[Paleopsych] Ubiquity: Reflections on the Limits of Artificial Intelligence Security
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Reflections on the Limits of Artificial Intelligence Security
http://www.acm.org/ubiquity/views/v5i38_tugui.html
Ubiquity - The ACM IT Magazine and Forum
Reflections on the Limits of Artificial Intelligence[i]
Nature is very simple and efficient in everything she makes. We,
humans, complicate things.
By Alexandru Tugui[ii]
Abstract: Nature is very simple and efficient in everything she makes,
and is extremely obvious. We humans like to simulate in an extremely
complicated manner what exists quite simply in nature, and what we
succeed in simulating falls in the category of artificial
intelligence. Artificial intelligence has limits of scope, but they
fade away when compared with the performances of natural intelligence.
In this study, we undertake to outline some limits of artificial
intelligence compared to natural intelligence and some clear-cut
differences that exist between the two.
Keywords: intelligence, limits, artificial, robots, digit, law of
entropy, ABAC.
Man has always had nature and environment as models for his various
achievements, and using those models he succeeded in making machines,
tools, and robots with impressive performances. It's been speculated
that in the next 40 - 45 years computers could reach the performance
of the human brain, and that achievements in the field of artificial
intelligence will be quite amazing, even to the extent of making
synthetic workers (humanoid robots) with performances very much like a
human's. Could all this be really possible? We shall live (some of us
by our offsprings) and ... we shall see!
Communication leads to intelligence
The basic idea of the living world consists in transmitting to future
generations what is considered important for survival. Over time, a
collective memory was created. The modality of transmitting
information was complex: from signs to body language, from drawings to
speaking as such, from chopped stone to magnetic support.
Communication eventually reached various performances:
1. From simple to simple, for instance: speaking - speaking, seeing -
speaking, speaking - seeing;
2. from simple to complicated, for instance: speaking - representing,
seeing - representing;
3. from complicated to complicated, for instance: representing -
representing.
Note: Representing is a codification approach according to a certain
algorithm.
The last two variants of communication always assumed a certain
technology by means of which communication as such could be made:
seeing, speaking, writing, reading. Under such circumstances, we
should notice the fact that whereas some people had direct access to
this collective memory, other people had an indirect access by
traditions and habits.
It is common knowledge that an immediate connection between natural
intelligence and the modality of transmitting information and
knowledge among the members of a community is made directly. Consider,
for instance, the situation of children raised in the wild, who take
over the collective memory of the animals with which they live.
In other words, from the beginnings of mankind to the present, people
tackled the issue of sharing information among the members of the same
community or of different communities, of the same times or of
different times. A first stage consisted in the communication based on
simple drawings. This communication modality was simple and accessible
to all people without needing additional training, because everything
was visual!
Then the period of using certain symbols followed, symbols that are
hard to understand by those who are unskilled, which limited the
access to the transmitted/communicated information. This stage also
comprises the period of alphabet use.
The information period assumed the complication of the modality of
transmitting data, information, knowledge.
At first sight, everything seems very simple, but data digitizing
assumes a set of operations that would eventually lead to the
representation as strings of 0 and 1. We show this with the following
example: we find by sheer accident a magnetic support on which data
and information are stored. To know (see) such data and information,
we have to access them with a specialized peripheral depending on the
magnetic support, to manage them with a utilitary program, and finally
to process them with specialized software. All these steps are
necessary because simply seeing such data and information is of no
help.
Considering the above, we may synthetize communication between two
individuals into one of the following three variants:
Man (1) - Man (1)
Man (1) - MMMan (natural) (1)
Man (1) - intermediary - Man (2)
Man (1)- peripheral - MMMan (radio, TV, phone, computer
peripheral) (2)
Note: MMMan - many men. The index 1 accounts for the fact that the
communication process is simultaneous, whole index 2 gives us the clue
that there is a discrepancy between the two moments.
We think that artificial intelligence must take into account the
communication modalities and the coupling of the intelligent entities
to the collective memory of every community.
When will a computer "grow up"?
As we consider the evolutionary character of artificial intelligence,
we naturally wonder When will a computer "grow up"? -- when we could
speak of an "artificial intelligence" of matter, and have contextual
procedures that cover most circumstances that occur. In other words,
we speak of a transmitted intelligence based on limited,
difficult-to-generalize case studies.
Anyway, there are situations of denial of natural intelligence -- and
we have to acknowledge that, once "formatted," the raw matter of
natural intelligence can hardly ever be recovered. We are speaking of
children grown in the wild, who lose some of the partial
characteristics of their natural intelligence -- for example the
capacity of formulating sentences even if they have a quite rich
vocabulary.
People start learning when they are young! They learn from others'
experience (by the rules transmitted via various modalities); they
learn from their own experience (by the rules they compile).
We all accept the idea that natural intelligence is specific to the
living world, and from this perspective we cannot imagine that
humankind will ever reach that level of development that would enable
the simulation of natural intelligence in full detail. We think this
could be possible only to a certain extent, only if a hybrid system
between the living cell and the technical system is made -- the
so-called bio-techno-system. But one should not misunderstand this
idea! The bio-techno-system does not assume the achievement of a
technical system having incorporated a sequence of software procedures
to simulate the biological system, but the coupling of a living
organism and of a technical system where the informational interaction
is made by means of the computer system.
The answer to the question above is the more obvious the closer we are
to a success in the bio-techno-system field.
Some limits of artificial intelligence
We see on various Internet sites posted discussions, courses and
opinions on the future performance of artificial intelligence
application fields.
Nevertheless, the specialists in the field are challenged to create
equipment and software able to cope with the performance of the human
brain. There are assessments of time and memory requirements,
operation speed, ethics regarding how such an artificial intelligence
system should look and operate. There are even worries that humankind
will have to face an additional risk if some intelligent informatic
entities are not restricted in running processes and in making major
decisions, if they can program themselves (re-writing codes,
re-compiling), etc.
Nevertheless, at this point we should take into account certain
restrictions and limitations pertaining to artificial intelligence
that we will not succeed in overcoming. These are some of these
limits:
1. Artificial intelligence must take into account the law of entropy.
At this point, the relevant achievements do not take them into
account and do not succeed in simulating them. In nature, the law
of entropy leads to the stabilization of any type of system. The
passage from a high level of entropy to a low one and vice-versa
consumes energy. Most common movements in nature are the result of
applying the law of entropy to a given system. We think that by
the symbiosis between the living cell (living organism) and the
technical systems, the intelligent control of matter could be
achieved;
2. The entire foundation of artificial intelligence is based on
informatic procedures that mean to circumscribe the intelligent
behaviour of a human being, although experts never succeeded in
simulating the behaviour of an ape with an ABAC. As we saw
previously, the human being has the quality of complicating things
very much when he knows what he must do but mostly when he does
not know where he is heading. Therefore, we consider that when the
goal is not known very well, the human brain both functionally and
structurally will complicate even further the solution procedures,
which consumes time and considerable information resources. We
strongly believe that bio-techno-systems can be a solution to this
problem;
3. The two pillars of computer science, "0" and "1" together with
the truth values "True" and "False" are major borders in
artificial intelligence. Any intelligent information procedure is
decomposed eventually in strings of "0" and "1", which leads us to
the fundamental objection that intelligent machines will never be
like humans. We have to consider that bio-systems also work with
intermediary values;
4. Artificial intelligence is based very much on symbolic logic,
and has not succeeded in involving so-called affective logic. In
affective logic, combinations of truth values may lead to
different evaluations. A possible solution could be obtained by
using affective computing [1], which undertakes to model affective
behavior in various situations.
Conclusion
We believe that we will make considerable progress in the applicative
and theoretical fields of artificial intelligence. The limits we
synthetized are and will be felt for a long time, yet they will
decrease as new materials and new technologies are discovered. At the
same time, bio-techno-systems will be solution with a particular
technological impact on the evolution of artificial intelligence.
Footnotes
1. [8]http://www.bartneck.de/link/affective_portal.html
Bibliography
1. Bergeron, B. (2002) Dark Ages II. When the Digital Data Die,
Prentice Hall PTR, New Jersey, 2002
2. Denning, P. J., Metcalfe, R.M. (eds.) (1997) Beyond Calculation.
The Next Fifty Years of Computing, Copernicus, Springer-Verlag, New
York
3. Mesarovic, M., Pestel, E. (1975) Mankind at the Turning Point: The
Second Report to the Club of Rome, Reader's Digest Press, New York
4. Moore, A.D. (1969) Invention, Discovery and Creativity, Anchor
Books, New York
5. Tugui, A., Fatu, I. (2004) What is the Globally Information Based
Society Followed By? in Cyber Society Forum, at
[9]http://www.wfs.org/04tuguifatu.htm
6. Tugui, A. (2004) Calm Technologies in a Multimedia World, in
Ubiquity, ACM, Vol. 5, Issue 4, 17-23 March.
***
1.[10]http://www.computergames.ro/forum/archive/index.php/t-54808.html
2. [11]http://alicebot.sourceforge.net/alice_page.htm
3. [12]http://www.bartneck.de/link/affective_portal.html
4. [13]http://www.abelard.org/turing/tur-hi.htm
Alexandru TUGUI, Ph.D., is a Senior Lecturer at "Al. I. Cuza"
University, Iasi, Romania
Source: Ubiquity, Volume 5, Issue 38, December 1 - 7, 2004,
http://www.acm.org/ubiquity/
References
7. http://www.acm.org/ubiquity/bk_ex.html
8. http://www.bartneck.de/link/affective_portal.html
9. http://www.wfs.org/04tuguifatu.htm
10. http://www.computergames.ro/forum/archive/index.php/t-54808.html
11. http://alicebot.sourceforge.net/alice_page.htm
12. http://www.bartneck.de/link/affective_portal.html
13. http://www.abelard.org/turing/tur-hi.htm
14. http://campus.acm.org/forums/ubiquity/messageview.cfm?catid=1&threadid=355
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