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How Artificial Intelligence is helpful in Business Analysis

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Knowledge Engineering 2017 The Uses of Artificial Intelligence in Business By Thomas B. Cross © 1 Knowledge Engineering 2016 "This text is meant to plant the seeds of knowledge about a young but growing new field. In the pursuit of this new technology, it is important to remember that humanism cannot be denied..." —from the Introduction to Knowledge Engineering No matter who you are or what you do, Knowledge Engineering is a book you must read to understand the vast technological advance- ments coming your way—advancements that will impact how you do business... how you make decisions... how you communicate... how you live. It's your personal guided tour into the latest trends, issues, problems, challenges, and promise of our technological past, present, and future. Beyond mere theory and speculation, you'll see firsthand the very real developments in Knowledge Technology Artificial Intelligence and Expert Systems Visualization Knowledge Networking Systems. © 2 © 2017 – TECHtionary Corporation All Rights Reserved NOTE: This was originally published is now being updated and re-written. As such, many of the “date-sensitive" references may not be relevant now, however, many of the fundamental concepts are as relevant today as they were more than twenty years’ ago. Contents Preface / 1. Trends in Knowledge Engineering / 1 Introduction / 2 Knowledge Engineering Limitations and Possibilities / 3 Information Technology in Business Management / 4 Management Styles and Information Technology / 5 Management Sources of Information / 7 Information Processing / 9 Information Processing Innovation / 10 Multidimensional Management Systems (MMS) / 13 Computer-Aided Decision-Making (CAD) / 15 Organizational Marketing / 17 Virtual Management (VM) / 19 The VM Manager / 23 Users as a Key Factor in VM / 24 Steps Leading to Virtual Management / 25 © 3 Management Operation Centers and VM / 26 Virtual Management Activities / 27 Benefits of Virtual Management / 28 Computer-Aided Management and Communications / 29 Matrix Organization / 30 Communications Technology and Management / 32 Group Decision-Making and Information Technology / 34 Summary / 36 Endnotes / 36 vii © 4 VMi KNOWLEDGE ENGINEERING 2. Issues in Knowledge Engineering / 37 Introduction / 38 Problem-Solving Strategies / 38 Gaming as a Business Strategy / 40 Models of Reasoning / 42 Guessing / 45 Practical Limits / 46 The Systematic-Intuitive Approach / 47 Channels of Distribution or Span of Control / 47 Real Time: Can Machines Think? / 49 Language and Perceptual Models / 51 Understanding / 53 Summary / 54 Endnotes / 54 3. Expert Systems / 55 Introduction / 56 What if? / 57 Expert Torque / 58 Standards / 59 Inference, Reasoning, and Knowledge Acquisition / 60 Harvesting Expertise / 63 Heuristics and Mathematical Models / 64 Data Base Management Formats / 68 Parsing / 71 Language Mapping / 72 Expert Systems and Artificial Intelligence / 74 Knowledge Versus Reasoning / 74 Expert Systems: A Definition / 75 Designing an Expert System / 77 © 5 CONTENTS IX AI and Commonsense Reasoning / 78 Reasoning Horizons / 80 AI Fantasies / 83 Scientific Methods / 83 Heuristics as Hypotheses / 85 Metaphors / 86 Natural Languages / 88 Natural Languages and Understanding / 90 Language Development / 93 Nodes and Languages / 94 Infinite Structures / 95 Summary / 97 Endnotes / 98 4. Visualization Systems / 99 Introduction / 100 Conceptual Information Processing / 101 Spatial Reasoning / 103 Communication Theory Versus Information Theory / 104 The Theory Bake-Off / 105 Entropy / 106 Machine Intelligence Technology / 107 Summary / 109 Endnotes / 109 5. Artificial Intelligence / 111 Introduction / 112 AI Systems and Variables / 113 The Effective Procedure Model / 114 Simple Becomes Complex / 118 © 6 KNOWLEDGE ENGINEERING Gaming / 119 Gaming Models / 121 Robotics / 124 Architecture for Intelligence / 125 Levels of Interaction / 126 Virtual Processing / 129 Parallel Connections—Liveware / 131 Summary / 133 Endnotes / 133 6. Knowledge Networking Systems / 135 Introduction / 136 Life in the Electronic Fast Lane / 137 Organizational Communications / 139 Communication Channels / 140 Human Interactions / 140 The Onset of Electronic Communications / 141 Nature and Types of Messages / 146 Organizational Relationships / 147 Organizational Intelligence System / 148 Corporate Management / 149 Organizational Networking / 150 Decision-Making / 150 Data =k Information / 151 On-Line Idea Exchange / 151 The Importance of Time / 156 Neural Networks / 159 Delphi—"On-Line" Decision-Making / 161 Knowledge Acquisition / 162 Learning Systems / 163 Knowledge Networking Features / 164 © 7 CONTENTS XI Communications Networks / 166 Summary / 167 Endnotes / 168 7. "Real World" Applications—Metal Models / 169 Introduction / 170 Classical Examples / 170 Mechanization of Knowledge / 172 Ergonomics / 173 Modeling States of Mind / 174 The Machine's State of Mind / 175 Model Building and Ambiguity / 175 Business Applications / 177 Thought Processing—Sales and Marketing / 180 Field Service Management / 187 Project Management / 188 Summary / 188 Endnote / 189 8. Future Trends in Knowledge Engineering / 191 Introduction / 192 Tactical and Strategic Considerations / 192 Methodologies / 193 Risk-Handling / 196 Business Strategy Analysis / 197 Monitoring and Environmental Tracking / 199 Corporate Culture and Strategic Alliances / 201 © 8 XII KNOWLEDGE ENGINEERING Anticipation Technologies / 202 Body Watcher / 203 Career Path / 204 Beyond the Information Age / 209 Future Management / 210 Summary / 211 Endnotes / 211 Afterword / 213 Glossary / 217 Bibliography / 237 Index / 257 © 9 © 10 Limits of Liability and Disclaimer of Warranty The author and publisher of this book have used their best efforts in preparing this book and the programs contained in it. These efforts include the development, research, and testing of the theories and programs to determine their effectiveness. The author and publisher make no warranty of any kind, expressed or implied, with regard to these programs or the documentation contained in this book. The author and publisher shall not be liable in any event for incidental or consequential damages in connection with, or arising out of, the furnishing, performance, or use of these programs. Trademarks Apple is a trademark of Apple Computer, Inc. CROSS/POINT is a trademark of Cross Information Company. IBM, IBM PC, IBM PCjr are trademarks of International Business Machines Corporation. KnowledgeWare, Information Engineering Workbench, Knowledge Coordi- nator, SAS, Focus, Decomposition Diagrammer, Entity Diagrammer, Data Flow Diagrammer, Entity Diagrammer, Data Flow Diagrammer, Data Designer, Action Diagrammer, and Information Planner are trademarks of KnowledgeWare, Inc. Lotus 1-2-3 and Symphony are trademarks of Lotus Development Corpora- tion. Personal Consultant and Explorer are trademarks of Texas Instruments. © 11 Preface In the beginning of any project there is a spark of inspiration that leads one to pursue the unknown. For the past five years, considerable research has taken place in the field of human-made machines that act or peform functions like humans. The goal of this book was to do the following: 1. Address the underlying problem that management and people are at the center of all concerns in the use and abuse of technology; 2. Recognize that communication and understanding are the limiting factors in the development of artificial or machine-based technologies; 3. Understand that technology has a social function as well as an analytical function; 4. Cope with the limitation that present technology is hardly more advanced than the Model T was in its time period and the technologies that will emerge even only 10 years from now will be as dramatically different as the jet airplane is from a candle. Chapter 1, "Trends in Knowledge Technology," examines communications and information technology in business and business management. Topics include: the move away from the pyramidal business approach; the development of virtual management, which stresses the incorporation of new technology with humanistic concerns; the multidimensional management system which recognizes the individual employee as a data base management system in itself; and computer communica- tion, networking, and computer-aided management. Chapter 2, "Issues in Knowledge Technology," takes a look at various problem-solving strategies for use in business management, the limits of information in a machine as well as humans, the concept and limitations of time in business decision-making, and language as it relates to understanding. Important to this chapter is the emphasis on human/machine relations and how they work together, rather than deciding which is better than the other. An overview of expert systems, Chapter 3, defines and explains the various aspects of this science, which is considered both a part of, and a separate entity from, AI. With an emphasis on reasoning about the knowledge underlying human expertise, as opposed to the emphasis on knowledge itself that characterizes AI, "Expert Systems" examines the need for establishing standards; inference, xvii © 12 XVIII KNOWLEDGE ENGINEERING reasoning, and knowledge acquisition; commonsense reasoning; and natural lan- guages. Chapter 4 reviews visualization systems, systems capable of providing simu- lations or models of the physical world. Still in an early development stage, visualization systems, their current status, and potential are examined. A detailed look is taken at computer-aided programs and the current state-of-the-art in such systems. Specific topics in "Visualization Systems" include conceptual information processing, spatial reasoning, and communication and information theories. Chapter 5, "Artificial Intelligence," provides a new look at AI. Most important are some of the philosophical developments that laid the groundwork for AI. Robots, as opposed to machines with intelligence, are also studied. This chapter concludes with a discussion of an architecture for intelligence. Here, the need for standards, an idea first introduced in Chapter 3, is reemphasized, and virtual processing, a mental gaming process that "devises ways to probe and enhance the abilities of both the brain and the machine," is introduced. Knowledge networking systems are the subject of Chapter 6. Recognized as the technology that will probably cause the most dramatic change in business and business management, these systems are studied in relation to organizational communication and corporate management. Topics in "Knowledge Networking Systems" include human interaction, perception, organizational relationships, orga- nizational networking, decision making, and on-line idea exchanges. Chapter 7, "Metal Models," (that's correct, not mental models) review human mental and machine (metal) modeling, examining ambiguity as one of the most important characteristics that currently separates humans from devices. Thought- processing applications are discussed as they relate to the sales and marketing field, with a particular look at CROSS/POINT®, a program that "supplies the end uses with the building blocks for applications" such as project management, software management, financial planning, marketing, field engineering, and virtually any endeavor that requires manipulation, tracking, and communication of ideas between people over time." "Future Trends in Knowlege Engineering," Chapter 8, concludes the book. Planning and methodologies for the practical applications of knowledge engineering are reviewed; a sample business plan and a short-term information resource management plan are also included. Anticipation technologies are discussed as issues for future users and designers of artificial intelligence. The text ends with a reemphasis of the need for a working relationship between the people and the technology: "The interdependence of technology and behavior cannot be overem- phasized." This text is meant to plant the seeds of knowledge, to instill that sense of wonder about a young, but growing new field. In the pursuit of this new technology, it is important to remember that humanism cannot be denied. Knowledge Engineering is meant to expand "human effectiveness and efficiency," not replace it. © 13 PREFACE XIX Audience This book is intended for those who are faced with management problems of all kinds and would like to think there may be some emerging technologies that can help solve them. Most importantly, for those managers who realize that communi- cation is the most significant part of any working activity. Expected Results This book is to help begin the process of examining how computer-communication technology can help by: 1. Improving and managing time more effectively, 2. Enhancing communications among workers, 3. Lowering and managing costs, and 4. Simplifying management activities. © 14 Chapter 1 Trends in Knowledge Engineering © 15 KNOWLEDGE ENGINEERING Introduction Knowledge engineering (KE) is the application of machine systems to problems of human endeavor. The purpose is not necessarily to develop systems that replace humans, but to allow the use of systems that increase human effectiveness and efficiency. The goal is to encourage humans to do what they do best, whatever this might be, at a time deemed appropriate, and to allow machines to assume the functions best suited to them, such as power saws, mechanical arms, and payroll computers do. KE has many major functions that are discussed here. Some of the fundamental KE issues addressed are: • Ergonomics: Human-machine interaction • Problem-solving and decision-making • Thinking • Communication: People-people, people-machine, and machine-machine • Dark-side problems (fear, conflict, privacy, etc.) • Intelligence • The future These issues are woven throughout the book, supplying the topical glue between distinct discussion areas. Of course, there are other areas related to these issues that are not covered here. It is the purpose of this book to focus on the concepts and issues of KE that will impact on business management strategies, productivity, and the key element of any business—its people. Much like auto mechanics determined to increase engine speed, those of us engaged in research in these areas often fail to present adequate and informative reasons for such enthusiastic pursuit. There are many humanistic and bottom-line reasons for explaining KE and its potential benefits to humankind. Experts, such as Herbert A. Simon, suggest that automation—the augmentation of manpower by machine power—is not the only way in which fundamental research in heuristic problem-solving is likely to contribute to productivity in our society. The most important productive resource in our economy and, very likely, the most important resource for generations to come, is brainpower. We are now learning a great deal about how this brainpower operates—about the processes of human thinking. This subtle, yet key issue is fundamental to any research in KE. It is the pursuit of humanistic uses of technology that offers the greatest challenge and hope for improving productivity and performance, while also improving the quality of life. © 16 TRENDS IN KNOWLEDGE ENGINEERING There are no right or wrong answers, only new problems to be solved. In the past, machines held forth the ability to free people from mundane, tedious, and repetitious tasks and chores. KE promises to facilitate human communication and interaction in ways unavailable or impossible without these systems. Moreover, as these systems become more "intelligent" and more competent, they should gradu- ally acquire the ability to make decisions on their own. The application of self-directed thinking machines offers mind-boggling benefits to education, quality control, and field engineering, to name only a few applications. The development of KE systems that can go places too toxic or otherwise unfit for humans is reason enough to pursue the development of such systems. Knowledge Engineering Limitations and Possibilities We now stand at the foot of the KE mountain, trying to find the most efficient path to the top. Today, the limitations of KE are associated with these general areas: • Computing capability • Problem definitions • Machine languages • Human knowledge ability Of these four areas, the basic horsepower problems of computing "engines" is the easiest to tackle. Computer processing capability has crossed the billion- instructions-per-second barrier. Computer memory now exceeds a billion bits. Communications technology now easily exceeds a billion bits per second using fiber optics. Storage technology now often exceeds a billion bits in a refrigerator, and soon a breadbox; and so on, and so on. Technology has often exceeded most projections and expectations. The processes of how humans approach a problem and how we explain these problems to machines are closely related. Although current human interfaces and programming languages offer vast improvements, still their development remains in the dark ages. The ability of humans to adequately understand, define, analyze, structure, and utilize a machine model is also quite fundamental in its development. People have a hard time identifying problems and reaching solutions in a normal human environment. When you introduce the handicap of trying to explain a problem using today's programming languages, the task is even more difficult. It is, of course, a major fallacy of computer folklore that machines can, in any real way, replace people. However, this does not mean that the machines or systems of the future will not be as intelligent as people. Fears concerning these developments are both © 17 KNOWLEDGE ENGINEERING justified and unjustified. This seeming paradox portends that we can achieve all of our hopes for machines and for humans as well. There is a dark side to computer advancement that corresponds to the dark side of humans. Despite their benefit to people, intelligent machines often become monsters of the id; they can be used in any possible way for war, invasion of privacy, and human destruction. In this case, machines are only extensions of humans and can be used as their warriors. This issue both leads to and stems from the area of human knowledge ability. Humans must recognize their own frailties, inadequacies, and limitations, and how they affect the technology. This is different from the problem definition issue. Humans might not as yet be adequately equipped to understand all of the forces behind intelligence, thinking, or other human mental processes. We might need to evolve a bit further before we can develop machines that can be as intelligent in as many ways as we are. This is not to say that humans will not design, build, and use these "power tools"; rather, it might take a massive effort of machine power, human-machine interface, and new problem-solving methods just to develop machines that have an average IQ. This book is intended to be an intermediate step between understanding the vast complexities of how KE works and realizing the practical effects it has on how we manage our business affairs. We might not need to know one to understand the other, but it could help. Information Technology in Business Management The technology of the office of the future is painfully emerging. As with children who thought they wanted to be firefighters and now are productivity analysts and systems managers, the office is emerging as a new entity. The people and the technology of the organization are restructuring the organization itself around information. Technology is becoming a survival issue in service industries like banking, brokerage, and sales. If you don't use the available technology to supply the same or better service than your competitor, you cannot win in the 1 marketplace. . . - notes Robert C. Hughes, vice-president of business and office systems marketing for Digital Equipment Corporation. Technology is rearranging organizational schemes from a pyramidal approach to one that appears flat. There has been a decrease in the number, and a change in © 18 TRENDS IN KNOWLEDGE ENGINEERING the type, of management levels in the past few years. In essence, they have been declining, reducing, and shifting power throughout the corporation. Management Styles and Information Technology Matrix management was once highly touted, then almost forgotten. As with most products, timing is the absolute key to success. Matrix management's timing was off by a decade. It will re-emerge as information technology-based systems evolve to provide a communications-based organization. Matrix management was the first step in breaking the bonds of the old production organization. It forced managers and staff to look around and work outside of their closed environment. The matrix organizational chart was fluid, allowing projects, task forces, and internal consultants to operate freely. It was far more open to innovation than a reactive mode of waiting for orders from headquarters. Seeking creative business relationships allows people to excel. This management style is needed more than ever today, with an increasingly independent, educated work force that needs to be challenged. Moreover, as the number of skilled workers declines with the "baby bust," X-type (trustless) managers (Y-managers trust their employees) will not be able to function effectively in the old top-down environment. According to Rosabeth Moss Kanten, matrix management: focuses a new style of management, because in the matrix you cannot order peo- ple around, you cannot command them to do what you want. You don't own the people and own their time, so you have to learn to persuade and once you learn that, you have to learn to sell your ideas. And that, by the way, often means that you need better ideas. Of course, you don't need a formal matrix to do that, just 2 an acknowledgement of cross-functional collaboration. Matrix management probably needs a new name. In this book, I use the term virtual management (VM) to describe a management system that thrives on new technology combined with humanistic concerns. VM, like matrix management, relies more on communication than information. It uses both the technology, such as knowledge networking, and the styles of management that keep people "in touch." VM focuses on the human ergonomic issues, recognizing that all organizations are societies of people. Professional/career and life-style associations In a paper I wrote about five years ago, called "Organizational Marketing (OM)," I projected that future society would fall into two major environments: professional/ © 19 KNOWLEDGE ENGINEERING career associations and life-style associations. If people need a job, a professional/ career association helps them find one. In addition, this association creates new opportunities for faster recognition within the company, especially for aspiring women. It is surprising to talk to men and women about their involvement in these professional associations and to discover how significant they are to these people. The other major association is life-style. In Boulder, Colorado, for example, people are more often identified by their life-style than their occupation. Occupation brings in the money; life-style exercises freedom. Life-style associations run the gamut from sports to religion, from exercise to PC users' groups. Indeed, in today's mobile young communities, such associations often play the role of an extended family. Life-style associations are the "soft side" of humanity. Not just in good deeds, like Boy Scouts, but in terms of art, culture, music, and play—the enjoyment of the world around us and its beauty. These associations have existed for thousands of years, mostly involving games and sports. Many emerge and become popular only to die off, and others like chess, the Olympics, and dice exceed the life span of some religions. The distinction between career and life-style associations is blurred. Certainly, there have always been the gypsies, beatniks, hippies, punkers, and other groups of people who seem to only have a life-style. Others, however, such as Mo Siegel of Celestial Seasonings Teas®, have made careers worth millions capitalizing on life-style, and there are hybrid career/life-style associations, such as the Peace Corps. Business associations are used to further the life-style interests of business associates, and life-style associations often provide opportunities for striking up casual business acquaintances. The ability to create associations of any kind is important, and understanding their significance and their role in the corporate culture of tomorrow is critical for corporate survival. Matrix management, virtual management, and professional associations are corporate cultures at work. They must be assimilated into today's operations and tomorrow's planning for corporate growth. IBM is famous for its corporate culture. It is also famous for its success. There is a correlation. Yet one must always be wary of these "cultural" aspects. Remember that the industrial age had its own style, and with the rapid growth of new technology came new labor unions that were not based on corporations but on specific professional abilities and skills. These associations now number in the thousands and include, for example, the North American Society for Corporate Planning, the International Facility Man- agers Association, and one that I helped start—the International Tele/conferencing Association (IT/CA). These associations flourish because they provide members with the information they need and contribute esteem and awards to people who are often unappreciated within their own company. To many, professional associations are at least as important as the company they work for. Corporations need to © 20