Open Access Research Article
SCOPE AND OBJECTIVE OF ARTIFICIAL INTELLIGENCE
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Article Details
SCOPE AND OBJECTIVE
OF ARTIFICIAL INTELLIGENCE
AUTHORED
BY - SUBASH S
ABSTRACT:
The scope of
artificial intelligence (AI) encompasses developing computer systems that can
mimic human cognitive abilities like learning, reasoning, problem-solving, and
perception, allowing them to perform tasks that typically require human
intelligence, while the primary objective is to create machines capable of
analyzing data, identifying patterns, and making informed decisions without
explicit programming, ultimately aiming to automate complex processes and
enhance decision-making across various industries.
INTRODUCTION:
The
transformative scope of Artificial Intelligence in daily life, industries, and
future advancements, highlighting its impact on productivity and innovation. From my point
of view in AI, I have seen technology go from a futuristic idea to a necessary daily
necessity. These days, AI assists us with things like suggestions, reminders, and even customized experiences. It's fascinating to observe how once complicated AI is now making everyone's lives easier.
KEYWORDS:
Machines, Artificial
intelligence, computers, robotics,
ARTIFICIAL INTELLIGENCE:
Artificial intelligence is one of humanity's most sophisticated and amazing creations
to date. While this fact has been mentioned
and reiterated countless
times, it is difficult to acquire a full view on the potential
influence of AI in the future. The reason for this is the revolutionary impact
AI is having on society, especially at such a young stage in evolution. People have become anxious
about the inevitability and proximity of an AI takeover due to AI's rapid expansion and tremendous powers.
Furthermore, the revolution brought about by AI in various industries has led
business executives and the general public to believe that we are
on the verge of reaching the pinnacle of AI research and realizing AI's full
potential. Understanding the forms of AI
that are possible and those that exist now,
on the other hand, will provide a
clearer sense of existing AI capabilities and the long road ahead for AI development.
Because AI
research aims to make computers mimic human-like functioning, the degree to
which an AI system can reproduce human capabilities is utilized as a criterion
for classifying AI. Thus, AI can be classified as one of several
categories of AI based on how a machine compares to humans in terms of variety
and performance. In such a system, an AI that can execute more human-like
functions with comparable levels of competency is deemed more advanced, whereas
an AI with restricted functionality and performance is considered simpler and less evolved.[1]
There are two
general classifications of AI based on this criterion. One classification is based on AI and AI-enabled machines'
resemblance to human minds and their ability
to "think" and possibly "feel" like humans. Arend
Hintze, an assistant professor of integrative biology and computer science
and engineering at Michigan State University, divides
AI in four categories, ranging from today's
AI systems to sentient systems
that do not yet exist89. He classifies AI or
AI-based systems into four categories: reactive machines, limited memory
machines, theory of mind, and self-aware AI.
Reactive Machines:
These are the
most primitive kind of AI systems, with extremely restricted capabilities. They mimic the human mind's ability to
respond to various types of stimuli. Memory-based functionality is not available
on these devices.
This means that such robots cannot use previous experiences to inform their
current behaviors, i.e., they lack the ability to "learn." These devices could only respond to a
restricted set or combination of inputs automatically. They cannot be used to
improve their operations by relying on memory. IBM's Deep Blue, which defeated
chess Grandmaster Garry Kasparov in 1997, is a popular
example of a reactive AI machine. Deep Blue can detect pieces on the chess board and make predictions,
but it has no memory and cannot learn from past encounters. It analyses
potential moves by itself and its
opponent and selects the most strategic move. Deep Blue and Google's AlphaGo
were created for specific goals and
cannot be easily transferred to another circumstance.[2]
Limited
Memory:
Limited memory
machines are machines that, in addition to having the characteristics of fully reactive machines, can make
decisions based on historical data. All modern AI systems, including those that use deep learning,
are trained using vast amounts
of training data that
they store in memory to construct a reference model for addressing future problems. For example,
an image recognition Al is taught to name items it scans by employing thousands
of images and their labels.
When such an
AI scans a picture, it uses the training photos as references to comprehend the
contents of the image supplied to it, and it classifies fresh images with
increasing accuracy based on its
"learning experience." Almost all modern AI applications, from
chatbots and virtual assistants to self-driving cars, are powered by AI with
minimal memory. These AI systems can learn from past events to make better
decisions in the future. Some decision-making functions in self-driving automobiles are created in this manner.
Observations influence activities that will take place in the not-too-distant future,
such as an automobile changing
lanes. These observations are
not saved indefinitely.
Theory
of Mind:
While the
first two forms of AI have been and continue to be abundant, the next two types of AI exist only as a
concept or as a work in progress for the
time being. The next level of
AI systems that researchers are currently inventing is theory of mind AI. AI
will be able to better grasp the
entities it interacts with at the theory of mind level by discerning their
wants, emotions, beliefs, and mental processes. While artificial emotional
intelligence is now a burgeoning industry and a focus for
prominent AI researchers, obtaining Theory of mind level AI would necessitate
advancements in other areas of AI as well. This is because, in order to
genuinely understand human wants, AI robots must recognize humans as
individuals whose minds may be changed by a variety of conditions, hence
"understanding" humans. This concept relates to the recognition that others have their own beliefs, wants, and intentions that influence their decisions. This type of AI does not
yet exist.
Self-aware:
AI systems
in this category have a feeling of self and consciousness. Machines with self-
awareness are aware of their current condition and can utilize this knowledge
to infer how others are feeling. This form of artificial intelligence does not
yet exist. This is the final step of AI development, which currently exists
only in theory. Self- aware AI is an AI that has evolved to be so similar to
the human brain that it has gained self- awareness. Developing this form of AI,
which is decades, if not centuries, away from becoming a reality, is and will
always be the ultimate goal of all AI research. This sort of AI will not only
understand and elicit emotions in individuals with whom it interacts, but will
also have emotions, wants, beliefs, and maybe desires of its own. This is the
type of AI that technology sceptics are concerned about. Although the emergence
of self-awareness has the potential to accelerate our civilization's progress,
it also has the potential to lead to disaster. This is because, once
self-aware, the AI would be capable of possessing thoughts like self-
preservation, which might either directly or indirectly mark the end of
humanity, since such an entity could easily outmaneuver any human being's
intellect and create sophisticated schemes to take over humanity. The
alternative classification scheme which is commonly used in tech jargon,
divides technology into Artificial Narrow Intelligence (ANI), Artificial Super
Intelligence (ASI), and Artificial General Intelligence (AGI).
Artificial Narrow Intelligence (ANI):
This form of
artificial intelligence encompasses all extant AI, including the most intricate
and competent AI yet constructed. Artificial
narrow intelligence refers to AI systems that can only do
a single task autonomously while exhibiting human-like capabilities. These
machines can only accomplish what they are designed to do, giving them a very
limited or narrow range of capabilities. These systems relate to all reactive
and limited memory AI, according to the aforementioned classification approach.
Even the most sophisticated AI that employs machine learning and deep learning
to teach itself is classified as ANI.
Artificial Super intelligence (ASI):
The
development of Artificial Super intelligence (AGI) will most likely signal the
apex of AI research, as AGI will be by far the most capable forms of
intelligence on the planet. ASI, in addition to mimicking human intellect, will
be significantly superior at everything they perform due to vastly increased memory, faster data processing and
analysis, and decision-making skills. The advancement of AGI and ASI will result
in a scenario known as the singularity. While the prospect of having such
powerful tools at our disposal appears tempting, these devices may endanger our
existence or, at the very least, our way of life.
It is
difficult to imagine the situation of the human world when more advanced
varieties of AI emerge. However, it is apparent that there is still a long way
to go because the current state of AI development in comparison to where it is anticipated to go is still in its infancy.
For those who are pessimistic about the future of
AI, this suggests that it is still too early to be concerned about the singularity, and there is still time to assure
AI safety. And for those who are bullish about Al's future, the fact that we have
only scratched the surface of AI development makes the future even more
fascinating.
Artificial General Intelligence (AGI):
The ability
of an AI age to learn, perceive,
understand, and function totally
like a human person is referred to as artificial general intelligence. These systems will be able to
build numerous competences independently and form linkages and
generalizations across domains, significantly
reducing training time. By mimicking
our multifunctional capacities, AI systems will be equally as capable as humans. Artificial general intelligence (AGI) is machine intelligence that can grasp or learn and intellectual work that a human can. It is a
key goal of some AI research
and a popular theme in science fiction
and futuristic studies.
Some academics define artificial general intelligence as "strong
AI," "full AI," or a machine's ability to undertake
"general intelligent action". Some sources distinguish between strong
AI and "applied AI" (sometimes known
as "narrow AI" or "weak AI"): the use of software to
study or perform specialized problem solving or reasoning activities. Weak AI,
as opposed to Strong AI, does not seek to replicate the entire range of human
cognitive capacities.
REQUIREMENTS.
Various criteria
for intelligence have been presented
(most notably the Turing test), but no definition has yet to
satisfy everyone. However, artificial intelligence experts generally agree that
intelligence is required to achieve the following:
• Reason, employ strategy, solve puzzles, and make decisions
in the face of uncertainty,
• Represent knowledge, especially common sense knowledge;
• Plan, Learn, and Communicate in Natural Language;
and
• Integrate all of these skills towards common goals.
Other key
talents include the ability to detect (e.g., see) and act (e.g., move and
manipulate objects) in a world where intelligent behavior can be seen. This would entail being able to detect and respond to
hazards. Many interdisciplinary approaches to intelligence (for example,
cognitive science, computational intelligence, and decision
making) underline the need of considering extra attributes like
imagination (defined as the ability to construct mental images and concepts
that were not programmed in) and autonomy. Many of these qualities are
available in computer-based systems (e.g., computational creativity, automated
reasoning, decision support
system, robot, evolutionary computation, intelligent agent),
but not at human levels.
TESTS FOR CONFIRMING
HUMAN-LEVEL AGI
THE TURING TEST:
A machine and
a person chat sight unseen with a second human, who must determine which of the
two is the machine. The machine passes the test if it can mislead the evaluator
a large percentage of the time. Turing does not specify
what constitutes intelligence, simply that understanding it is a machine does not disqualify
it.
WOZNIAK'S COFFEE TEST:
A machine is
required to enter a typical American home and figure out how to make coffee: locate
the coffee machine,
locate the coffee,
locate the coffee,
locate the water, locate
a mug, and brew the coffee by pressing the appropriate buttons.
THE ROBOT COLLEGE STUDENT TEST (GOERTZEL):
A machine enrolls in a university, takes and passes
the same classes
as humans, and earns a degree.[3]
SCOPE OF AI:
AI has a very wide scope.
1.
Autonomous Planning
and Scheduling
2.
Autonomous Control
3.
Diagnosis
4.
Game Playing
5.
Theorem Proving
6.
Natural Language
Processing
a) Natural Language Understanding
7.
Robotics
OBJECTIVES OF AI
The main objectives of AI research
are.
1. Understand Human Cognition.
2. Cost-effective automation can replace humans in intellectual activities.
3. Low-cost intelligent augmentations
provide systems that assist humans think better, faster, and deeper.
4. Superhuman intelligence creates programmed
that outperform human intelligence
5. General problem solving solves a wide range of difficulties. Mind-blowing systems
6. Natural language communication with coherent discourse. Conducts an intelligent discourse.
7. Autonomy is defined as intelligent systems
operating on their own initiative. Must respond to the real world.
8. When
learning the system,
students should be able to acquire their own data and
generalize, hypothesis, apply/learn heuristics, and reason by analogy.
IMPORTANCE OF AI:
Many of today's largest
and most successful organizations, like Alphabet,
Apple, Microsoft, and Meta, use AI technologies to improve operations
and outperform competition. AI is
significant because of its potential to alter how humans live, work, and play.
It has been successfully employed in business to automate functions previously
performed by humans, such as customer service,
lead creation, fraud
detection, and quality
control. AI can do tasks far better than humans in a variety
of areas. When it comes to repetitive, detail-oriented activities, such as
analyzing huge quantities of legal papers to verify important fields are
correctly filled in, AI systems frequently accomplish assignments swiftly and with few errors.
CONCLUSION:
The pursuit of
AI's goals has given rise to groundbreaking advancements that are
revolutionizing various industries and reshaping modern society. From
problem-solving and decision-making to robotics and automation, AI's impact is
both far-reaching and transformative.
As we embrace the potential of AI, it is essential to navigate the ethical
considerations and ensure responsible development to harness its full potential
for the betterment of humanity.
[1] Ed Burns, “Artificial Intelligence”, https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial- Intelligence, March 2023
[2] Mia Williams, “Artificial Intelligence”, Larsen &
Keller, 2020
[3] K. Nitalaksheswara Rao, Dr. Satyanarayana, Mummana,
CH V Murali Krishna, Alabazar Ramesh, “ Artificial Intelligence and Machine
Learning – A Practitioner’s Approach”, Shanlax Publications, 2022, Page No 6.
[4] R.Vidya, “Introduction to
Artificial Intelligence and Expert Systems”, Pallavi Pathippagam S. India Pvt
Ltd., 2008, Page no 25.
[5] Er. Rajiv Chopra, “Artificial Intelligence, A
Practical Approach”, S.Chand & Company Ltd, Page No.4.
[6] Rajendra Akerkar, “Introduction
to Artificial Intelligence”, Prentice Hall of India Private Limited, 2005, Page
no, 13.
Article Information
SCOPE AND OBJECTIVE OF ARTIFICIAL INTELLIGENCE
Authors: SUBASH S
- Journal IJLRA
- ISSN 2582-6433
- Published 2025/02/15
- Issue 7
About Journal
International Journal for Legal Research and Analysis
- Abbreviation IJLRA
- ISSN 2582-6433
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