Enhancing Knowledge Management Systems with Cognitive Agents

1. Enhancing Knowledge Management Systems with Cognitive Agents Journée de recherche de l’AIM, France, 26 March 2004 Thierry NABETH, Albert A. Angehrn, Claudia Roda INSEAD CALT – The Centre for Advanced Learning Technologies, Fontainebleau, France

2. Situation • Many of the approaches proposed until now for managing knowledge were too narrow (knowledge = only document) and often mainly driven by technologies. As a consequence many of them have failed. • Yet, the Management of Knowledge still represents a critical challenge in all sectors (many pressures to do more with less) and at all the levels (organisation, group, individual). • New approaches have appeared, «promising» to change this situation (learning networks, ontology, knowledge ecology, personalization, etc. … and agents).

3. Objective of this presentation • Objective of this presentation • To present on how cognitive agents can help in the design of the next generation knowledge management systems better able to support the Knowledge intensive organizations at the organizational, group and individual level.

4. Structure of this presentation • Analyse the reasons for the relative failure of Knowledge management system. • Indicate the direction for the next generation knowledge management systems. • Present the concept of the cognitive agent. • Indicate how cognitive agent can help in the design of this next-generation knowledge management systems. • Next steps

5. Analysis of the failure Why knowledge management has not (yet?) fulfilled the expectations

6. The reasons of the failure: • The Reasons of the failure: • A two narrow technological vision (let’s create a big database; it is just a matter of tools). • A too shallow and passive support of the knowledge processes (KM should include support for K-exchange, K-use, K-stimulation, cultural transformation, etc.). • A user not enough in control (empowerment?). • An under-estimation of the importance of the Human factors (resistance to change, social dynamic aspects, etc).

7. Some Myths to be challenged • Knowledge is only in the document. The perfect Knowledge Management system is a big database system that will have captured all the knowledge of the organization. • Universality. The more general, powerful and complete the solution, the better (let’s provide the maximum of functionalities). • Social interaction spontaneously «emerges» once you have provided the adequate communication infrastructure. • People are self motivated and are eager to adopt new processes if this help the organization to become more efficient.

8. A vision for better Knowledge Management Systems What are the needs, What are the solutions

9. A vision for the future: (the needs) • The needs: • Encompassing all the processes (identification, capture, acquisition, exchange, use, stimulation, etc.), knowledge sources (including tacit knowledge), and the different categories of users. • A deep and active support of the knowledge processes (high level active & cognitive objects reflecting the mental models of the users). • The empowered the user (the user is in control), and taking into account his/her specificity. • Addressing the social factors, managing the change (cultural transformation).

10. A vision for the future (some directions) • Next Knowledge Management Systems some directions: • (1) provide tailored (personalised) support to the users (taking into account the specificity / context) • (2) better address the management of tacit knowledge, and in particular the social aspects of knowledge exchange. • (3) provide to the users with high-level (cognitive) interface and actively engage actively them in the dynamic of knowledge processes (stimulation).

11. Executing the vision • The «tools» of the vision • personalize the interaction in order to maximize the value / impact of this interaction. Reduce information overload. • provide mechanisms supporting deeply the social and human dimension. • use active mechanisms proactively engaging the individual & group into knowledge activities.

12. The agents Defining the concepts

13. The agents (defining the concept) • What is an agent • Perception, autonomy, social ability,proactiveness • The reasons for using agents • Designing complex active applications (distributed control, integrated with human organization) • Agent technologies & approaches • Middleware but also models have been developed • Application of agents in Knowledge Management • Automating search, mediation mechanisms etc.

14. The agents (definition) • Characteristic of agenthood (Wooldridge & Jennings) • Perception of the environment • Autonomy (self-direction) • Social ability (capability to interact with other entities) • Proactiveness (initiative) • Other properties (not mandatory): • Consciousness, intelligence, adaptability, etc.

15. The cognitive agents • Cognitive agent: Agent + some properties of consciousness: • Belief • Desires • Intentions • Believability • Maintain a high level state of the environment • Explicit semantic • Why to use cognitive agents: • They are able to support more deeply the human process • The concept they manipulate are more similar to the human concept.

16. The cognitive agents (architectures) • Pioneer: The SOAR system (Laird, Newel & Rosenbloom) • Very complex • Rule based (mainly). • New architectures have appeared: • ConAg, Boid, ICARUS, etc. • Further develop agent «brain» model (BDI, etc.) • Evolutivity/adaptability/learning sometime built-in (ecology of behaviours) • Semantic web oriented (ontology, semantic network, …)

17. Cognitive agents for Knowledge Management Or how they can contribute to design KM systems more personalised, socially aware and cognitive&active

18. The cognitive agents for KM activities • Social agents • The role of these agents is to support the social dimension. (group level). • Social translucence agents, facilitators, aggregators, etc. • Process agents • Support the knowledge management processes of the organization. (organisational level) • Automating the tasks, etc. • Personal agents • Support the knowledge worker. (individual level) • Supporting the individual

19. The cognitive agents for KM activities (illustrations) • Social agents • EdComNet project (supporting learning network in municipalities – for the citizen). • Social translucence agents, group forming agents, etc. • Process agents • KInCA (Agent for transforming behaviours & attitudes – towards the knowledge sharing organization) • Pedagogical agents intervening in the activity. • Personal agents • Ontologging • Ontology-based User modelling and agents for KM.

20. Next steps Where are we now? Where are we heading to?

21. When will these mechanisms be available? • Some of them already present (social translucence, social collaboration filtering, interface agents, etc.). • Some other one are currently attracting a lot of attention today (personalization / contextualization in particular in e-learning, personal agents, …). • Other are still in the Labs (emotional agents, agent for decision making, etc.).

22. Annexes Myths to be challenged The technical mechanisms

23. Annexes 1 Some myths to be Challenged

24. Some Myths to be challenged • Knowledge is only in the document. The perfect Knowledge Management system is a big database system that will have captured all the knowledge of the organization. • Universality. The more general, powerful and complete the solution, the better. (let’s provide the maximum of functionalities to every user). • Social interaction spontaneously «emerges» once you have provided the adequate communication infrastructure. • People are self motivated and are eager to adopt new processes if this help the organization to become more efficient.

25. The reality (knowledge = only in the documents?) • A very important amount of Knowledge is not (and never will be) present in documents*. • An important role of KM Systems should be to provide mechanisms that support the circulation & exploitation of the tacit knowledge. (the ultimate objective of KM is that K is used, not that it is stored!). • *Note: Why tacit knowledge will remain important? • Because making the knowledge explicit is an heavy operation (expensive), which can hamper the flexibility of the organization. • Because Knowledge can sometime be difficult to formalize and risks exist of overcoming the formalization of important pieces of knowledge. • Because people are lazy, and capturing knowledge is often boring.

26. The reality (the more the better?) • People are getting overwhelmed by information overload (think of email for instance). • KM systems should not try to provide to all users every functionality, and to deliver all the knowledge that is potentially useful, but rather to provide the individuals with what they really need. • KM systems should develop a very deep understanding of the user (including his cognitive style and his working context) in order to be able to deliver him relevant (according to his profile and context) knowledge and support to his work.

27. The reality (communication tools social interaction ?) • Many of the first generation virtual community systems (computer supported knowledge networks in which the tacit knowledge flows) have died due to the belief that the availability of communication tools (bulletin boards, etc.) was a sufficient condition for social interaction. • The process of creating, growing & maintaining virtual community systems is complex and involve many human factors. KM systems should explicitly address and support the social dynamic aspects (creation, growth & maintenance).

28. The reality (people are self motivated?) • Many People are satisfied by the status-quo. They only change their practices when they have no other choice, or at least after they have well evaluated the risks and have some guaranty that they will received a minimum of support in this transition. • KM systems should actively help and stimulate the users in engaging in a continuous knowledge management process and exchange. • Also, people are different and are in particular driven by different motives. Systems should take this into account. • Note: the limitation of this “self motivation” is in particular visible in the difficulty of making people to share their knowledge.

29. Annexes 2 Executing the vision of designing personalized, socially aware and cognitive & active Knowledge Management systems

30. Executing the vision • The «tools» of the vision • personalize the interaction in order to maximize the value / impact of this interaction. Reduce information overload. • provide mechanisms supporting deeply the social and human dimension. • use active mechanisms proactively engaging the individual & group into knowledge activities. • + Tools are not enough. Provide methodology.

31. Personalising the interaction • Taking into account the context. • Take into account the characteristic of the users (role, users’ current working activities, preferences, cognitive style, etc.). • Personalising the interactions according to the organizational context (priorities, goal orientations). • Note: Privacy issues • However, better knowing people also brings the possibility to better serve them

32. Personalising the interaction (2) • Technologies & Researches conducted in this direction • Key technologies used: Ontology (modelling the user, the work context, the organization) and AI (matching) • Standards: e-Learning standards, HR-XML, identity representation, etc. • Example of works in this direction: • Ontology-based KM, (deep user modelling via ontology) • next generation e-learning systems able to take into account the context

33. Supporting the social dimension • Key concepts & means. • Supporting different modes of Communication (synchronous, asynchronous). • Social translucence: Making the social activity visible (social pressure, trust building, motivation, etc). • Deep support for the social processes: facilitation, recommender & opinion, group formation. • Managing the cultural transformation (i.e. attitude transformation for sharing knowledge), incentives etc.

34. Supporting the social dimension (2) • Technologies & research • Communication tools (mail, bulletin board chats, etc.), … Virtual community systems. • Social translucence & navigation tools. Provide real-time indicators of the social activity (who contributes, who read, what are the knowledge element the most accessed, social network visualization, etc.). Analysing digital trace. • Advanced coordination tools (technical or not technical). Example: moderation, facilitation, structure, etc. • Change management (transforming people attitude).

35. Deep & Proactive support for knowledge activities • Technologies & research • High-level (cognitive) knowledge objects. Ontology are used to help to manipulate concepts familiars to the one used by the knowledge worker (people, projects, topics etc.) • Serendipity & in context search (navigation). (versus search engines) • Personal artificial agents that develop a deep understanding of the user and intervene. Stimulus agents, KInCA project (change management)

36. Deep & Proactive support for knowledge activities (2) • Technologies & research • Agents that exploit the social traces to intervene proactively and stimulate the social activities. • Electronic circulation folders (BSCW) • Interactive experiences (role playing & multi-users virtual reality) • Etc.