This document discusses using artificial intelligence for successful knowledge flow (Kflow) in organizations. It argues that computers are fast and accurate but lack human brilliance, while humans are slow but brilliant - together, AI and humans can be powerful. The document then outlines how AI can contribute to corporate knowledge management by organizing knowledge, facilitating new discovery, and supporting decision-making. It provides examples of how knowledge management is used in practice and argues that AI can help optimize knowledge sources and sharing, as well as support innovation, learning and training.

1. Artificial Intelligence for
Sucessful Kflow
Eunika MERCIER-LAURENT
Knowledge & Innovation Management
Magellan Research Center, Jean Moulin University Lyon 3
eunika.mercier-laurent@univ-lyon3.fr
http://innovation-ecosystems.eu

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Collaborative
Human-Machine Intelligence
Computers are incredibly fast, accurate, and stupid.
Human beings are incredibly
slow, inaccurate, and brilliant. Together they are
powerful beyond imagination.
Albert Einstein

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Corporate Knowledge
Corporate Visibility
Langage naturel
Navigation hypertexte
Corporate Decision
Système expert
Propagation contraintes
Corporate Memory
Banque de
Connaissances
Corporate modeling
Classes/objets
Réseaux semantiques
SI existant

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Kflow
• “Creation, collection, processing and
sharing
of information and knowledge
in an organized and optimized way,
taking into consideration
different activities of an extended
organization as well as needs and
individual and collective motivations of
all participants »

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Contribution of AI
• Thinking (data, knowledge)
• Methods
• Techniques
• Experience

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Evolution of knowledge models

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Knowledge Management
• Tools
• Users
• Management

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KM in PracticeKM in Practice
• User’s activity oriented
– Help desk, diagnostic, decision support
systems
– K capitalization
– “best practice”
– Documents management
– Design (& eco-design)
– Skills & Competency management
– Business Intelligence
– E-learning

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KM in PracticeKM in Practice
• Management oriented
– Innovation process management
– Leadership management
– Sustainability
– Well being

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AI for KMAI for KM
• Organizing and optimizing sources of
knowledge (including connected objects)
• Facilitating creation and discovery of new
knowledge
• Smart finding and share
• Collective knowledge and experience
• Decision support Systems
• e-, m-learning and training
• Support for innovation and e-co-innovation

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Evolution of Business (5D)
• EBN involvement
• Opportunity-based
• High risk
• Value of links
• Virtual teams
• New business models
• Environment as a source of business

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Business Transformation
Collaborative eco-innovation Systems
• Effective knowledge access
• External data exploration (big data)
• Effective opportunity finding
• Risk management
• Eco-design - simulation before doing

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Business Transformation
Collaborative eco-innovation Systems
• Multicultural environment - common
language, translations
• M-working facilities
• RT Learning (e-,m-, by doing..)
• Feedback
• Security
• ..

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Perspectives for Research
• KLego = Reusable knowledge models
(world library?)
• Raisoning techniques (MAS, analogy,
rules, constraint programming,
computational…
• Intelligent learning, teaching and
training
• Complex problem solving

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AI 4.0
• New trends?
• AI 4 Smart City?
• 6D?