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What would happen if the world had a shared and open source collective intelligence-creation network?  We want to find out. 

 

 

O P E N   G A R A G E   D O O R  D E V E L O P M E N T   /   <join>

Task: Design and build a scalable, user-owned collective intelligence AI

Step 1: IDENTITY.  Create your Totem identity-manager and become a partner in a network of intelligence. <here>

Step 2: CONCEPT GRAPHING.  Elicitation (intelligence), collecting intelligence information from people as part of human intelligence (intelligence collection) Elicitation technique or elicitation procedure, any of various data collection techniques in social sciences or other fields to gather knowledge or information from people. <here>

Step 3: LEVERAGE.  Use a network of linked concept graphs and the people who created them to solve problems together! <here>

A R I S T O T L E  2.1 ,   elicitation in a box  

MEANS

METHOD

OUTCOME

METHOD

METHOD

METHOD

SERVICE

PURPOSE

narrative

path

culture

leverage

ADMINISTRATION OF SHARED VALUE

Knowledge and the ability to use it wisely are our greatest resources. They are foundational for building societies that are sustainable and equitable. We believe these resources are being diverted, throttled, and taxed wherever possible making them inaccessible or unaffordable to most people.

Aristotle 2.0 is a small piece in a puzzle that encompasses an entire ecosystem of interlocking modules which are designed for a singular purpose: to make knowledge markets fair and equitable and for the creators of data and intelligence to interface without interference.

To that end we have designed a knowledge market map >>>>

which shows the major components of a collective intelligence marketplace.

Activity within any section of this map enriches all of its parts.

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IT BEGINS WITH KNOWING WHAT'S WHAT

In a network, everyone has vast reservoirs of unique knowledge, most of which cannot be reliably accessed by traditional approaches.

Sense Collective recognizes the opportunity to organize groups who already work together to enrich data through ongoing processes of their work, conversations, and activities.

 

Example:

A community environmental group that meets on FB and raises money every year, and does beach cleanups, and lobbies for local environmental bills, this group is already generating massive value from their work in the form of the data and conversations that they are having, and the special, local knowledge that they understand better than anyone else.  That is not just collateralizing static data, enriched by a group but also recording the associative trails of SMEs licensed as subscription services and organizing top-level schemas and taxonomies which make it easy for others in a similar context. Solutions as searchable collections.

CONTEXTUAL KNOWLEDGE MAKETS

Intelligent matching of knowledge market participants and contextual knowledge repository design allow for the creation of self-sustaining, highly specialized knowledge channels that allow for knowledge seekers and knowledge creators to collectively invest in the development and delivery of decision support systems.

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