INFORMATION TECHNOLOGY AND THE CONSUMER
At different rates IT is diffusing into the home. The implications of consumer innovations can be substantial. Widespread use of cars facilitated new ways of life, with a growth of suburban living and out-of-town shopping centres, and a decline of train and bus services. The expansion of consumer IT is associated with changes in ways of working (for example, telework), playing (new home entertainment systems), shopping (teleshopping), and learning (multimedia products of various sorts, such as this encyclopedia).IT can be used in monitoring body conditions (digital thermometers, pulse meters, and blood-pressure meters are available), and in providing health and lifestyle monitoring and advice (recommending exercise levels, medical check-ups, or diets). Telephone helplines have long offered advice, counselling, and medical services; these and many other services are beginning, sometimes in rudimentary form, to be provided on the Internet.
Thursday, June 3, 2010
TRENDS IN EMPLOYMENT
TRENDS IN EMPLOYMENT
The tendency to fit a new technology into established structures, rather than to start afresh every time, has often been documented. It is one reason for the absence of the huge office job losses that were being predicted in the late 1970s and early 1980s, when word processing first began to be taken up on a large scale. However, this is no reason to assume that existing structures will endure. Industrial interest in new forms of organization, such as novel management structures, coordination of activities over large distances by means of telecommunications, teleworking, and other forms of distance working, indicates willingness to consider change.
The “hollow firm” is one effort to gain flexibility. The company attempts to dispense with the direct ownership and operation of many facilities that would traditionally have belonged to it, instead outsourcing production, distribution, and other tasks to other firms. Many computer companies, for example, buy in many or most of their components from specialist suppliers, and some firms do little more than design the computer for others to assemble.
A related idea is “de-layering”, or “flattening”, in which the company tries to do away with the numerous layers of middle management and administration that have traditionally processed information, and communication flows between the senior staff and the shop floor or fieldworkers. New information systems are typically used to allow rapid communication across a reduced number of organizational layers.
By the late 1990s the integration of office IT is becoming apparent: material is increasingly exchanged by e-mail (which has finally established itself); many professionals use personal computers directly, often at home and while travelling, as well as in the office; and increasingly, personal computers are networked. Whether a loss of clerical jobs will result remains much debated. Some commentators point to job losses in office-based sectors such as financial services, which use IT intensively, as a harbinger of things to come. Others argue that the unemployment problems of industrial societies are related more to political and economic changes than to the use of new technology. Indeed, new information-related services are emerging, creating new jobs. While some office jobs may have gone, some other traditional clerical jobs have been upgraded to involve new functions made possible with new IT, such as desktop publishing, database management, and customer services.
A similar debate has concerned the quality of working life—whether skills have been enhanced or reduced, and whether working conditions have been improved or degraded, in the information revolution. Evidence to date indicates a mixed picture. There are certainly some areas in which conditions have worsened and skills have been lost, and many low-skill jobs have been created—for example, in cooking and serving fast food. Yet there is also a tendency for more jobs to be upgraded, and new technical skills and skill combinations are in demand. Large-scale deskilling has not taken place.Polarization of the workforce in terms of quality of work and levels of wages has ensued; at the same time a gulf has been opening between employed and unemployed people. Whether this is a result of the information revolution, or of more or less coincidental economic and political factors, the threat is evident of a widening social gulf between the “information-rich” and the “information-poor”. The former have information-processing skills, access to advanced technologies in their work, and the money to invest in IT at home for themselves and their children; the latter do not.
The tendency to fit a new technology into established structures, rather than to start afresh every time, has often been documented. It is one reason for the absence of the huge office job losses that were being predicted in the late 1970s and early 1980s, when word processing first began to be taken up on a large scale. However, this is no reason to assume that existing structures will endure. Industrial interest in new forms of organization, such as novel management structures, coordination of activities over large distances by means of telecommunications, teleworking, and other forms of distance working, indicates willingness to consider change.
The “hollow firm” is one effort to gain flexibility. The company attempts to dispense with the direct ownership and operation of many facilities that would traditionally have belonged to it, instead outsourcing production, distribution, and other tasks to other firms. Many computer companies, for example, buy in many or most of their components from specialist suppliers, and some firms do little more than design the computer for others to assemble.
A related idea is “de-layering”, or “flattening”, in which the company tries to do away with the numerous layers of middle management and administration that have traditionally processed information, and communication flows between the senior staff and the shop floor or fieldworkers. New information systems are typically used to allow rapid communication across a reduced number of organizational layers.
By the late 1990s the integration of office IT is becoming apparent: material is increasingly exchanged by e-mail (which has finally established itself); many professionals use personal computers directly, often at home and while travelling, as well as in the office; and increasingly, personal computers are networked. Whether a loss of clerical jobs will result remains much debated. Some commentators point to job losses in office-based sectors such as financial services, which use IT intensively, as a harbinger of things to come. Others argue that the unemployment problems of industrial societies are related more to political and economic changes than to the use of new technology. Indeed, new information-related services are emerging, creating new jobs. While some office jobs may have gone, some other traditional clerical jobs have been upgraded to involve new functions made possible with new IT, such as desktop publishing, database management, and customer services.
A similar debate has concerned the quality of working life—whether skills have been enhanced or reduced, and whether working conditions have been improved or degraded, in the information revolution. Evidence to date indicates a mixed picture. There are certainly some areas in which conditions have worsened and skills have been lost, and many low-skill jobs have been created—for example, in cooking and serving fast food. Yet there is also a tendency for more jobs to be upgraded, and new technical skills and skill combinations are in demand. Large-scale deskilling has not taken place.Polarization of the workforce in terms of quality of work and levels of wages has ensued; at the same time a gulf has been opening between employed and unemployed people. Whether this is a result of the information revolution, or of more or less coincidental economic and political factors, the threat is evident of a widening social gulf between the “information-rich” and the “information-poor”. The former have information-processing skills, access to advanced technologies in their work, and the money to invest in IT at home for themselves and their children; the latter do not.
THE DIRECTION OF THE INFORMATION REVOLUTION
THE DIRECTION OF THE INFORMATION REVOLUTION
The outcome of the information revolution is seen by some commentators as likely to be as profound as the shift from agricultural to industrial society. Others see the transformation as essentially a change from one form of industrial society to another, as has happened in earlier technological revolutions.
One major issue is how rapidly social institutions adapt to take advantage of the new ways of doing things that new IT makes possible. While some jobs and some areas of people’s lives do seem to have changed rapidly, many others appear to have been affected relatively little. Historians point out that it can take a very long time for what in retrospect seems the obvious way to use a technology to become standard practice. For example, electric motors were first used as if they were steam engines, with one centralized motor powering numerous devices, rather than numerous small motors, each powering its own appliance.
New IT has often been introduced into well-established patterns of working and living without radically altering them. For example, the traditional office, with secretaries working at keyboards and notes being written on paper and manually exchanged, has remained remarkably stable, even if personal computers have replaced typewriters.Often the technology that gains acceptance is that which most easily fits within traditional ways of doing things. For example, the fax machine, which could take hand-written or typed notes, and was often delegated to a secretary to use, was hugely successful in the 1980s. At the beginning of that decade, it had been predicted that fax would rapidly die out, and e-mail would take its place; but this proved to involve too much organizational change.
The outcome of the information revolution is seen by some commentators as likely to be as profound as the shift from agricultural to industrial society. Others see the transformation as essentially a change from one form of industrial society to another, as has happened in earlier technological revolutions.
One major issue is how rapidly social institutions adapt to take advantage of the new ways of doing things that new IT makes possible. While some jobs and some areas of people’s lives do seem to have changed rapidly, many others appear to have been affected relatively little. Historians point out that it can take a very long time for what in retrospect seems the obvious way to use a technology to become standard practice. For example, electric motors were first used as if they were steam engines, with one centralized motor powering numerous devices, rather than numerous small motors, each powering its own appliance.
New IT has often been introduced into well-established patterns of working and living without radically altering them. For example, the traditional office, with secretaries working at keyboards and notes being written on paper and manually exchanged, has remained remarkably stable, even if personal computers have replaced typewriters.Often the technology that gains acceptance is that which most easily fits within traditional ways of doing things. For example, the fax machine, which could take hand-written or typed notes, and was often delegated to a secretary to use, was hugely successful in the 1980s. At the beginning of that decade, it had been predicted that fax would rapidly die out, and e-mail would take its place; but this proved to involve too much organizational change.
SOCIAL AND TECHNOLOGICAL DEVELOPMENTS
SOCIAL AND TECHNOLOGICAL DEVELOPMENTS
First, there are social and organizational changes. Information-processing has become increasingly visible and important in economic, social, and political life. One familiar piece of evidence is the statistical growth of occupations specializing in information activities. Numerous studies have demonstrated substantial growth in information-based occupations. These occupations now take the largest share of employment in the United States, the United Kingdom, and many other industrial societies. The biggest category is information processors—mainly office workers—followed by information producers, distributors, and infrastructure workers.
Second, there is technological change. The new information technology (IT) based on microelectronics, together with other innovations such as optical discs and fibre optics, underpins huge increases in the power, and decreases in the costs, of all sorts of information-processing. (The term “information-processing” covers the generation, storage, transmission, manipulation, and display of information, including numerical, textual, audio, and video data.) The information-processing aspects of all work can be reshaped through IT, so the revolution is not limited to information occupations: for example, industrial robots change the nature of factory work.
Computing and telecommunications (and also such areas as broadcasting and publishing) used to be quite distinct industries, involving distinct technologies. Now they have converged around certain key activities, such as use of the Internet. Using the same underlying technologies, modern computing and telecommunication devices handle data in digital form. Such data can be shared between, and processed by, many different devices and media, and used in a vast range of information-processing activities.
The pace of adoption of new IT has been very speedy: it is markedly more rapid than that of earlier revolutionary technologies, such as the steam engine or electric motor. Within 25 years of the invention of the microprocessor, it had become commonplace in practically every workplace and many homes: present not only in computers, but also in a huge variety of other devices, from telephones and television sets to washing machines and children’s toys.
First, there are social and organizational changes. Information-processing has become increasingly visible and important in economic, social, and political life. One familiar piece of evidence is the statistical growth of occupations specializing in information activities. Numerous studies have demonstrated substantial growth in information-based occupations. These occupations now take the largest share of employment in the United States, the United Kingdom, and many other industrial societies. The biggest category is information processors—mainly office workers—followed by information producers, distributors, and infrastructure workers.
Second, there is technological change. The new information technology (IT) based on microelectronics, together with other innovations such as optical discs and fibre optics, underpins huge increases in the power, and decreases in the costs, of all sorts of information-processing. (The term “information-processing” covers the generation, storage, transmission, manipulation, and display of information, including numerical, textual, audio, and video data.) The information-processing aspects of all work can be reshaped through IT, so the revolution is not limited to information occupations: for example, industrial robots change the nature of factory work.
Computing and telecommunications (and also such areas as broadcasting and publishing) used to be quite distinct industries, involving distinct technologies. Now they have converged around certain key activities, such as use of the Internet. Using the same underlying technologies, modern computing and telecommunication devices handle data in digital form. Such data can be shared between, and processed by, many different devices and media, and used in a vast range of information-processing activities.
The pace of adoption of new IT has been very speedy: it is markedly more rapid than that of earlier revolutionary technologies, such as the steam engine or electric motor. Within 25 years of the invention of the microprocessor, it had become commonplace in practically every workplace and many homes: present not only in computers, but also in a huge variety of other devices, from telephones and television sets to washing machines and children’s toys.
Information Revolution
INTRODUCTION
Information Revolution, fundamental changes in the production and use of information, occurring in the late 20th century. Human societies throughout history have had “information specialists” (from traditional healers to newspaper editors); and they have had “information technologies” (from cave painting to accountancy); but two interrelated developments, social and technological, underpin the diagnosis that an information revolution is now occurring.
Information Revolution, fundamental changes in the production and use of information, occurring in the late 20th century. Human societies throughout history have had “information specialists” (from traditional healers to newspaper editors); and they have had “information technologies” (from cave painting to accountancy); but two interrelated developments, social and technological, underpin the diagnosis that an information revolution is now occurring.
Wednesday, June 2, 2010
A brief overview of Information Technology-Advantages and Disadvantages
Our world today has changed a great deal with the aid of information technology. Things that were once done manually or by hand have now become computerized operating systems, which simply require a single click of a mouse to get a task completed. With the aid of IT we are not only able to stream line our business processes but we are also able to get constant information in 'real time' that is up to the minute and up to date.The significance of IT can be seen from the fact that it has penetrated almost every aspect of our daily lives from business to leisure and even society. Today personal PCs, cell phones, fax machines, pagers, email and internet have all not only become an integral part of our very culture but also play an essential role in our day to day activities. With such a wide scope for the purpose of this article we shall focus on the impact of the internet in information technology.
Some of the advantages of information technology include:
Globalization - IT has not only brought the world closer together, but it has allowed the world's economy to become a single interdependent system. This means that we can not only share information quickly and efficiently, but we can also bring down barriers of linguistic and geographic boundaries. The world has developed into a global village due to the help of information technology allowing countries like Chile and Japan who are not only separated by distance but also by language to shares ideas and information with each other.
Communication - With the help of information technology, communication has also become cheaper, quicker, and more efficient. We can now communicate with anyone around the globe by simply text messaging them or sending them an email for an almost instantaneous response. The internet has also opened up face to face direct communication from different parts of the world thanks to the helps of video conferencing.
Cost effectiveness - Information technology has helped to computerize the business process thus streamlining businesses to make them extremely cost effective money making machines. This in turn increases productivity which ultimately gives rise to profits that means better pay and less strenuous working conditions.
Bridging the cultural gap - Information technology has helped to bridge the cultural gap by helping people from different cultures to communicate with one another, and allow for the exchange of views and ideas, thus increasing awareness and reducing prejudice.
More time - IT has made it possible for businesses to be open 24 x7 all over the globe. This means that a business can be open anytime anywhere, making purchases from different countries easier and more convenient. It also means that you can have your goods delivered right to your doorstep with having to move a single muscle.
Creation of new jobs - Probably the best advantage of information technology is the creation of new and interesting jobs. Computer programmers, Systems analyzers, Hardware and Software developers and Web designers are just some of the many new employment opportunities created with the help of IT.
Some disadvantages of information technology include
Unemployment - While information technology may have streamlined the business process it has also crated job redundancies, downsizing and outsourcing. This means that a lot of lower and middle level jobs have been done away with causing more people to become unemployed.
Privacy - Though information technology may have made communication quicker, easier and more convenient, it has also bought along privacy issues. From cell phone signal interceptions to email hacking, people are now worried about their once private information becoming public knowledge.
Lack of job security - Industry experts believe that the internet has made job security a big issue as since technology keeps on changing with each day. This means that one has to be in a constant learning mode, if he or she wishes for their job to be secure.
Dominant culture - While information technology may have made the world a global village, it has also contributed to one culture dominating another weaker one. For example it is now argued that US influences how most young teenagers all over the world now act, dress and behave. Languages too have become overshadowed, with English becoming the primary mode of communication for business and everything else.
Some of the advantages of information technology include:
Globalization - IT has not only brought the world closer together, but it has allowed the world's economy to become a single interdependent system. This means that we can not only share information quickly and efficiently, but we can also bring down barriers of linguistic and geographic boundaries. The world has developed into a global village due to the help of information technology allowing countries like Chile and Japan who are not only separated by distance but also by language to shares ideas and information with each other.
Communication - With the help of information technology, communication has also become cheaper, quicker, and more efficient. We can now communicate with anyone around the globe by simply text messaging them or sending them an email for an almost instantaneous response. The internet has also opened up face to face direct communication from different parts of the world thanks to the helps of video conferencing.
Cost effectiveness - Information technology has helped to computerize the business process thus streamlining businesses to make them extremely cost effective money making machines. This in turn increases productivity which ultimately gives rise to profits that means better pay and less strenuous working conditions.
Bridging the cultural gap - Information technology has helped to bridge the cultural gap by helping people from different cultures to communicate with one another, and allow for the exchange of views and ideas, thus increasing awareness and reducing prejudice.
More time - IT has made it possible for businesses to be open 24 x7 all over the globe. This means that a business can be open anytime anywhere, making purchases from different countries easier and more convenient. It also means that you can have your goods delivered right to your doorstep with having to move a single muscle.
Creation of new jobs - Probably the best advantage of information technology is the creation of new and interesting jobs. Computer programmers, Systems analyzers, Hardware and Software developers and Web designers are just some of the many new employment opportunities created with the help of IT.
Some disadvantages of information technology include
Unemployment - While information technology may have streamlined the business process it has also crated job redundancies, downsizing and outsourcing. This means that a lot of lower and middle level jobs have been done away with causing more people to become unemployed.
Privacy - Though information technology may have made communication quicker, easier and more convenient, it has also bought along privacy issues. From cell phone signal interceptions to email hacking, people are now worried about their once private information becoming public knowledge.
Lack of job security - Industry experts believe that the internet has made job security a big issue as since technology keeps on changing with each day. This means that one has to be in a constant learning mode, if he or she wishes for their job to be secure.
Dominant culture - While information technology may have made the world a global village, it has also contributed to one culture dominating another weaker one. For example it is now argued that US influences how most young teenagers all over the world now act, dress and behave. Languages too have become overshadowed, with English becoming the primary mode of communication for business and everything else.
Information Technology & Artificial Intelligence
Artificial Intellegince (AI)-Bringing Common Sense, Expert Knowledge, and Superhuman Reasoning to Computers
Artificial Intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.
Although there are some fairly pure applications of AI -- such as industrial robots, or the IntellipathTM pathology diagnosis system recently approved by the American Medical Association and deployed in hundreds of hospitals worldwide -- for the most part, AI does not produce stand-alone systems, but instead adds knowledge and reasoning to existing applications, databases, and environments, to make them friendlier, smarter, and more sensitive to user behavior and changes in their environments. The AI portion of an application (e.g., a logical inference or learning module) is generally a large system, dependent on a substantial infrastructure. Industrial R&D, with its relatively short time-horizons, could not have justified work of the type and scale that has been required to build the foundation for the civilian and military successes that AI enjoys today. And beyond the myriad of currently deployed applications, ongoing efforts that draw upon these decades of federally-sponsored fundamental research point towards even more impressive future capabilities:
Autonomous vehicles: A DARPA-funded onboard computer system from Carnegie Mellon University drove a van all but 52 of the 2849 miles from Washington, DC to San Diego, averaging 63 miles per hour day and night, rain or shine;
Computer chess: Deep Blue, a chess computer built by IBM researchers, defeated world champion Gary Kasparov in a landmark performance;
Mathematical theorem proving: A computer system at Argonne National Laboratories proved a long-standing mathematical conjecture about algebra using a method that would be considered creative if done by humans;
Scientific classification: A NASA system learned to classify very faint signals as either stars or galaxies with superhuman accuracy, by studying examples classified by experts;
Advanced user interfaces: PEGASUS is a spoken language interface connected to the American Airlines EAASY SABRE reservation system, which allows subscribers to obtain flight information and make flight reservations via a large, on-line, dynamic database, accessed through their personal computer over the telephone.
Artificial Intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.
Although there are some fairly pure applications of AI -- such as industrial robots, or the IntellipathTM pathology diagnosis system recently approved by the American Medical Association and deployed in hundreds of hospitals worldwide -- for the most part, AI does not produce stand-alone systems, but instead adds knowledge and reasoning to existing applications, databases, and environments, to make them friendlier, smarter, and more sensitive to user behavior and changes in their environments. The AI portion of an application (e.g., a logical inference or learning module) is generally a large system, dependent on a substantial infrastructure. Industrial R&D, with its relatively short time-horizons, could not have justified work of the type and scale that has been required to build the foundation for the civilian and military successes that AI enjoys today. And beyond the myriad of currently deployed applications, ongoing efforts that draw upon these decades of federally-sponsored fundamental research point towards even more impressive future capabilities:
Autonomous vehicles: A DARPA-funded onboard computer system from Carnegie Mellon University drove a van all but 52 of the 2849 miles from Washington, DC to San Diego, averaging 63 miles per hour day and night, rain or shine;
Computer chess: Deep Blue, a chess computer built by IBM researchers, defeated world champion Gary Kasparov in a landmark performance;
Mathematical theorem proving: A computer system at Argonne National Laboratories proved a long-standing mathematical conjecture about algebra using a method that would be considered creative if done by humans;
Scientific classification: A NASA system learned to classify very faint signals as either stars or galaxies with superhuman accuracy, by studying examples classified by experts;
Advanced user interfaces: PEGASUS is a spoken language interface connected to the American Airlines EAASY SABRE reservation system, which allows subscribers to obtain flight information and make flight reservations via a large, on-line, dynamic database, accessed through their personal computer over the telephone.
In a 1977 article, the late AI pioneer Allen Newell foresaw a time when the entire man-made world would be permeated by systems that cushioned us from dangers and increased our abilities: smart vehicles, roads, bridges, homes, offices, appliances, even clothes. Systems built around AI components will increasingly monitor financial transactions, predict physical phenomena and economic trends, control regional transportation systems, and plan military and industrial operations. Basic research on common sense reasoning, representing knowledge, perception, learning, and planning is advancing rapidly, and will lead to smarter versions of current applications and to entirely new applications. As computers become ever cheaper, smaller, and more powerful, AI capabilities will spread into nearly all industrial, governmental, and consumer applications.
Moreover, AI has a long history of producing valuable spin-off technologies. AI researchers tend to look very far ahead, crafting powerful tools to help achieve the daunting tasks of building intelligent systems. Laboratories whose focus was AI first conceived and demonstrated such well-known technologies as the mouse, time-sharing, high-level symbolic programming languages (Lisp, Prolog, Scheme), computer graphics, the graphical user interface (GUI), computer games, the laser printer, object-oriented programming, the personal computer, email, hypertext, symbolic mathematics systems (Macsyma, Mathematica, Maple, Derive), and, most recently, the software agents which are now popular on the World Wide Web. There is every reason to believe that AI will continue to produce such spin-off technologies.
Intellectually, AI depends on a broad intercourse with computing disciplines and with fields outside computer science, including logic, psychology, linguistics, philosophy, neuroscience, mechanical engineering, statistics, economics, and control theory, among others. This breadth has been necessitated by the grandness of the dual challenges facing AI: creating mechanical intelligence and understanding the information basis of its human counterpart. AI problems are extremely difficult, far more difficult than was imagined when the field was founded. However, as much as AI has borrowed from many fields, it has returned the favor: through its interdisciplinary relationships, AI functions as a channel of ideas between computing and other fields, ideas that have profoundly changed those fields. For example, basic notions of computation such as memory and computational complexity play a critical role in cognitive psychology, and AI theories of knowledge representation and search have reshaped portions of philosophy, linguistics, mechanical engineering and, control theory.
Historical PerspectiveEarly work in AI focused on using cognitive and biological models to simulate and explain human information processing skills, on "logical" systems that perform common-sense and expert reasoning, and on robots that perceive and interact with their environment. This early work was spurred by visionary funding from the Defense Advanced Research Projects Agency (DARPA) and Office of Naval Research (ONR), which began on a large scale in the early 1960's and continues to this day. Basic AI research support from DARPA and ONR -- as well as support from NSF, NIH, AFOSR, NASA, and the U.S. Army beginning in the 1970's -- led to theoretical advances and to practical technologies for solving military, scientific, medical, and industrial information processing problems.
By the early 1980's an "expert systems" industry had emerged, and Japan and Europe dramatically increased their funding of AI research. In some cases, early expert systems success led to inflated claims and unrealistic expectations: while the technology produced many highly effective systems, it proved very difficult to identify and encode the necessary expertise. The field did not grow as rapidly as investors had been led to expect, and this translated into some temporary disillusionment. AI researchers responded by developing new technologies, including streamlined methods for eliciting expert knowledge, automatic methods for learning and refining knowledge, and common sense knowledge to cover the gaps in expert information. These technologies have given rise to a new generation of expert systems that are easier to develop, maintain, and adapt to changing needs.
Today developers can build systems that meet the advanced information processing needs of government and industry by choosing from a broad palette of mature technologies. Sophisticated methods for reasoning about uncertainty and for coping with incomplete knowledge have led to more robust diagnostic and planning systems. Hybrid technologies that combine symbolic representations of knowledge with more quantitative representations inspired by biological information processing systems have resulted in more flexible, human-like behavior. AI ideas also have been adopted by other computer scientists -- for example, "data mining," which combines ideas from databases, AI learning, and statistics to yield systems that find interesting patterns in large databases, given only very broad guidelines.
Moreover, AI has a long history of producing valuable spin-off technologies. AI researchers tend to look very far ahead, crafting powerful tools to help achieve the daunting tasks of building intelligent systems. Laboratories whose focus was AI first conceived and demonstrated such well-known technologies as the mouse, time-sharing, high-level symbolic programming languages (Lisp, Prolog, Scheme), computer graphics, the graphical user interface (GUI), computer games, the laser printer, object-oriented programming, the personal computer, email, hypertext, symbolic mathematics systems (Macsyma, Mathematica, Maple, Derive), and, most recently, the software agents which are now popular on the World Wide Web. There is every reason to believe that AI will continue to produce such spin-off technologies.
Intellectually, AI depends on a broad intercourse with computing disciplines and with fields outside computer science, including logic, psychology, linguistics, philosophy, neuroscience, mechanical engineering, statistics, economics, and control theory, among others. This breadth has been necessitated by the grandness of the dual challenges facing AI: creating mechanical intelligence and understanding the information basis of its human counterpart. AI problems are extremely difficult, far more difficult than was imagined when the field was founded. However, as much as AI has borrowed from many fields, it has returned the favor: through its interdisciplinary relationships, AI functions as a channel of ideas between computing and other fields, ideas that have profoundly changed those fields. For example, basic notions of computation such as memory and computational complexity play a critical role in cognitive psychology, and AI theories of knowledge representation and search have reshaped portions of philosophy, linguistics, mechanical engineering and, control theory.
Historical PerspectiveEarly work in AI focused on using cognitive and biological models to simulate and explain human information processing skills, on "logical" systems that perform common-sense and expert reasoning, and on robots that perceive and interact with their environment. This early work was spurred by visionary funding from the Defense Advanced Research Projects Agency (DARPA) and Office of Naval Research (ONR), which began on a large scale in the early 1960's and continues to this day. Basic AI research support from DARPA and ONR -- as well as support from NSF, NIH, AFOSR, NASA, and the U.S. Army beginning in the 1970's -- led to theoretical advances and to practical technologies for solving military, scientific, medical, and industrial information processing problems.
By the early 1980's an "expert systems" industry had emerged, and Japan and Europe dramatically increased their funding of AI research. In some cases, early expert systems success led to inflated claims and unrealistic expectations: while the technology produced many highly effective systems, it proved very difficult to identify and encode the necessary expertise. The field did not grow as rapidly as investors had been led to expect, and this translated into some temporary disillusionment. AI researchers responded by developing new technologies, including streamlined methods for eliciting expert knowledge, automatic methods for learning and refining knowledge, and common sense knowledge to cover the gaps in expert information. These technologies have given rise to a new generation of expert systems that are easier to develop, maintain, and adapt to changing needs.
Today developers can build systems that meet the advanced information processing needs of government and industry by choosing from a broad palette of mature technologies. Sophisticated methods for reasoning about uncertainty and for coping with incomplete knowledge have led to more robust diagnostic and planning systems. Hybrid technologies that combine symbolic representations of knowledge with more quantitative representations inspired by biological information processing systems have resulted in more flexible, human-like behavior. AI ideas also have been adopted by other computer scientists -- for example, "data mining," which combines ideas from databases, AI learning, and statistics to yield systems that find interesting patterns in large databases, given only very broad guidelines.
Case Studies
The following four case studies highlight application areas where AI technology is having a strong impact on industry and everyday life.
Authorizing Financial Transactions
Credit card providers, telephone companies, mortgage lenders, banks, and the U.S. Government employ AI systems to detect fraud and expedite financial transactions, with daily transaction volumes in the billions. These systems first use learning algorithms to construct profiles of customer usage patterns, and then use the resulting profiles to detect unusual patterns and take the appropriate action (e.g., disable the credit card). Such automated oversight of financial transactions is an important component in achieving a viable basis for electronic commerce.
Configuring Hardware and Software
AI systems configure custom computer, communications, and manufacturing systems, guaranteeing the purchaser maximum efficiency and minimum setup time, while providing the seller with superhuman expertise in tracking the rapid technological evolution of system components and specifications. These systems detect order incompletenesses and inconsistencies, employing large bodies of knowledge that describe the complex interactions of system components. Systems currently deployed process billions of dollars of orders annually; the estimated value of the market leader in this area is over a billion dollars.
Diagnosing and Treating Problems
Systems that diagnose and treat problems -- whether illnesses in people or problems in hardware and software -- are now in widespread use. Diagnostic systems based on AI technology are being built into photocopiers, computer operating systems, and office automation tools to reduce service calls. Stand-alone units are being used to monitor and control operations in factories and office buildings. AI-based systems assist physicians in many kinds of medical diagnosis, in prescribing treatments, and in monitoring patient responses. Microsoft's Office Assistant, an integral part of every Office 97 application, provides users with customized help by means of decision-theoretic reasoning.
Scheduling for Manufacturing
The use of automatic scheduling for manufacturing operations is exploding as manufacturers realize that remaining competitive demands an ever more efficient use of resources. This AI technology -- supporting rapid rescheduling up and down the "supply chain" to respond to changing orders, changing markets, and unexpected events -- has shown itself superior to less adaptable systems based on older technology. This same technology has proven highly effective in other commercial tasks, including job shop scheduling, and assigning airport gates and railway crews. It also has proven highly effective in military settings -- DARPA reported that an AI-based logistics planning tool, DART, pressed into service for operations Desert Shield and Desert Storm, completely repaid its three decades of investment in AI research.
The Future
AI began as an attempt to answer some of the most fundamental questions about human existence by understanding the nature of intelligence, but it has grown into a scientific and technological field affecting many aspects of commerce and society.
Even as AI technology becomes integrated into the fabric of everyday life, AI researchers remain focused on the grand challenges of automating intelligence. Work is progressing on developing systems that converse in natural language, that perceive and respond to their surroundings, and that encode and provide useful access to all of human knowledge and expertise. The pursuit of the ultimate goals of AI -- the design of intelligent artifacts; understanding of human intelligence; abstract understanding of intelligence (possibly superhuman) -- continues to have practical consequences in the form of new industries, enhanced functionality for existing systems, increased productivity in general, and improvements in the quality of life. But the ultimate promises of AI are still decades away, and the necessary advances in knowledge and technology will require a sustained fundamental research effort.
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