In 1980, John Searle introduced a division of the field of AI into "strong" and "weak" AI. Strong AI denoted the attempt to develop a full human-like intelligence, while weak AI denoted the use of AI techniques to either better understand human reasoning or to solve more limited problems. Although there was little progress in developing a strong AI through symbolic programming methods, the attempt to program computers to carry out limited human functions has been quite successful. Much of what is currently labeled AI research follows a functional model, applying particular programming techniques, such as knowledge engineering, fuzzy logic, genetic algorithms, neural networking, heuristic searching, and machine learning via statistical methods, to practical problems. This view sees AI as advanced computing. It produces working programs that can take over certain human tasks. Such programs are used in manufacturing operations, transportation, education, financial markets, "smart" buildings, and even household appliances. For a functional AI, there need be no quality labeled "intelligence" that is shared by humans and computers. All computers need do is perform a task that requires intelligence for a human to perform. It is also unnecessary, in functional AI, to model a program after the thought processes that humans use. If results are what matters, then it is possible to exploit the speed and storage capabilities of the digital computer while ignoring parts of human thought that are not understood or easily modeled, such as intuition. This is, in fact, what was done in designing the chess-playing program Deep Blue, which in 1997 beat the reigning world chess champion, Gary Kasparov. Deep Blue does not attempt to mimic the thought of a human chess player. Instead, it capitalizes on the strengths of the computer by examining an extremely large number of moves, more moves than any human player could possibly examine. There are two problems with functional AI. The first is the difficulty of determining what falls into the category of AI and what is simply a normal computer application. A definition of AI that includes any program that accomplishes some function normally done by a human being would encompass virtually all computer programs. Nor is there agreement among computer scientists as to what sorts of programs should fall under the rubric of AI. Once an application is mastered, there is a tendency to no longer define that application as AI. For example, while game playing is one of the classical fields of AI, Deep Blue's design team emphatically states that Deep Blue is not artificial intelligence, since it uses standard programming and parallel processing techniques that are in no way designed to mimic human thought. The implication here is that merely programming a computer to complete a human task is not AI if the computer does not complete the task in the same way a human would. For a functional approach to result in a full human-like in.

1. In 1980, John Searle introduced a division of the field of AI
into "strong" and "weak" AI. Strong AI denoted the attempt to
develop a full human-like intelligence, while weak AI denoted
the use of AI techniques to either better understand human
reasoning or to solve more limited problems. Although there
was little progress in developing a strong AI through symbolic
programming methods, the attempt to program computers to
carry out limited human functions has been quite successful.
Much of what is currently labeled AI research follows a
functional model, applying particular programming techniques,
such as knowledge engineering, fuzzy logic, genetic algorithms,
neural networking, heuristic searching, and machine learning
via statistical methods, to practical problems. This view sees AI
as advanced computing. It produces working programs that can
take over certain human tasks. Such programs are used in
manufacturing operations, transportation, education, financial
markets, "smart" buildings, and even household appliances.
For a functional AI, there need be no quality labeled
"intelligence" that is shared by humans and computers. All
computers need do is perform a task that requires intelligence
for a human to perform. It is also unnecessary, in functional AI,
to model a program after the thought processes that humans use.
If results are what matters, then it is possible to exploit the
speed and storage capabilities of the digital computer while
ignoring parts of human thought that are not understood or
easily modeled, such as intuition. This is, in fact, what was
done in designing the chess-playing program Deep Blue, which
in 1997 beat the reigning world chess champion, Gary
Kasparov. Deep Blue does not attempt to mimic the thought of a
human chess player. Instead, it capitalizes on the strengths of
the computer by examining an extremely large number of
moves, more moves than any human player could possibly
examine.
There are two problems with functional AI. The first is the

2. difficulty of determining what falls into the category of AI and
what is simply a normal computer application. A definition of
AI that includes any program that accomplishes some function
normally done by a human being would encompass virtually all
computer programs. Nor is there agreement among computer
scientists as to what sorts of programs should fall under the
rubric of AI. Once an application is mastered, there is a
tendency to no longer define that application as AI. For
example, while game playing is one of the classical fields of AI,
Deep Blue's design team emphatically states that Deep Blue is
not artificial intelligence, since it uses standard programming
and parallel processing techniques that are in no way designed
to mimic human thought. The implication here is that merely
programming a computer to complete a human task is not AI if
the computer does not complete the task in the same way a
human would.
For a functional approach to result in a full human-like
intelligence it would be necessary not only to specify which
functions make up intelligence, but also to make sure those
functions are suitably congruent with one another. Functional
AI programs are rarely designed to be compatible with other
programs; each uses different techniques and methods, the sum
of which is unlikely to capture the whole of human intelligence.
Many in the AI community are also dissatisfied with a
collection of task-oriented programs. The building of a general
human-like intelligence, as difficult a goal as it may seem,
remains the vision.
AI in science fiction
A truly intelligent computer remains in the realm of
speculation. Though researchers have continually projected that
intelligent computers are immanent, progress in AI has been
limited. Computers with intentionality and self consciousness,
with fully human reasoning skills, or the ability to be in
relationship, exist only in the realm of dreams and desires, a
realm explored in fiction and fantasy.
The artificially intelligent computer in science fiction story and

3. film is not a prop, but a character, one that has become a staple
since the mid-1950s. These characters are embodied in a variety
of physical forms, ranging from the wholly mechanical
(computers and robots) to the partially mechanical (cyborgs)
and the completely biological (androids). A general trend from
the 1950s to the 1990s has been to depict intelligent computers
in an increasingly anthropomorphic way. The robots and
computers of early films, such as Maria in Fritz Lang's
Metropolis (1926), Robby in Fred Wilcox's Forbidden
Planet (1956), Hal in Stanley Kubrick's 2001: A Space
Odyssey (1968), or R2D2 and C3PO in George Lucas's Star
Wars(1977), were clearly constructs of metal. On the other
hand, early science fiction stories, such as Isaac Asimov's I,
Robot (1950), explored the question of how one might
distinguish between robots that looked human and actual human
beings. Films and stories from the 1980s through the early
2000s, including Ridley Scott's Blade Runner (1982) and
Stephen Spielberg's A.I. (2001), pick up this question, depicting
machines with both mechanical and biological parts that are far
less easily distinguished from human beings. Fiction that
features AI can be classified in two general categories:
cautionary tales (A.I., 2001 ) or tales of wish fulfillment (Star
Wars ; I, Robot ). These present two differing visions of the
artificially intelligent being, as a rival to be feared or as a
friendly and helpful companion.