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The Philosophical, Mathematical, Psychological, And Linguistic Foundations Of Artificial Intelligence
It is said that artificial intelligence is in a juvenile stage of development. However, the level of maturity it has attained in a short period of time can be attributed to the incorporation of viewpoints from the disciplines of philosophy, mathematics, logic, probability, computation, psychology as well as decision sciences. In addition to this, the correlation of Artificial Intelligence with Computer Sciences has made this subject a reality that we see today. Over a period of time, artificial intelligence has evolved to become a part and parcel of many engineering courses. Artificial intelligence has also carved a separate genre of research for itself owing to its interdisciplinary nature. In the present times, there is hardly any AI engineering course that does not include this subject in its curriculum.
Philosophical foundations
The philosophical foundations of artificial intelligence can
be traced to the time when simple algorithms were devised to distinguish
between rational and irrational judgments. Scientists came up with the laws
governing the rational decisions of the human mind. The next step in the
process was to extend these laws to physical systems. This was done by
conceiving algorithms for logical processes. Over a period of time, the power
of reasoning found a strong parallel with intelligent machines and systems.
Various types of logical theorems, observation sentences, and confirmation
theories started to shape the structure of knowledge related to intelligent
systems.
Mathematical foundations
The mathematical foundations of artificial intelligence can
be traced to the quantitative tests prescribed by Alan Turing. In addition to
this, the age-old science of statistics has holistically shaped the discipline
of artificial intelligence. It needs to be noted at this point in time that
there have been other quantitative contributions of mathematical theorems to
the field of artificial intelligence. For instance, the incompleteness theorem
significantly concluded that there are limitations in determining the truth and
validity of all paradoxical statements. In other words, this theorem did not
prescribe the use of appropriate algorithms for establishing the truth of a
statement. This paved the way for the interpretation of statements in other
intelligent ways. Gradually, artificial intelligence started to develop as a
system that could interpret natural language, process vast data sets, and
acquire cognitive capabilities in line with humans. Mathematics also
contributed to the development of decision sciences by providing holistic
treatment of the line of logical thinking, thereby, contributing to the
widening of frontiers of artificial intelligence.
Psychological foundations
The study of
scientific psychology was a route to comprehension of the thinking of the human
brain. This field was extremely important as it helped in devising machines and
systems that could reason in a way identical to the human brain. The study of
psychology also proved beneficial for Artificial Intelligence in two major
dimensions. The first dimension was that of cognitive psychology which paved
the way for conscious and logical inference. The second important dimension was
the comprehension of human behavior that led to the development of
knowledge-based artificial agents. This also allowed the translation of
stimulus into internal knowledge and led to a course of action that was both
rational and scientific.
Linguistic foundations
The relevance of linguistics to artificial intelligence is
as important as knowledge representation. The domain of linguistics is
intricately linked to behavioral sciences. This is popularly called the
behavior approach to language learning. One of the most popular works in this
regard is syntactic structures by Noam Chomsky. He argued that the creativity
and symbolism in a language influence human behavior in one or another way.
This work-related to syntactic structures proved to be a landmark for the foundation
of intelligent systems that could seamlessly interact with humans and adapt to
a dynamic environment. The domain of linguistics evolved over a period of time
to cater to the requirements of artificial intelligence. The modern form of
linguistics was suited to understand the requirements of hybrid machines. In
this way, we saw the rise of computational linguistics which was popular in the
domain of artificial intelligence with the name natural language processing.
Natural language processing helped in the cognitive understanding of a machine
by translating the problem into a language that could be fed as an input to a
system.
Concluding remarks
We can conclude that the rise of artificial intelligence is
a direct result of contributions from fields like philosophy, psychology,
linguistics, mathematics, and decision sciences. As such, this
interdisciplinarity has enabled it to carve a separate niche for itself in the
current technological ecosystem.