MANAGING KNOWLEDGE: KNOWLEDGE WORK AND ARTIFICIAL INTELLIGENCE - E4t
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.1 c h a p t e r 12 MANAGING KNOWLEDGE: KNOWLEDGE WORK AND ARTIFICIAL INTELLIGENCE 12. 12.1 2002 by Prentice Hall & 2012 by Yacoub Sabatin LEARNING OBJECTIVES 1/2 EXPLAIN ORGANIZATIONAL KNOWLEDGE MANAGEMENT (Data/Knowledge) DESCRIBE USEFUL APPLICATIONS FOR DISTRIBUTING, CREATING, SHARING KNOWLEDGE EVALUATE ROLE OF ARTIFICIAL INTELLIGENCE IN KNOWLEDGE MANAGEMENT 12. 12.2 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.2 LEARNING OBJECTIVES 2/2 DEMONSTRATE HOW ORGANIZATIONS USE EXPERT SYSTEMS, CASECASE-BASED REASONING TO CAPTURE KNOWLEDGE DEMONSTRATE HOW NEURAL NETWORKS & OTHER TECHNIQUES IMPROVE KNOWLEDGE BASE * 12. 12.3 2002 by Prentice Hall & 2012 by Yacoub Sabatin MANAGEMENT CHALLENGES KNOWLEDGE MANAGEMENT IN THE ORGANIZATION INFORMATION & KNOWLEDGE WORK SYSTEMS ARTIFICIAL INTELLIGENCE (AI) OTHER INTELLIGENT TECHNIQUES * 12. 12.4 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.3 KNOWLEDGE MANAGEMENT IN THE ORGANIZATION 1/3 KNOWLEDGE MANAGEMENT: Systematically & actively managing and leveraging stores of knowledge in an organization 12. 12.5 2002 by Prentice Hall & 2012 by Yacoub Sabatin KNOWLEDGE MANAGEMENT IN THE ORGANIZATION 2/3 KNOWLEDGE MANAGEMENT: Organizational learning mechanisms Processes to create, gather, store, maintain, disseminate knowledge CHIEF KNOWLEDGE OFFICER (CKO) DIGITAL FIRM: Substantial use of info technology enhances ability to sense, respond to environment 12. 12.6 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.4 KNOWLEDGE MANAGEMENT IN THE ORGANIZATION 3/3 KNOWLEDGE MANAGEMENT: Office Automation Systems (OAS) Knowledge Work Systems (KWS) Group Collaboration Systems (GCS) Artificial Intelligence Applications (AI) * 12. 12.7 2002 by Prentice Hall & 2012 by Yacoub Sabatin INFORMATION AND KNOWLEDGE WORK SYSTEMS INFORMATION WORK: Work consists primarily of creating, processing information DATA WORKERS: People who process & disseminate organization’s ‘paperwork’ KNOWLEDGE WORKERS: People who: Design products or services or Create new knowledge for organization * 12. 12.8 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.5 KNOWLEDGE MANAGEMENT & INFORMATION TECHNOLOGY NETWORKS DATABASES SHARE KNOWLEDGE GROUP COLLABORATION SYSTEMS OFFICE AUTOMATION SYSTEMS ARTIFICIAL INTELLIGENCE SYSTEMS KNOWLEDGE WORK SYSTEMS CAPTURE, CODIFY KNOWLEDGE 12. 12.9 DISTRIBUTE KNOWLEDGE PROCESSORS SOFTWARE CREATE KNOWLEDGE 2002 by Prentice Hall & 2012 by Yacoub Sabatin MAJOR ROLES OF OFFICES (Office Activities) Coordinate work of local professionals and information workers Coordinate work across levels and functions Couple organization to external environment and operators (vendors, customers) * 12. 12.10 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.6 OFFICE AUTOMATION SYSTEMS 1/5 MANAGING DOCUMENTS: 12. 12.11 CREATION STORAGE RETRIEVAL DISSEMINATION TECHNOLOGY: Word processing, desktop publishing, document imaging, Web publishing, work flow managers 2002 by Prentice Hall & 2012 by Yacoub Sabatin OFFICE AUTOMATION SYSTEMS 2/5 SCHEDULING: For individuals & groups: Electronic Calendars (Desktop/Web) Groupware Intranets Events planning SW To To--Do lists 12. 12.12 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.7 OFFICE AUTOMATION SYSTEMS 3/5 COMMUNICATING: INITIATING, RECEIVING, MANAGING: VOICE DIGITAL DOCUMENTS TECHNOLOGY: E-mail, voice mail, digital answering systems, GroupWare, intranets, contact management systems, Web 2.0 applications 12. 12.13 2002 by Prentice Hall & 2012 by Yacoub Sabatin OFFICE AUTOMATION SYSTEMS 4/5 MANAGING DATA (a): Employees, customers, vendors: Desktop databases Spreadsheets User User--friendly interfaces to mainframe databases Cloud/non Cloud/non--cloud based HR Systems 12. 12.14 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.8 OFFICE AUTOMATION SYSTEMS 5/5 MANAGING DATA (b): DOCUMENT IMAGING SYSTEMS: Systems convert documents, images into digital form (e.g.: optical character recognition; microfiche) OCR Systems JUKEBOX: Storage & retrieving device for CDCDROMs & other optical disks INDEX SERVER: Imaging system to store / retrieve document *** 12. 12.15 2002 by Prentice Hall & 2012 by Yacoub Sabatin CREATE KNOWLEDGE 1/4 KNOWLEDGE WORK SYSTEMS: Information systems that aid knowledge workers to: Create Integrate New knowledge in organization 12. 12.16 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.9 CREATE KNOWLEDGE 2/4 KNOWLEDGE WORKERS: KEEP ORGANIZATION UPUP-TO TO--DATE IN KNOWLEDGE: Technology; science; thought; the arts INTERNAL CONSULTANTS IN THEIR AREAS CHANGE AGENTS: Evaluating; initiating; promoting change projects 12. 12.17 2002 by Prentice Hall & 2012 by Yacoub Sabatin CREATE KNOWLEDGE 3/4 KNOWLEDGE SYSTEMS: CAD/CAM: Computer Aided Design/Computer Aided Manufacturing: Provides precise control over industrial design, manufacturing VIRTUAL REALITY: Interactive software creates photorealistic simulations of real world objects (Virtual Reality Modeling VRML)) Language: VRML 12. 12.18 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.10 CREATE KNOWLEDGE 4/4 KNOWLEDGE SYSTEMS: INVESTMENT WORKSTATIONS: High--end PCs used in finance High to analyze trading situations, facilitate portfolio management *** 12. 12.19 2002 by Prentice Hall & 2012 by Yacoub Sabatin SHARE KNOWLEDGE GROUP COLLABORATION SYSTEMS: GROUPWARE: Allows interactive concurrent collaboration, approval of documents, and so on INTRANETS/Web: Good for relatively stable information in central repository TEAMWARE: Group collaborative software to customize team efforts Web/Wikis Web/Wikis. 12. 12.20 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.11 CAPABILITIES OF GROUPWARE Publishing, Replication Discussion Tracking (Legal Documentation) Record Document Management Work Work--flow Management Portability (Formats/Web/Integration) Security Application Development * 12. 12.21 AI 2002 by Prentice Hall & 2012 by Yacoub Sabatin ARTIFICIAL INTELLIGENCE (AI) SYSTEMS: AI: COMPUTER COMPUTER--BASED SYSTEMS WITH ABILITIES TO LEARN LANGUAGE, ACCOMPLISH TASKS, USE PERCEPTUAL APPARATUS ( صناعي ( إدراك صناعي ))إدراك , EMULATE HUMAN EXPERTISE & DECISION MAKING * 12. 12.22 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.12 AI AI FAMILY ARTIFICIAL INTELLIGENCE NATURAL LANGUAGE 12. 12.23 AI ROBOTICS PERCEPTIVE SYSTEMS EXPERT SYSTEMS INTELLIGENT MACHINES 2002 by Prentice Hall & 2012 by Yacoub Sabatin BUSINESS INTERESTS IN AI PRESERVE EXPERTISE CREATE KNOWLEDGE BASE MECHANISM NOT SUBJECT TO FEELINGS, FATIGUE, WORRY, CRISIS ELIMINATE ROUTINE / UNSATISFYING JOBS ENHANCE KNOWLEDGE BASE (Continuous Evolution) Machine vs. Human * 12. 12.24 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.13 AI EXPERT SYSTEMS 1/5 An expert system is subfield of AI, that attempts to provide an answer to a problem, or clarify uncertainties where normally one or more human experts would need to be consulted, usually in a specific problem domain. So. KNOWLEDGE - INTENSIVE CAPTURES HUMAN EXPERTISE IN LIMITED DOMAINS OF KNOWLEDGE (EXPERTISE) 12. 12.25 AI 2002 by Prentice Hall & 2012 by Yacoub Sabatin EXPERT SYSTEMS 2/5 KNOWLEDGE BASE: Model of Human Knowledge RULE RULE--BASED EXPERT SYSTEM : AI system based on IF - THEN statements (Bifurcation ;)تشعبات ;)تشعبات Rule Base: Collection of IF - THEN knowledge KNOWLEDGE FRAMES: FRAMES: Knowledge organizes in chunks based on shared relationships 12. 12.26 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.14 AI EXPERT SYSTEMS 3/5 AI SHELL: Programming environment of expert system INFERENCE ENGINE: Search through rule base – FORWARD CHAINING: Uses input; searches rules for answer – BACKWARD CHAINING: Begins with hypothesis, seeks information until hypothesis accepted or rejected 12. 12.27 AI 2002 by Prentice Hall & 2012 by Yacoub Sabatin EXPERT SYSTEMS 4/5 EXAMPLES: BLUE CROSS BLUE SHIELD: Automated medical underwriting system COUNTRYWIDE FUNDING CORP.: Loan underwriting expert system UNITED NATIONS: Employee salary calculations 12. 12.28 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.15 AI EXPERT SYSTEMS 5/5 LIMITATIONS: Often reduced to problems of classification for different cases Can be large, lengthy, expensive to implement Maintaining knowledge base critical Many managers unwilling to trust such systems (in DSS) *** 12. 12.29 AI 2002 by Prentice Hall & 2012 by Yacoub Sabatin CASE--BASED REASON (CBR) CASE CBR: Process of solving new problems based on the sol’ns of similar past problems. 4 Steps: Retrieve, Reuse, Revise, Retain AI uses database of cases: User describes problem System searches database for similar cases System asks more questions Finds closest fit Modified as required 12. 12.30 * 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.16 AI OTHER APPROACHES NEURAL NETWORKS: Software attempts to emulate brain processes FUZZY LOGIC: Tolerates ambiguity using nonspecific MEMBERSHIP FUNCTIONS GENETIC ALGORITHMS INTELLIGENT AGENTS HYBRID AI SYSTEMS: Combinations * 12. 12.31 2002 by Prentice Hall & 2012 by Yacoub Sabatin NEURAL NETWORKS (ANN) Mathematical/computational model that tries to simulate the structure and/or functional aspects of biological neural networks. ANN consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. Usually it’s adaptive system (changes its structure based on external or internal information that flows through the network during the learning phase) learn usage ANN are usually models complex relationships bet’n i/p’s and o/p’s o/p’s to find patterns in data. App’ns in real life: classifications, ee-learning, DSS 12. 12.32 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.17 FUZZY LOGIC A form of manymany-valued logic To deal with reasoning that is fluid or approximate rather than precise In contrast with "crisp logic“ 0/1 Fuzzy logic variables may have a truth value that ranges in degree between 0 and 1 12. 12.33 AI 2002 by Prentice Hall & 2012 by Yacoub Sabatin GENETIC ALGORITHMS Search technique to find exact or approximate solutions to optimization and search problems. They are evolutionary algorithms (EA) that use techniques such as inheritance, mutation, & selection, and crossover. Use models of organisms to promote evolution of solution * 12. 12.34 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.18 AI INTELLIGENT AGENT 1/2 Autonomous entity which observes and acts upon an environment (it’s agent) and directs its activity towards achieving goals (it is rational). IA may also learn or use knowledge to achieve their goals. The meaning is general (a human being, a community of human beings working together towards a goal). So in CS they are usually referred to as Abstract IA’s 12. 12.35 AI 2002 by Prentice Hall & 2012 by Yacoub Sabatin INTELLIGENT AGENT 2/2 Program with builtbuilt-in, learned knowledge base to do specific, repetitive, predictable tasks for: Individual Business process Software application * 12. 12.36 2002 by Prentice Hall & 2012 by Yacoub Sabatin
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.19 DIKW Hierarchy / Wisdom Hierarchy / Knowledge Hierarchy / Information Hierarchy / Knowledge Pyramid 12. 12.37 2002 by Prentice Hall & 2012 by Yacoub Sabatin c h a p t e r 12 MANAGING KNOWLEDGE: KNOWLEDGE WORK AND ARTIFICIAL INTELLIGENCE 12. 12.38 2002 by Prentice Hall & 2012 by Yacoub Sabatin
CREATE KNOWLEDGE CREATE KNOWLEDGE 11//44 KNOWLEDGE WORK SYSTEMS: Information systems that aid knowledge workers to: Create Integrate New knowledge in organization AQU -Information Systems Fundamentals -Spring 2012. Pg. 12.9 1122.1177
5.1 Managing Azure Active Directory (AD) 5.2 Managing Azure AD objects 5.3 Creating users and groups 5.4 Implementing and managing hybrid identities 5.5 Installing and configuring Azure AD Connect and managing Azure AD Connect 5.6 Performing bulk user updates and managing guest accounts 5.7 Including password hash and pass-through synchronization
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MANAGING CHANGE INSTRUCTOR MANUAL 2015 - 8 - B. What is Managing Change? 1. Definition of Managing Change: (The instructor invites participants to define managing change. The participants are provided space in their workbook for notes. Page 4). Understanding how people adjust to change; and knowing how to negotiate the change process successfully.
RACI Knowledge User Knowledge Author Knowledge Reviewer (Content SME) Knowledge Manager / Coordinator(s) Knowledge Mgt Process Owner 1.0 Identify Knowledge AR 2.0 Author / Update Knowledge AR R 3.0 Review and Update Knowledge C R AR 4.0 Publish Knowledge I I I
3 The TSP Body of Knowledge 7 Competency Area 1: TSP Foundations and Fundamentals 9 Knowledge Area 1.1: Knowledge Work 9 Knowledge Area 1.2: TSP Prerequisite Knowledge 12 Knowledge Area 1.3: TSP Principles 14 Knowledge Area 1.4: TSP Process Elements and Measures 15 Knowledge Area 1.5: TSP Quality Practices 17
Managing the work environment and facilities Code of Practice 2021 Page 4 of 42 Foreword This code of practice on managing the work environment and facilities is an approved code of practice under section 274 of the Work Health and Safety Act 2011 (the WHS Act).
Senior Jazz Combo Wild and unpredictable band of senior musicians in years 10 to 13 for whom anything goes! (Grade 5 with a focus on improvisation). Senior Vocal Group Run by 6th form students for 6th form students, this is an acappella group of mixed voices with high standards of singing. St Bartholomew’s School Orchestra (SBSO) All instrumentalists are expected to perform in the school .
