisciplinary vocabulary.
- Interdisciplinary axioms are between AI fields of art
[I] whereas
metaphors in general inhabit all these axioms drive a wide variety and aid
in associations, interdisciplinary contributions and conversations about
broad fields not necessary involved with a particular project but if about
a project about all context including city plan, land use, institutions,
culture and site selection, site planning and potential neighborhood
and institutional involvement.
- Micro Discipline: Between AI architects all involved
in making the built environment particularly on single projects involving
relevant arts[I], crafts, manufactures, engineers,
sub-con tractors and contractors. As well as owners, users, neighbors,
governments agencies, planning boards and town councils.
bb. The Charrette Handbook, Bill Caudill interviewed by
Larry Meyer for an Oral Business History Project, University of Texas, 1971;
sponsored by The Moody Foundation. Source: CRS Archives, CRS Center, Texas
A&M University, College Station, TX. A Piece of
Charrette History: The CRS “Squatters” April 3rd, 2006 by Bill Lennertz “The evolution of the collaborative,
multiple-day, inclusive, on-site Charrette is not a linear one but its roots
can be found in a variety of projects and processes, some of which were related
to land use and some of which were not. It is hard to pinpoint just when design
firms first began to involve stakeholders in the design process.
One of the most sited processes is the CRS
“squatters.” In 1948, CRS held the first “squatters” in Blackwell, Oklahoma on
an elementary school project. The Austin, Texas firm had a long commute to the
project site that they found wasted a lot of time, money, energy and creative
ideas. The partners set up a temporary office and “squatted” at the school site
until all of the design issues with the school board were resolved”..
CC. TrusSteel
is the product of over fifty-four years of combined experience in the truss
and CFS building products industry. Built upon the extensive truss
engineering and software knowledge of Alpine, an experienced staff of CFS
design engineers and many years of designing and building efficient trusses, it
is no surprise that more TrusSteel trusses are installed on commercial projects
each year than any other proprietary CFS truss system. With computerized design
what would take hours for each member, now is done in minutes and multiplied
time the hundreds in each system the material is now economically available.
dd. between Narrative and Number: The Case of
ARUP's 3D Digital City Model
Harvey Cultural Sociology.2009; 3: 257-276
ee. Emergence:
Morphogenetic Design Strategies by Michael Hensel, Michael Weinstock Hensel, M., Menges,
A., Weinstock, M. (eds.): 2004, Emergence: Morphogenetic Design Strategies,
Architectural Design, Vol. 74 No. 3, Wiley Academy, London. (ISBN:
0-470-86688-8)
ff. “Risk
management is the identification, assessment, and prioritization of
risks followed by
coordinated and economical application of resources to minimize, monitor, and
control the probability and/or impact of unfortunate events. Risk management
should create value; be an integral part of organizational processes; be part
of decision making; explicitly address uncertainty; be systematic and
structured; be based on the best available information; should be tailored;
take into account human factors; be transparent and inclusive; be dynamic,
iterative and responsive to change and should be capable of continual
improvement and enhancement. Once an
AI
risks has been identified, it must then be assessed as to its potential
severity of loss and to the probability of occurrence. These quantities can be
either simple to measure, in the case of the value of a lost building, or
impossible to know for sure in the case of the probability of an unlikely event
occurring. Therefore, in the assessment process it is critical to make the best
educated guesses possible in order to properly prioritize the implementation of
the
risk management plan.
The fundamental
difficulty in
risk assessment is determining the rate of
occurrence since statistical information is not available on all kinds of past
incidents. Furthermore, evaluating the severity of the consequences (impact) is
often quite difficult for immaterial assets” In architectural design AI risks
extend to return on investment analysis and cost to benefit in including the
cost of the AI system and the manpower needed to manage and monitor the works.
Only such projects as has recently been budgeted for Shanghai, Hong Kong,
Dubai, and Doha could afford deploying this initiative. “Risk management also
faces difficulties allocating resources to minimize spending while maximizing
the reduction of the negative effects of risks. Assessment of an AI initiative
includes identifying, characterizing, and assessing threats; assess the
vulnerability of critical assets to specific threats; determine the risk (i.e.
the expected consequences of specific types of attacks on specific assets);
identify ways to reduce those risks and prioritize risk reduction measures
based on a strategy”.
gg. Researched Publications: Refereed and
Peer-reviewed Journals:
1. "Architecture the making of
metaphors” Main Currents in Modern Thought/Center for Integrative
Education; Sep.-Oct. 1971, Vol. 28 No.1, New Rochelle,
New York.
2."Schools and metaphors”
Main Currents in Modern Thought/Center for Integrative Education Sep.-Oct.
1971, Vol. 28 No.1, New Rochelle, New York.
3."User's metametaphoric phenomena
of architecture and Music": “METU”
(Middle East Technical University: Ankara, Turkey): May 1995" Journal of
the Faculty of Architecture
4."Metametaphors and Mondrian:
Neo-plasticism and its' influences in architecture", 1993
5. "The Metametaphor of architectural
education", North Cypress, Turkish University. December, 1997
6."Mosques and metaphors”
Unpublished, 1993
7."The basis of the metaphor of
Arabia" Unpublished,
1993
8."The conditions of Arabia in
metaphor" Unpublished, 1993
9. "The metametaphor theorem" Architectural Scientific Journal,
Vol. No. 8; 1994 Beirut Arab University.
10. "Arabia’s metaphoric images"
Unpublished, 1993
11."The context of Arabia in metaphor" Unpublished, 1993
12. "A partial metaphoric vocabulary
of Arabia" “Architecture: University of Technology in Datutop;
February 1995 Finland
13."The Aesthetics of the Arab
architectural metaphor" “International Journal for Housing Science
and its applications” Coral Gables, Florida.1993
14."Multi-dimensional
metaphoric thinking" Open House, September 1997: Vol. 22; No. 3,
United Kingdom: Newcastle uponTyne
15."Teaching the techniques of
making architectural metaphors in the twenty-first century."
Journal of King Abdul Aziz University
Egg...Sciences; Jeddah: Code: BAR/223/0615:OCT.2.1421 H. 12TH EDITION; VOL.I
16. Word Gram #9 Permafrost:
Vol.31 Summer 2009 University of Alaska Fairbanks; ISSN: 0740-7890; page 197
17. "Metaphors
and Architecture." ArchNet.org. October, 2009.MIT press
hh. The
technical is that all art
[I],
including AI expresses one thing in terms of another by its inherent and
distinct craft. On the one hand there is the architect who acts as the
master builder (head carpenter); and on
the other the fountain of conceptual
metaphors which expresses ideas as built conceptual metaphors other wise
known as works of architecture.
Techne
is actually a system of practical knowledge a
s a craft or art informed
by knowledge of forms,
cybernetics and
computational neuroscience computer scientists, programmers, are just some of the
disciplines researching this craft.
 |
| Pen and ink by Barie Fez-Barringten |
,commonality, commonplace, Dubbing, equilibrium, equipoise, human, intelligence, knowing, natural, Stasis, thought, top-down, topoi, Barie Fez-Barringten
Is the originator (founder) of “Architecture: the making of metaphors(architecture as the making of metaphors)"
First lecture at Yale University in 1967
In 1970, founded New York City not-for-profit called Laboratories for Metaphoric Environments (LME) and has been widely published in many international learned journals.
First published 1971 in the peer reviewed learned journal:"Main Currents in Modern Thought";
The book “Architecture: the making of metaphors" has been published in February 2012 by Cambridge Scholars Publishing in New Castle on Tyne,UK
architecture, Architecture is a metaphor, art, Artificial intelligence, cognitive, commonality, commonplace, Dubbing, equilibrium, equipoise, human, intelligence, knowing, metaphor
http://www.blogger.com/blogger.g?blogID=2433463466927232250#editor/target=post;postID=4848192886019486313
Ozman,
H.A., and Craver, S.M., "Philosophical
foundations of education"
