(Click to Enlarge)

The diagram above shows the relationship between Little AI, Big Ai, and Collective Intelligence. 

Micro- or Macro-processing includes memory and recollection, knowledge creation/learning (delivered or extracted from social knowledge base), knowledge compilation and integration, etc.

The knowledge/question cycle is the core processing function that enables either learning or knowledge creation, depending on the type of question asked.  Questions asked about existing knowledge result in learning.  Questions asked about knowledge that does not exist result in knowledge creation.

 Most AI efforts today are aimed at micro-processing of limited tasks and extracting (e.g., search) and compiling knowledge or gaining meaning from existing knowledge.  A bot is a program or machine with a limited task focus.  Bots tend to mimick or be compared with human capabilities because humans also have a limited task focus.

As micro-bots continue to emerge, some kind of symbiotic relationship between these and humans is forming.  Humans relate through collaboration and networks and micro-bots are essentially injected into this process as human ‘enablers,’ and eventually as human ‘equivalents.’

Knowledge creation and learning both occur at the micro, little AI, level.  When new knowledge is created it must be delivered to the social knowledge base and pass through social acceptance.  With learning, knowledge is extracted from the social knowledge base into the micro bot or human.

Big AI is any machine macro processing performed across all human knowledge.  As computer processing increases in power, it macro-bot approaches could be as common as the micro-bot approachs of today.  The Google search is getting close to a Macro program as it seeks to crawl human knowledge (excluding deep web).  Wolfram Alpha simple program approach tries to take this macro search a bit farther by adding additional ’simple program’ processing to it.  As these offerings improve, retrieval and sophisticated processing will occur across both data and knowledge.

Collective intelligence then, is the ‘process’ wrapper for how humans fit into and navigate the interactions between micro and macro intelligence and innovation (knowledge creation).  It includes how humans and machines network, compile knowledge, and exchange new and existing knowledge.

Today, collective intelligence is more popularly seen as collective human intelligence, but it needs to morph into a model for collective human and machine intelligences.  The diagram above shows the key aspects of this collective intelligence model.

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Social media and ‘Web 2.0′ brings an interaction capability to the web.  It is exemplified by applications such as MySpace, Facebook, and Ning.  The vast majority of Web 2.0 applications today simply serve to connect or network people in their communications.  These create a global shared space where people can create interest groups and become aware of one another’s interests.  One way to think of Web 2.0 is as creating or organizing the ‘interest space.’

Now then, human interests can be trivial, entertaining, serve some purpose, etc., or can be some mixture of these things. 

It may seem overly simplistic, but people need to be interested and motivated before they take action.  That action could be any range from trivial to purposeful, but interest is the start of action.  Interest drives intention, or the intent to take action, and intention drives action.  Purpose is the overarching motivation driven by ‘why’ we intend to take action.  The flow is something along these lines:

Overarching Purpose

• Interest => Motivation/Intent => Action
• Interest => Motivation/Intent => Action

But this goes much deeper in that there are three main kinds of action:

1. Aimless action (without specific goals and objectives)
2. Performance-based action
3. Integral performance-based action.

Aimless actions are self-descriptive.  They occur on a whim or without plans or in a chaotic manner.

Performance-based action is much more rigorous in planning and execution.  Performance-based actions follow this basic flow:

• Formulate long-range plans =>
• Formulate strategy =>
• Set specific goals =>
• Derive objectives from strategy/goals =>
• Make Decisions/Set Operational Plans =>
• Execute objectives (by either saying or doing) =>
• Evaluate outcomes/results

Integral performance-based actions as described above, but the strategy and long-range planning is done in an integral way so that oucomes/results are synergistic across society.  In particular, integral long-range planning allows us to set complimentary courses of action within a physical region or virtual interest group.

Understanding the context above, if we look again at social media, we can understand that this is currently a front-end space with very weak linkages to performance.  It definitely enables connections of people with interests, but does little to move those interests into action.

Enter the civic space.  The civic space is the shared community space outside of institutions and enterprises.  Some people have defined the civic space as the ‘citizen space.’  Physical community assets like the public library, a public art gallery, the county courthouse, or a community center, are commonly associated with the civic space, but this space is much broader. 

Figure 1.1 expands on the role of the civic space in terms of its assets and their public utility.

Figure 1.1 (click to view)

 Civic space assets are public.  As such they can be given, loaned, or civic-owned.

As the table above shows, the Internet is a global civic space asset.  Google and other businesses have devised profit-making mechanisms within the context of the Internet, but by-in-large, the Internet is free.  It is free to the global public and serves as a social information infrastructure for the entire planet. 

‘Free’ can be problematic for businesses and startup business plans when they are attempting to compete by providing paid information.  This is possible if one can argue that paid content is more trusted or higher quality, but generally speaking this kind of competition is a losing proposition.

The concept of Intellectual Property (IP) ownership operates under the assumption that property is plentiful to own. 

Imagine a large new island was discovered in the pacific.  When the pioneers to the island arrive, they set up government over the land and sell property lots to new citizens.  As people arrive the availability of land starts to decrease and price of land starts to increase.  Over time, the island is densly populated and there is no more land left.  The only buying or selling occurs when people leave or die.

Now imagine all human knowledge.  At first, new knowledge was plentiful and access was limited.  When new concepts were formed, the publishing industry flourished, people were granted IP, and they were then allowed to enjoy the fruits of that property.  When the Internet was formed, all global existing knowledge began to converge into a single access point.  Google became synonymous with this access point.  As global knowledge began to converge, ‘newness’ of knowledge became much more rare.  If it is known, someone somewhere, probably published it.  It became relatively easy and ‘free’ to find most concepts fully documented somewhere in this e-space.  Like the example of physical land above, buying property in this new context is a much different proposition.

And then back to social networking on the Internet.  As discussed at the start of this post, social networks create a global shared space where people can create interest groups and become aware of one another’s interests.  One way to think of Web 2.0 is as creating or organizing the ‘interest space.’  This is a ‘free’ interconnectedness.  Tools like MySpace, and Facebook can potentially turn a profit, but it won’t be through content sales.

This free interconnectedness creates a place where people can connect, collaborate, find, reference, innovation, etc.  A free space where communication and transfer of information is global and ubiquitous.

It is exceptionally important to realize that the nature of knowledge is to come together into one, and not to break apart into individual silos.  Random knowledge creation and knowledge working are in direct opposition to knowledge convergence.  In the old days, one could originate a concept, sell it, and move on.  Today,  when one originates a concept, it demands to be placed into a larger context, but that global context (the Internet) is chaotic today at best and does not tie in well to community, business enterprise, or government.

Many people are looking for the next Google to propagate the next evolution of the Internet.  While this technically could happen temporarily with the emergence of Web 3.0, data sharing/crunching and semantic tools, the affect of any new innovation will be short-lived for one simple reason.  Increased knowledge processing power will bring knowledge into one even more quickly.  The only question that will remain is:  “Can a business entity own all human knowledge?”  The answer will, of course, be “No.”

The paradigm we have set out on is starting to break down as the Internet becomes difficult to distinguish from an information garbage dump and global society is almost begging for the next evolution of the Internet to solve its business and social issues.

The Civic Space of the Future

This brings us to the civic space of the future.  The first premise of this space is that it will build around a central social knowledge base.  One knowledge will be stored centrally and owned publicly.

Knowledge creation occurs when individuals question that new knowledge.  A new paradigm needs to be established that is much different from the IP paradigm to reward new knowledge creation, but whatever that looks like, the knowledge itself, after creation, will move to the civic space.

Social networks will move to the civic space as social infrastructure.  The tool itself may be a profit center (as may also be the case with search and Google), but it will necessarily need to revolve around, and interact with, free and ‘one’ knowledge.  The same holds true for educational institutions.  Instruction will likely continue to be a paid service, but the knowledge instructed will not be owned by any specific institution.  This is already evident in public offerings like MIT Open Courseware.

The green and tan circles in Figure 1.2 illustrate this future society-centric relationship.

Figure 1.2 (click to view)

You can also see by looking at Figure 1.2 that the social knowledge base, supported by the civic space networks and education, will flow into business enterprises and industry (movement is from left to right in the diagram).  This is where efforts like civic space innovation, economic development, or technology centers come into play.  Efforts like these will be designed to support enterprise and industry with connections, collaborations, integral plans, or public policy decisions.

The most important transitional element between the civic space and enterprise is integral long-range planning.  This is a long-range look into the future and planning is done across interest groups, institutions, enterprises, government, military, etc.  In other words, we have a global societal long-range plan that balances interests across all groups. 

This integral long-range planning is the ‘missing link’ in modern society.  Capitalistic models encourage individualism and competition.  But without proper social balance, this will mature into social chaos.  Balance plans simply consider all interests.  For example, in making long-range energy decisions things like environment or public health are also considered.  

The following diagram shows a model that might be used to bring long-range planning globally under one umbrella:

http://www.futureindiana.com/index.php?option=com_content&view=article&id=53&Itemid=58

The Enterprise of the Future

But that said, the civic space will stop at integral long-range planning and enterprises will take over with the remainder of performance:

The civic space will  incorporate communication and knowledge, but products, services, and profits will still belong in enterprise.  ‘Tools’ may be a mixture of public and private offerings.  And healty competition for these will continue and key measurements will feed back into integral long-range planning.

Again, looking at Figure 1.2, government will reside over the balancing of interests, the civic space, education, and enterprise.  It doesn’t really matter if that government is communistic, democratic, or a dictatorship.  The only prerequisite is that that government buys into the integral long-range planning process, which will include social ‘give and take.’  We see the start of this model in the concept of carbon trading where the right to pollute is essentially traded across nations with all forms of government.  This kind of concept will continue to expand into other facets of society through integral long-range planning.

In summary, knowledge and the tools that work it, are converging into one.  That transition is breaking down traditional forms of competition, intellectual property ownership, social structures, and is shaking up enterprise.

As we look to the future, no single enterprise will be allowed by society to own all human knowledge.  As such, the civic space will emerge as the clear owner of this one knowledge and the enabler of many opportunities that emerge from it.  It will house public data, the libraries of the future, dialogue, integral long-range plans, and many other key social elements.

Web 2.0 will collapse into the civic space of the future, the global front porch of society, and it will be a key and powerful global resource that enables all social advance and assists governments in the balance of interests across society.

• Energy – Natural, artificial, self-generating; Dependent or independent

Intention

• Intention Source – Human directed, human intention transferred to computer, computer senses and responds to human intention, computer senses to anticipate human intention, computer originated intention (self-aware)
• Intention type – friendly, covert, hostile, or mixed
• Resolve – Resilience of intention

Intelligence collection

• Ability to sense (see, hear, smell, taste, touch).
• Amplified or alternate sensing (e.g., amplified smell for detecton, radar, spectrometer, chromatograph, etc.)
• Ability to collect data and assess the environment
• Ability to track
• Ability to collect knowledge

Covert functions

• Ability to hide or blend or camouflage
• Ability to cloak

Intelligence (ability to store and retrieve knowledge)

• Ability to store and retrieve objectives (Sensing, surveillance, disruption, building, diversion, killing, destruction, payload delivery, etc.)
• Ability to store and retrieve relevant knowledge (e.g. knowledge of threats)

Rational thinking (ability to structure knowledge)

• Ability to formulate mission or project objectives
• Ability to change objectives
• Ability to assess and identify value or threat
• Ability to prioritize objectives and tasks
• Ability to project manage (Cost/timing/resources)

Knowledge creation

• Ability to question.
• Ability to create new knowledge/answer questions from sensed questions/data
• Ability to change objectives based on answered questions
• Ability to transmit intelligence

Language processing

• Ability to interpret language
• Ability to communicate language

Physical Enablers

• Scale – Nano, micro, small, large, macro or distributed • Size – Length, width, height, weight
• Composition – Cyborg or machine, materials
• Mobility – Land, sea, air, space
• Navigation – Ability to sense direction and location
• Balance – Ability to maintain and recover balance
• Engineering Parameters (adapted from TRIZ Methodology) http://homepages.cae.wisc.edu/~me349/lecture_notes/triz_procedure.pdf

Weight

Length

Area

Volume

Speed

Force

Tension, pressure

Shape

Stability of object

Strength

Durability

Brightness

Energy spent

Power

Waste of energy

Waste of substance

Loss of information

Waste of time

Amount of substance

Reliability

Accuracy of measurement

Accuracy of manufacturing

Harmful factors acting on object

Harmful side effects

Manufacturability

Convenience of use

Repairability

Adaptability

Complexity of device

Physical Performance

• Ability to physically execute objectives (Sensing, surveillance, disruption, building, diversion, killing, destruction, payload delivery, etc.) Payload Dimensions (See TRIZ dimensions)
• Destructive
• Disruptive
• Denial
• Crippling
• Invasive
• Poison or biological
• Latent (Trojan horse)
• Amplification of norms – Amplified sound, smell, light, taste, environment (land, sea, air)
• Combinatory

Cooperative performance

• Distribution of effort
• Collective action or cooperation with human
• Collective action or cooperation with other machines
• Swarm behavior
• Self-proliferation

Assessment

• Ability to make objective assessments.
• Ability to make subjective assessments.
• Ability to adjust objectives based on assessment

T Ashok said,

on May 30th, 2009 at 11:01 pm

Say with with use of ‘knowledge creation questions’ we create new knowledge. How does one know the usefulness of knowledge created? The usefulness of a question is about the informations/knowledge it discerns. If you mechanize this, how do you ensure that the questions are good enough to glean useful knowledge?

There are three basic categories of knowledge, 1) Science, which draws data from reality and makes conclusions about it, 2) Technology, which builds knowledge from knowledge (techno-logic) largely to support industry or making things, and 3) Spiritual knowledge, which I use as a broad category for knowledge not tied to this reality or dimension.

In the sense of science, data is gathered from reality and that data is logically assembeled with regard to the aspects of reality being investigated.  Usefulness here is defined in terms of the direction of sensing or in terms of what reality is being investigated.  For example, imagine that a probe was sent to another planet.  The planet itself is a scientific target, or something we want to know about.  A probe is simply a mechanical sensor (that can extend the 5 human senses).  If that probe gathered data about that planet, and conclusions were mechanically generated from that data, then we have new knowledge about that planet, which was our scientific target or the aspect of reality we wanted to know more about.

 Technology is distinct from science in purpose and knowledge usefulness.  The intent of technology is to generate knowledge for industry (for profit or not for profit) and industry makes things.  Knowledge here then must be based on a purpose for the thing made.  Performance is what is used to make things and performance is executed against set objectives.  Things can be made without setting objectives (e.g., art), but the usefulness of making things is in the objective set.  A theoretical knowledge machine could encompass both objective setting and knowledge creation to reach that objective.  And it could also theoretically use, e.g., robotics or molecular manufacturing to make the thing.  In this way, performance and technology are inseparable.  The one is not useful without the other.

 It is also important to note that scientific knowledge may be a catalyst for technological advance.  For example, science may discover a wormhole, but technology may be needed to travel through it.

 Spiritual knowledge might seem like an entirely different proposition, but as we learn more and more about quantum physics the lines between spritual knowledge and scientific/technological knowledge are becomming much thinner.  This gets into things like the validity of our own perception of reality.  Or whether or not we have accurately defined what reality fundamentally is.  Suffice it to say in this post that all three of these knowledge types may ultimately converge in a very powerful way.

We will be talking about futuring, the knowledge/question cycle, and the future of enterprise.If you would like to attend live, see the Mid-Town Brews site for details:  http://www.midtownbrews.net/

Questions are a realized lack of knowledge structure.  Knowledge is logical structure.  Any time there is a realization of a lack of logic a question is formed.

Questions are at the cutting edge of things we know.  There are two kinds of questions, 1) Learning Questions and 2) Knowledge Creation Questions.

Learning questions are asked about knowledge that exists.  Knowledge creation questions are asked about knowledge that does not yet exist.

As such, questions are either the door to learning or the door to new knowledge and social advance.

 As a door to social advance, the question is behind all human achievement, past, present, and future.  By mechanizing knowledge creation questions, human achievement will explode.

• Deepening Recession – 2009 will be a year of continued and deepening recession. We will see more companies close their doors in first half of 2009 and all U.S. states will squarely enter the recession. The states already in recession will see deeper impacts.
  - The Dow Jones declined steadily until a 20% rise in March
  - Unemployment rate was up 8.5% in March
  - Jobless claims highest since 1982
  - The American economy shed 663,000 jobs in March. 
  - Global slump deepening.
• Rise in Crime Rates – There will be a rise in crime rates, especially theft and violent crime.It looked in February as if this was occuring:
  http://www.cbsnews.com/video/watch/?id=2878207n
  But that said, overall, crime appears to be mixed:  http://thecrimereport.org/topics/policing/crime-rates/
  That said though, the part I did not forsee is how the surge in community would diametrically oppose crime rates. See this article on Neighborhood Watches in Miami.
• Inflation – Inflation is more likely now than deflation. Some believe hyperinflation, but I don’t think we’re there yet.
  By the official numbers, the inflation situation seems to be quite good. But according to James Grant (see his BNN interview here), the amount that the Fed has printed over the last three months is 2.1 TRILLION dollars. This is equivalent to an annualized inflation rate of 2009%.
• Seeding - 2009 will be a year of seeding. Seeding Web 3.0 (and beyond) technologies, cottage industries, instant manufacturing, and open-source economic development.
  -  In a Volatile Time, Obama Strikes New Tone
  - A mainstream article on web 3.0: Exploring a ‘Deep Web’ That Google Can’t Grasp.
  - Still a seed, but growing exponentially: Thinking about economic development in new ways.
• Deepening Community – As the bulwarks of traditional society fail, look for a deepening of dependency on the local community. Being connected locally will become much more important and the recession iself could bring on a shift in personal values. Probably the best assignable cause for why crime rates have dropped in some communities.
  See comments above on Neighborhood watches.
• Transformation or Bust – 2009 will see the continued move from hierarchies to networks. The dilemna of traditional newspapers that is coming into the headlines now is exemplary of the pressures that every industry is experiencing. Web sales and media usage will continue to expand and traditional sales and media usage will continue to decline. How well we ‘transform’ will determine the outcome that will surface in Q4 of 2009. We need to sow seeds of change now or the U.S. could experience a permanent decline on the world stage.
  Effectively what has been done is the big bubbles has been extended against Chinese credit. This will prolong the agony, but the long-term solution is a mixture of several emerging economies. Green tech alone is not enough to bring the U.S. out of it’s issues. It’ will likely take a green, deep web, nanotech revolution juxtaposed against a fully revamped and regulated financial system to fix these monstrous issues we are looking at now.
• Rise of Consumer Unions – Consumer unions will continue to emerge and will steadily gain power.
  I don’t think the changes here are substantial enough to say they’ve occured. I still do expect a steady rise of consumer unions over the next 10 years.
• Overall – 2009 overall will be a steady year of somewhat painful transformation. Q4, in th October/November timeframe will be the next big shift, in either a positive or negative direction, depending on how well we transform.
  I still see October/November as the next big shift. The current situation shouldwill either stablize or break down by then. In either case a change will be introduced.