CHAPTER 11 INTELLIGENT SYSTEMS IN BUSINESS

1
CHAPTER 11INTELLIGENT SYSTEMSIN BUSINESS
2
Learning Objectives

• Describe artificial intelligence and compare it
  to conventional computing
• Identify the characteristics, structure,
  benefits,and limitations of expert systems
• Describe the major characteristics of natural
  language processing and voice technologies
• Describe neural computing and its capabilities
• Define intelligent agents and their role in IT
• Describe virtual reality

3
Chapter Overview
4
Case Analog Devices Uses Intelligent Systems
to Support Sales

• The Problem

• The Solution

• using an intelligent technology call case-based
  reasoning to improve the customer-company
  communication

• The Results

• quality of the service makes the difference in
  this competitive market

5
Case (continued)

• What have we learned from this case??

• the intelligent system solution was integrated
  with other information technologies (CD-ROM,
  Internet, extranet, search engine) as well as
  with a DSS

6
Intelligent Systems and Artificial Intelligence

• Artificial Intelligence (AI)
• the branch of computer science that deals with
  ways of representing knowledge, using symbols
  rather than numbers, and heuristics, or rules of
  thumb, rather than algorithms for processing
  information
• involves studying the thought processes of humans
• deals with representing those processes via
  machines
• objectives
• to make machines smarter
• to understand what intelligence is
• to make machines more useful

7
Comparing Artificial and Natural Intelligence
8
Conventional vs. AI Computing
9
Commercial AI Systems

• Expert systems (ESs)
• Natural language technology
• Speech (voice) understanding
• Robotics and sensory systems
• Computer vision and scene recognition
• Intelligent computer-aided instruction (ICAI)
• Machine learning
• Handwriting recognizers

10
Expert Systems
Expertise is transferred from an expert to a
computer and it is stored there
11
Benefits of Expert Systems

• Increased output and productivity
• Increased quality and reliability
• Capture of scarce expertise
• Ability to operate in hazardous environment
• Improved customer service
• Human-like intelligence
• Fault tolerance
• Complex problem solving and decision making
• Training capabilities
• Reduction of cycle time and downtime

12
Limitations of Expert Systems

• Limited expertise
• No single correct solution
• Natural cognitive limits
• Narrowly defined subject areas
• Occasional incorrect recommendations
• Limited vocabulary or jargon
• Cost
• Lack of trust by end users
• Biases
• Liability issues

13
The Process of ES
14
The Components of ES

• The knowledge base contains knowledge necessary
  for understanding, formulating, and solving
  problems
• The Blackboard is an area of working memory set
  aside for the description of a current problem
• The inference engine is essentially a computer
  program that provides a methodology for reasoning
  and formulating conclusions
• The user interface in ES allows for user-computer
  dialog usually presented as questions and
  answers, and sometime supplemented by graphics
• The explanation subsystem can trace
  responsibility for conclusions to their source

15
ESs and the Internet/Intranet
16
Other Intelligent Systems

• Natural Language Processing (NLP)
• Communicating with a computer in English or
  whatever language you may speak, instead of
  commands
• Voice Technology
• Voice (speech) recognition and understanding
• allows users to communicate with a computer by
  speaking to it
• Voice synthesis
• the technology by which computer speak

17
Other Intelligent Systems (continued )

• Neural Computing or Artificial Neural
  Network (ANN)
• emulates a biological neural network
• receives information from other neurons or from
  external sources, transform the information, and
  pass it on to other neurons or as external
  outputs
• value useful for pattern recognition, learning,
  and the interpretation of incomplete inputs

18
Other Intelligent Systems (continued )

• Case-Based Reasoning (CBR)
• basic idea adapt solutions that were used to
  solve old problems and use them to solve new
  problems
• an extremely effective approach in complex cases
• used by itself or it can be combined with other
  reasoning paradigms
• used to facilitate and expedite knowledge
  acquisition and information system development,
  enhance learning and training, and generate
  explanations to users of systems

19
Other Intelligent Systems (continued )

• Fuzzy Logic
• deals with uncertainties by simulating the
  process of human reasoning, allowing the computer
  to behave less precisely and logically than
  conventional computers do
• rationale not always a matter of true or false
  or black and white
• creative decision-making processes are often
  unstructured, playful, contentious, and rambling

20
Intelligent Agents (IA)

• Characteristics of Intelligent Agents
• capability to work on their own (autonomy)
• exhibition of goal-oriented behavior
• transportable over networks (mobility)
• dedication to a single repetitive task
• ability to interact with humans, systems, and
  other agents
• inclusion of knowledge base
• ability to learn

21
Applications of IA

• Application

Description
22
Virtual Reality (VR) Emerging Technology

• What Is Virtual Reality (VR)?
• most common definitions interactive,
  computer-generated, three-dimensional graphics,
  delivered to the user through a head-mounted
  display
• technical definitions environment and/or
  technology that provides artificially generated
  sensory cues sufficient to engender in the user
  some willing suspension of disbelief

23
Applications of VR

• Application

Description
24
Ethical and Global Issues

• Ethical and Society Issues Related to Intelligent
  Systems
• The Laws of Robotics
• Hal and Dave
• computer may refuse human orders
• Virtual Reality
• peoples behavior in a world where the
  distinction between the real and the virtual is
  unclear
• Privacy

25
Ethical and Global Issues (continued )

• Legal and ethical Issues
• what is the value of an expert opinion when the
  expertise is encoded in a computer?
• who owns the knowledge in a knowledge base?
• should royalties be paid to experts who provide
  the knowledge to ES, and if so how much?
• can management force experts to contribute their
  expertise?
• who is an expert? what if several experts
  disagree?

26
Ethical and Global Issues (continued )

• Global Aspects of Intelligent Systems
• Foreign trade
• Advising companies on how to exploit
  opportunities related to the NAFTA agreement
• Foreign exchange transactions
• FS System advises on trading currencies of
  various nations
• Employee training
• Intelligent systems cut the time to train
  employees online before they go to a foreign
  country
• Weather forecasting
• Climatic expert systems provide long-range
  climate forecasts
• Automatic language translations
• Intelligent systems translate languages,
  including voice in telephone conversations

27
Whats in IT for Me?

• For Accounting
• Intelligent systems are used extensively in
  auditing to uncover irregularities, uncover and
  prevent fraud
• For Finance
• Intelligent systems can facilitate the use of
  spreadsheets and other computerized systems used
  in finance and can help in reducing fraud in
  credit cards, stocks, and other financial markets

28
Whats in IT for Me? (continued )

• For Marketing
• Intelligent systems are partially useful in
  mining customer databases and predicting customer
  behavior
• For Production/Operations Management
• Expert systems were developed for tasks ranging

29
Whats in IT for Me? (continued )

• For Human Resource Management
• Intelligent agents can find resumes of applicants
  posted on the Web and sort them to match needed
  skill and can facilitate training and to manage
  fringe benefits programs
• Expert systems are used in evaluating candidates
• Neural computing is used to predict employee
  performance on the job and to pre