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Managing the benefits and risks of architectural artificial intelligence (resolution)

(16,502 words total (9,370 +- words in article) on 64 double spaced pages

By Barie Fez-Barringten: “A real architect”: Florida license #:AR 0012705

www.bariefez-barringten.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.

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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).

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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.

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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?

Keywords: 271 words (keywords, bio and affiliations)

Artificial intelligence, natural, intelligence, human, architecture, thought,

commonality, commonplace, dubbing, cognitive, knowing, stasis, art , [I] linguistic

analogy, equilibrium, equipoise, topoi, top-down, frame conflict, appreciate, conduit,

parte, design system, modified culture, mapping, structure, domain, signs, apparatus,

spaces, volumes, shapes, forms, metaphorical mappings, invariance principle, alive, dead,

onomatopeics, surrogates, appetite, desire, mind, indirect use, direct use, vision, gestalt,

formulae, grand design, psychological, processes, metaphor comprehension, memory,

mnemonics, encoding, mapping, categorizing, inference, assimilation, accommodation,

attribution, inferential import, structured programming, stability, referential specificity,

general acceptance of terms, vividness thesis, difference, identity, comparison sensible,

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communications, architecture, design, axioms, building, information, modeling, strength,

materials, warrant, resolution, inference, claim, building, information, modeling, axioms

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.

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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.

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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.

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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, contactors 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”.

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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

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

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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”.

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“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

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imagined, possible the reality of the probable is marginal, isolated, miniscule 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

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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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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.

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“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

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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

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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

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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).

“Universality, Global uniqueness, Sameness, Identity, and Identity abuse” are

just some of the axioms of web architecture. Francis Hsu of Rutgers writes that

“Software Architecture Axioms is a worthy goal. First, let's be clear that software axioms

are not necessarily mathematical in nature”.

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

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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.

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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.

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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

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create a world of possible machine parts, systems and structures well suited for artificial

intelligent life.

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,

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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

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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.

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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

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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

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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 anthropometrics (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

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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),

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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 onomatopeics 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.

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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

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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

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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

commonalties and is the selection between commonalties 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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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

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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

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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]

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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”;

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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

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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 les control of our habitations, that is while we wish our habitations

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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

40

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

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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?

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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.)

4.5 Michael Polanyi, Personal Knowledge. (Chicago: University of Chicago Press

43

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

44

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

45

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

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

46

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.

47

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

48

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

49

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 contactors 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.

50

We are all three and more. We are singulars who own and express ourselves in

and through them. In my early twenties I diagramed 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”

51

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.

I. This idea, and a detailed examination of the underlying processes, was first extensively

explored by George Lakoff and Mark Johnson in their work 1.4.9 Metaphors We Live

52

By. Other cognitive scientists study subjects similar to conceptual metaphor under the

labels "analogy" and "conceptual blending."

J. Artificial brain: Moravec 1988; Kurzweil 2005, p. 262; Russell Norvig, p. 957; and

Crevier 1993, pp. 271 and 279 The most extreme form of this argument (the brain

replacement scenario) was put forward by Clark Glymour in the mid-70s and was

touched on by Zenon Pylyshyn and John Searle in 1980. Daniel Dennett sees human

consciousness as multiple functional thought patterns; see "Consciousness Explained".

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

53

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

54

(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

55

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))

56

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.

T. Other monographs by Barie fez-Barringten

1. Deriving the Multidiscipline axioms from Metaphor and Thought [1]

57

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

lifecycle; 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

58

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

59

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

60

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.

1. 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.

2. 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 potent

ional neighborhood and institutional involvement.

3. 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 contactors. 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

61

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)

62

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

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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”.

[ff] Disaster Recovery Journal "Committee Draft of ISO 31000 Risk

management" (PDF). International Organization for Standardization.

http://www.nsai.ie/uploads/file/N047_Committee_Draft_of_ISO_31000.pdf

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

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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 as a craft or art informed

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by knowledge of forms, cybernetics and computational neuroscience computer scientists,

programmers, are just some of the disciplines researching this craft.