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12. MANAGING KNOWLEDGE

12. MANAGING KNOWLEDGE. Learning Objectives. Explain organizational knowledge management Describe useful applications for distributing, creating, sharing knowledge Evaluate role of artificial intelligence in knowledge management *. Learning Objectives.

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12. MANAGING KNOWLEDGE

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  1. 12. MANAGING KNOWLEDGE

  2. Learning Objectives • Explain organizational knowledge management • Describe useful applications for distributing, creating, sharing knowledge • Evaluate role of artificial intelligence in knowledge management *

  3. Learning Objectives • Explain organizational knowledge management • Describe useful applications for distributing, creating, sharing knowledge • Evaluate role of artificial intelligence in knowledge management *

  4. Knowledge Management • Systematically & actively managing and leveraging stores of knowledge in an organization • Repositories for retaining the collective corporate learning • Reduce the amount of “relearning” in an organization *

  5. Knowledge Management • Office automation systems (OAS) • Knowledge work systems (KWS) • Group collaboration systems (GCS) • Artificial intelligence applications (AI) Datainformationknowledgewisdom *

  6. Information and Knowledge Work Systems • Data workers:people who process & disseminate organization’s paperwork • Information work:work consists primarily of creating, processing information • Knowledge workers:people who design products or services or create new knowledge for organization *

  7. Distribute Knowledge • Office automation systems • Office information systems

  8. Office Automation Systems • Word processing • Desktop publishing • Imaging & web publishing • Electronic calendars • Desktop databases *

  9. Office Automation Systems • Document imaging systems:systems convert documents, images into digital form (e.g., optical character recognition; Microfiche) • Jukebox:storage & retrieving device for CD-ROMs & other optical disks • Index server:imaging system to store / retrieve document *

  10. Office Information Systems • Managing documents • Scheduling • Communicating: e-mail; Voice mail; Groupware; Intranets • Managing data: desktop databases; Spreadsheets; Mainframe databases *

  11. Create Knowledge • Knowledge Work Systems • Knowledge Workers Beware of the hypes

  12. Knowledge Work Systems Information systems that help knowledge workers create, integrate new knowledge in organization *

  13. Knowledge Workers • Keep organization up-to-date in knowledge: technology; Science; Thought; The arts • Internal consultants in their areas • Change agents: evaluating; Initiating; Promoting change projects *

  14. Knowledge Workers • CAD:computer aided design automates creation, revision of products, services • Virtual reality:interactive software creates simulations of real world activities (virtual reality modeling language: VRML) • Investment work stations:special work station to access, manipulate massive amounts of financial data *

  15. Share Knowledge Group collaboration systems • Groupware:allows interactive collaboration, approval of documents • Intranets:good for relatively stable information in central repository • Lotus notes:popular proprietary software; Flexible changes, updates, editing; More secure than intranets *

  16. Capture & Codify KnowledgeArtificial Intelligence (AI) Systems: • Expert systems • Neural nets • Fuzzy logic • Genetic algorithms • Intelligent agents *

  17. ARTIFICIAL INTELLIGENCE NATURAL PERCEPTIVE EXPERT INTELLIGENT ROBOTICS LANGUAGE SYSTEMS SYSTEMS MACHINES AI FAMILY

  18. Business Interests In AI • Preserve expertise • Create knowledge base • Mechanism not subject to feelings, fatigue, worry, crisis • Eliminate routine / unsatisfying jobs • Enhance knowledge base *

  19. Expert Systems • Knowledge-intensive • Captures human expertise • In limited domains of knowledge • Basically a set of in-then-else decision trees *

  20. Expert Systems • Knowledge base:Model of Human Knowledge • Rule-based expert system :AI system based on IF - THEN statements (Bifurcation); Rule Base: Collection of IF - THEN knowledge

  21. Expert Systems LIMITATIONS: • Often reduced to problems of classification • Can be large, lengthy, expensive • Maintaining knowledge base critical • Many managers unwilling to trust such systems *

  22. Other AI Techniques • Neural networks:Software attempts to emulate brain processes • Fuzzy logic:Tolerates ambiguity using nonspecific Membership functions • Genetic algorithms:Use models of organisms to promote evolution of solution • Hybrid AI systems:Combinations *

  23. Dream and Reality • Unsupervised, Self-Adaptive systems that find pattern from chaos • Microsoft’s auto-launch of applications according to email contents • Still must based on human ingenuity to discover the algorithm first • Will never be fool-proof

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