What is Artificial Intelligence System (AIS) ?
Intelligence is a term which does not have any perfect definition.
For example, what one perceives as intelligent might not seem intelligent to someone else.
But there are certain characteristics that are needed for possessing intelligence :
- Ability to respond on various situations in a flexible manner.
- Capability of making sense out of ambiguous or erroneous messages.
- Ability of assigning relative importance to various elements, associated with a situation.
- Finding out similarities among different situations.
- Pointing out the differences between those situations that may be similar to each other in various aspects.
Artificial Intelligence System in MIS :
Artificial intelligence is a very growing field of science and technology and is interdisciplinary in nature and based on the concept of various disciplines such as computer science, linguistics, engineering, biology, mathematics and psychology.
The main objective of Artificial Intelligence (AI) is to make computer intelligent such that computers have human like capabilities (viz., ability to think, talk, hear, see, etc.). The major focus of AI is on developing computers a way, that they can perform human intelligence related functions such as problem solving, reasoning and learning from experience.
In the field of research AI demonstrates the intelligence of machines, i.e., the ability to learn, think, understand, use common sense and exhibit some of the sensory feelings. Intelligent systems are able to think logically, draw conclusions to problems related with the real world, learn new tasks & concepts, perform various tasks that need intelligence to understand the natural language and perceive visual scenes, just like human beings.
Definition of Artificial Intelligence
According to Haugeland :
AI is, "the exciting new effort to make computers think...machines with minds, in the full and literal sense".
According to Bellman :
AI is "the automation of activities that we associates with human thinking, activities such as decision making, problem solving, learning..."
Charniak and McDermett define AI as :
"the study of mental faculties through the use of computational model"
According to Winston :
Artificial Intelligence is "the study of the computations that make it possible to perceive reason and act'.
According to Kurzweil :
AI is "the art of creating machines that perform functions that require intelligence when performed by people".
According to Rich and Knight :
AI is "The study of how to make computers thinks at which, at the movement, people are better".
According to Schalkoff :
AI is "a field of study that seeks to explain and emulate intelligent behavior in terms of computational process".
According to Luger and Stubblefield :
Artificial Intelligence (AI) is "the branch of computer science that is concerned with the automation of intelligent behavior".
Need of Artificial Intelligence in Businesses
Following are the unique characteristics and abilities of AI, which make it very useful and interesting for various businesses. Role / Importance of artificial intelligence in business are as follows :
1) Preserve Intelligence and Knowledge :
Computers do not leave the job by giving a short notice. They also have the ability to acquire the skills of the experts and preserve it, so that skills can be used in the future in case the experts resign or retire from the job or are dead.
2) Store Information for Access by a wider Group than may be Possible with a Human :
With the help of the intelligent systems, it is possible to distribute knowledge throughout the organization. This has become important concern in the new e new economy. The information stored in the form of organizational knowledge base and the employees can access them and can analyse like electronic manuals and text books to interpret the knowledge. This knowledge interpretation is required to carry out the work in a better way. The computer has the ability to distribute the information in a much easy and faster manner as compared to the human beings.
3) Eliminates Monotonous Jobs :
In many organisations, intelligence computers or robots are being used to carry out the repetitive and tedious tasks.
4) Suggests Solutions of Similar Situations :
The human expert of the organization can present the details about the job process (its working), performed last year only while computers have the ability to present a wide range of data of even previous years.
5) Provides Strategic Advantage :
With the help of well-designed artificial intelligent systems, it is possible to reduce the cost (associated with production) and deliver an improved 'product mix'. This will help the organisation to enhance its strategic position and retain it for a long time.
Nature of Artificial Intelligence
1) Learn from Experience and Apply the Knowledge Acquired from Experience :
Humans have the natural ability to learn from past situations and by trial and error methods. This ability can be programmed in a computer system by researchers who are currently working on developing those types of systems which can learn and rectify from earlier experience.
2) Handle Complex Situations :
There may be times when people are trapped in complex situations, like world leaders facing tough decision making regarding terrorism, conflict, global economic conditions, hunger and poverty. Similarly, in business too, top-level managers and executives must handle complex market. challenging competitors, elaborate government regulations and a demanding workforce. While taking these decisions, human may also make mistakes. Therefore, developing a computer system, for handle such complex situations. would involve careful planning and intricate computer programming.
3) Solve Problems when Important Information is Missing :
Decision making almost always has to deal with uncertainty. This means that whenever decisions need to be taken, certain information is always missing or inaccurate as acquiring complete information is expensive or not possible. AI systems today, can calculate, compare and take decisions even when the complete information is unavailable.
4) Determine what is Important :
The mark of a good decision maker is having knowledge of the most significant task. This feature also needs to be inculcated in the computer systems by developing programs which identify important information.
5) React Quickly and Correctly to a New Situation :
A small child will react quickly and correctly when faced with new situation. The same is not with the computers.
Artificial intelligence examples, a child will know exactly that he must not risk. being too close to a position when he first goes near one.
6) Understand Visual Images :
A perceptive system is one which helps computers interpret visual images. Moving through a room of chairs and tables may prove to be a very insignificant activity for a human but not for a robot or computer. Here, the perceptive system which is an extension of visual image understanding, help any machine (robot or computer) to see, hear and feel object just like humans.
For example, military robots utilize cameras and perceptive systems to carry out exploration missions for detection of enemy weapons and soldiers. If correct detection is done, then it helps in saving many lives.
7) Process and Manipulate Symbols :
It is usual for people to see, manipulate and process symbols every day which act as Visual information to our brains. In comparison, computers have a difficulty in information from visual images but are getting exceedingly good at numerical calculations However, recent developments in machine-vision hardware and software have assisted computers to process and manipulate symbols in a limited way.
8) Be Creative and Imaginative :
Some creative and imaginative people have traditionally turned complex situations into advantages.
For example, when defective mints were manufactured with a whole in the middle, an entrepreneur instead of returning the consignment marketed it as Life Savers.
9) Use Heuristics :
Heuristics refer to the thumb rule which arise from people experience. This is often used for decision making. For example, while searching for a job, one might rank companies on the basis of profits per employee. With the right kind of programs, computers today get solutions by the use of approximation in place of trying to find the optimal solution which could be technically unfeasible or time consuming.
Applications/Domain of Artificial Intelligence
The major domains which are associated with the AI development and research. The applications of AI can be categorized into three major classes. cognitive science, robotics and natural interfaces. Though these classifications have many common things and overlap each other, therefore various other classifications are also used. Applications of Artificial Intelligence in management information system (MIS) are as follows :
1) Cognitive Science Applications :
The main concern of this branch of AI is to incorporate the knowledge from various disciplines like psychology, biology, mathematics, neurology and many other associated disciplines. It is related with the study of working of human brain. In order to understand how the human beings think and learn, human information processing is conducted. Some of the applications of cognitive science area for AI are given below:
i) Learning Systems :
The adaptive learning system uses the gathered learning to include the changes in their own behavior.
ii) Expert Systems :
These knowledge-based systems possess the ability of reasoning and analysis. They are also capable to provide 'expert's information'. The knowledge engineer interviews the experts (in a particular area) and then enters the acquired knowledge into the computer programs, so that the intelligent system can carry out its tasks.
iii) Fuzzy Logic :
The main aim of this area is to narrow the gap between human beings and artificial intelligence. Fuzzy logic is able to deal with the imperfect data in a careful way. Though not completely, yet it is able to solve many unstructured problems to a great extent, with the help of the inferences (collected through processing of uncertain data).
iv) Neural Networks :
Systems based on neural networks process the sample problems and learn their solutions to recognize the patterns. Such systems associate the input patterns with the correct answer by looking for patterns in a set of examples and also learns them. Fraud detection and credit assessment are the examples of application of neural networks.
v) Genetic Algorithms :
In this technique, problems are solved with the help of mathematical or randomized functions. It follows the 'survival of the fittest' law, proposed by Darwin, to replicate the advanced processes and solve the problem in a better way. With the help of the genetic algorithm software, it is able to find out the alternative, that best fits.
vi) Intelligent Agents :
These knowledge-based systems are able to carry out the tasks that are compatible to the expectation of the user by using expert systems in association with the other AI technologies. They act as 'agents' that fulfill the activity or need or assist the end user in performing the activities.
For example, the search engines take the help of intelligent agents to increase the popularity of e-commerce.
2) Robotics :
Robotics is a field of artificial intelligence whose main concern is to build computer controlled machines having the ability to exhibit physical features like human beings. It is able to do so by using various disciplines such as physiology, engineering and AI. Computer intelligence is provided, to supplement the functioning of machines. The application of this machine is found in Computer Aided Manufacturing (CAM). They inspect the products by identifying, gauging and guiding. With the help of robots, users are able to perform the tasks efficiently and in less time compare to human beings, and thereby gain competitive advantage. Robots possess certain features which help them in carrying out their tasks. They are :
i) Visual Perception :
The ability to see.
ii) Tactility :
The ability to understand, touch or perform corporeal assessment.
iii) Dexterity :
The power to manipulate and handle the tasks using both the hands.
iv) Locomotion :
Move and carry out task whatever environment it may be.
v) Navigation :
Ability to trace the direction and reach the final objective within the stipulated time.
3) Natural Interfaces :
One of the breakthroughs in the field of artificial intelligence is the development of the natural interfaces that allows the human beings to use the computers in an optimal manner. It includes following:
i) Natural Language :
The main concern of this area is to establish communication with robots or computers using those languages that human beings use in their conversation. Thus, a clear platform is established where user and robots/computers are able to communicate easily. Hence, the system is able to understand the instruction given by the user and response in an enhanced manner.
ii) Speech Recognition :
After getting motivated by the development and success of natural language processing, such systems have been built that have the ability to recognize voice and process the instructions by taking voice input. It has been possible to input data by using speech rather than conventional methods such as "mouse and keyboard".
iii) Multi-Sensory Interfaces :
Computers or robots carry out tasks by using the body movements just like in human beings.
iv) Virtual Reality (VR) :
Such systems are multi-sensory I/O devices to enable the user to interact and experience a virtual environment or object, to be as real as if it actually exists. VR finds greatest application in the field of computer aided design. Some other fields that have started incorporating VR are engineering, game playing, flight simulation, human resource training, training of astronauts and pilots, scientific analysis, recreation and medical diagnosis.
Difference between Natural Intelligence and Artificial Intelligence
Difference between natural and artificial intelligence is shown in table.
|
Capabilities |
Natural Intelligence |
Artificial Intelligence |
|
Preservation of knowledge
|
From the organizational point of view it is perishable in nature. |
Permanent.
|
|
Duplication and dissemination of knowledge |
Tough, costly, time consuming and expensive. |
Fast and easy. |
|
Total cost of knowledge
|
Can be inconsistent. Erroneous and sometimes incomplete. |
Can be thorough and consistent.
|
|
Documentability of process and knowledge |
Costly and difficult.
|
Is much cheaper and easy. |
|
Creativity
|
It is of high degree.
|
Uninspired and low in nature. |
|
Use of sensory experiences
|
The possibilities are rich and direct. |
Limited, initial interpretation is needed. |
|
Recognizing patterns and relationships
|
Easily explainable and very fast.
|
Though machine learning might be better than human beings in some cases
but in most of the cases it is not as good as human beings. |
|
Reasoning |
A wide context of experiences can be used. |
It is good only when the domain is focused narrow and stable. |