Squared Outline: Collective Knowledge

 Collective knowledge is the outcome of a twofold transformation:

Such organizational learning capability can be represented by a quadrant crossing the kind of agent (people or systems) with the kind of knowledge (implicit or explicit).

Collective Intelligence

Transitions from implicit to explicit knowledge can be achieved at individual and collective levels:

  • Between people and organizations, it’s typically done through a mix of experience and collaboration (a)
  • Between systems and representations, it’s the nuts and bolts of Machine learning and Knowledge graphs technologies (b)
  • Between people and systems, learning relies on the experience feedback achieved through the integration of ML into the OODA loop (c)
  • Between organization and systems, learning relies on the functional distinction between judgment, to be carried out at the organizational level, and observation and reasoning, supported by systems (d)

Such organizational integration will ensure:

  • Knowledge based collaboration
  • Incremental and smooth learning curves
  • Learning driven by people experience and feedback from systems

The integration of learning at the enterprise level finds its raison d’être with the accountability (organization) and traceability (systems) of decision-making and reasoning processes.


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