Bruce LaDuke's Blog

My Wife Brenna Singing "Make You Feel My Love"

2012-01-01T12:27:00.000-08:00

Here's my wife Brenna singing Adele's "Maske You Feel My Love:"

The Fundamentals of HyperNet

2011-02-25T10:25:00.000-08:00

HyperNet is an innovation-optimized Internet. There are five layers involved in a global knowledge working fix. HyperNet is the final layer on these fixes.

The first layer is the tranformation of the social grid to a user-centric Internet. See CLOUD, Inc. for a great explanation of what this is and how it works: http://cloudinc.org/

The second layer is establishment of an electronic civic space. Physical and virtual civic spaces have been decimated, especially in the U.S. I think many tech companies are attempting to privatize electronic civic space assets by creating profit centers around them. Personally, I think we need a '.pub' domain that is funded and built through corporate social responsibility programs, volunteers, and national governments. I-Open is a great example of a civic space Internet and the kind of content that belongs there: http://i-open.posterous.com/

The third layer is to fix the mechanics of the copyright system. Copyright is pretty much a global process
today, which is good. It is based on the assignment of five rights. Copyright and "All rights reserved," reserves these rights, creative commons selectively assigns each of those five rights, and public domain is the assignment of those five rights to the public. Our copyright system should formally include all variations of the assignment of these five rights. What is also missing is a metadata standard and global rights registry. The metadata would be centralized and documents would link into it. If, for example, an author changes his or her mind and decides to sell content they had previously made available for free, that should be as simple as changing the metadata in the rights registry. The author shouldn't have to track down every instance of where the document was published to do that.

The fourth layer is to make the patent process more affordable and find a way to prevent reverse re-engineering of patents. It is very difficult for the average person with a prduct idea to secure a patent. The system is designed in a way that makes it easy to keep invention in large corporations and is stifling small business. What is needed is a more robust system around patents that make searches easier, prototyping more affordable, and theft of ideas much more difficult.

The fifth and and most important layer is conceptually challenging, but it is the foundation for a HyperNet. What is needed is to move away from a content proliferation and duplication model and towards a model that rewards creation and cooperation.

Our copyright and publishing system was set up in a world that was just dipping its toes into the information age. They wanted to reward proliferation of knowledge, because, in those days, 'more knowledge was always better.' But today we have matured in knowledge working and are quickly learning that 'more knowledge is not always better' Unrestrained knowledge proliferation, can create massive duplication, information overload, and unnecessary complexity.

Knowledge is one, not many. The current paradigm encourges its proliferation without regard to the logical structure of the whole, which is the social knowledge base. As information technology capabilities increase, we are increasingly able to cut through the chaos and complexity (using semantic tools) to bring knowledge into one. In the next 20 years, it will be possible to remove all duplication from knowledge and download the entire social knowledge base to your laptop. In that kind of world, proliferation of knowledge is counter-intuitive. Why would a person need to proliferate knowledge if he or she can download everything that is known to your laptop? At the same time that which is known across society becomes more evident, that which is not known will take center stage as society starts to realize that this is how it advances itself. The focus will shift entirely to new knowledge formed.

With that emminent future in mind, two things need to happen today. We need to 1) clearly identify and reward knowledge creators, and 2) we should encourage and reward knowledge collaboration and integration and expedite the centralization of knowledge. Over time, this should become the publishing model and the norm, not the exception.

In terms of creation, the concept originator should be declared as knowledge is created and new concepts could be 'awarded' through the same central body that manages copyright, to that individual's profile on the user-centric Internet. This permanently recognizes the 'real' thought leader, not just the politically declared thought leader.

In terms of integration, the copyright laws around compilation need to be broadened to encourage and reward more robust integrative knowledge works, especially those that contribute to the public domain (.pub).

The Six Sigma Achilles Heel

2011-01-04T09:59:00.000-08:00

This post will distinguish the key differences between Six Sigma/Kaiizen and performance consulting approaches and will explain why both are needed.

Both Six Sigma and Kaiizen were born in the manufacturing environment. Kaiizen is more focused on improvements overall and Six Sigma is focused on the elimination of quality defects with a reliance on statistical analysis. In a purist sense, both Six Sigma and Kaiizen methodologies operate in different ways within the same basic framework:

Describe the current process
Detect and measure waste or increase efficiencies (Six Sigma uses statistical method)
Identify improvement(s) to eliminate that waste
Implement improvement(s)
Measure the impact of improvement(s).

But in this context, it is extremely important to ask yourself a few questions like: "What are problems? What is waste? And what is inefficiency? Your answer will determine the effectiveness of your performance improvement approach.

Since both Six Sigma and Kaiizen were born in the context of manufacturing or 'making/producing things,' both tend to see problems as production waste and/or production inefficiencies. In a production context, waste is any unneeded step(s) in a production process and inefficiencies are any unnecessary cost in production processes. Said another way, what step(s) are not needed to make the things you want to make and what money does not need to be spent in the process of making things you want to make?

Enter performance consulting. While performance consulting is typically associated with training, it is really the science of solving any performance problems—and training is only one of many interventions that solve performance problems. In my personal approach to performance consulting, I delineate five categories of performance: 1) thinking, 2) knowing, 3) saying, 4) doing, and 5) enabling. 2 and 3 can be combined, but I use these five as a framework for analyzing what problem you need to solve and also as a framework for performance measurement.

At any rate, in the performance consulting frame, problems are seen in a much broader context than in the Six Sigma/Kaiizen frame. From a performance consulting perspective, problems are anything that prevents objectives from being accomplished, waste is anything that does not contribute to the accomplishment of those objectives, and inefficiency is anything that adds unnecessary cost to accomplishing set objectives.

Because it is centered on accomplishing objectives, performance consulting is a compliment to the performance management process. Companies set strategy, derive objectives from that strategy, and they set out to accomplish those objectives with execution governed by performance management. Performance consulting then, works in this context, seeking to understand why objectives are not being met, or it works to ‘raise the bar’ of performance expectations.

In performance consulting, a performance needs assessment, a performance analysis, or a gap analysis is used to determine what problem needs to be solved. There are many different models for this which I won’t get into in this post, but suffice it to say that performance consulting looks quite extensively and comprehensively at all aspects of performance, not just production or process aspects.

As such, the definition of a ‘problem’ in the performance consulting frame is much broader than it is in the Six Sigma or Kaiizen frame. An organization can use Six Sigma/Kaiizen to remove all wasted and costly steps in a process and still have performance problems that need to be solved. For example, the employees may not be motivated to perform that 100% waste-free, efficient process. Or the employees themselves may have knowledge or skill gaps that prevent them from performing it. Performance consulting looks comprehensively at the performance problem, well beyond the Six Sigma/Kaiizen production mindset.

It is because of this Achilles heel in problem identification, that Six Sigma and Kaiizen, when applied to overall performance within an organization, starts to become ineffective (or even cannibalistic) after about 5 years of implementation. The obvious problems are identified and solved early in the implementation, and the deeper or more abstract problems that remain are best identified through a more sophisticated approach like performance consulting. It is possible to avoid this affect with customization, but most companies squarely hit this wall.

But while both Six Sigma and Kaiizen are weak in terms of problem identification, they are both very strong in terms of actually solving certain problems. Performance consulting has a broader set of interventions than Six Sigma/Kaiizen have, but both Six Sigma and Kaiizen are much stronger than performance consulting when applied to production problems.

The optimal approach is an integral blend of performance consulting and Six Sigma that leverages the strengths and avoids the weaknesses in each. It is critical to establish a comprehensive measurement framework that includes all aspects of performance (think, know, say, do, enable), and then to use each methodology to its strengths, measuring the impact holistically.

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Moved to Blogger

2010-12-09T18:51:00.001-08:00

I've had so much trouble with spam in Wordpress that I'm moving my blog to blogger to see how it goes here. I've removed some of the content because I'm incorporating this into my new book on HyperNet (coming soon).

Empirical and Rational Logic

2010-12-09T18:48:00.003-08:00

Science is knowledge rooted in experience or empiricism.

Technology is knowledge rooted in thought or rationalism.

When we advance science we ‘discover’ reality and move forward our understanding of that reality. When we advance technology we ‘invent’ new reality by rearranging existing reality. When this is applied it becomes industry or the science of making things.

Genetic knowledge is knowledge that is physically inherent to the mind. The age old argument of empiricism or rationalism is solved when one not only realizes that both are valid, but when one also comes to see that these two are the two worlds of knowledge. One is convergent, and one is divergent. One is associated with discovery and the other with creativity and invention. One is building upon observations and one is building thoughts upon other thoughts. And both operate by the same logic, but it simply flows in different directions (convergence and divergence).

On Expertise

2010-12-09T18:48:00.001-08:00

The wrapper for all industrial applications is performance. Only through performance do organizations accomplish their goals.

Capabilities or competencies can exist, but people can choose not to apply them to performance.
Or people can, for whatever reason, not be allowed to use their capabilities or competencies and hence these cannot be applied to performance.
Or people can not have the capability or competency to start with and hence it is never applied to performance.
Or the capability or competency a person has is not needed or required to meet performance objectives, so they are not applied to performance. – etc. (other performance gaps)

In other words, performance is often found struggling against things like apathy, politics, a lack of acceptance, a lack of free flow for ideas, ignorance, or lack of focus. Capability and competency are dormant performance. You could also say that they represent the potential to perform. This potential is not always realized, and in all of these scenarios, motivation is a key factor in shoring up performance gaps.

The other key is cooperation. If individuals do not apply knowledge (perform) cooperatively, then its objectives are hindered. In knowledge working outside of industry, society suffers for the same reason. In terms of industry, only one thing matters, and that is performance. If a discipline like knowledge management, or a component, or a department, or even a person, is disconnected from this aim then there are performance gaps within the organization, and all organizations have these gaps. The goal is to minimize them.
I like to talk about the term expert because I think it contains a conundrum that represents most of the problems with knowledge working today.

If a person is deemed an expert strictly by social recognition or solely because they are published, then logic can become irrelevant.
If a person is deemed an expert by position, then logic can become irrelevant.
If being an expert is more important than knowledge itself, then we have given up knowledge for position power. – If a person is deemed an expert by their knowledge, but without regard to social recognition, then their knowledge will likely not be valued or used.
If a person is deemed an expert by knowledge context, then they may sit down in that context and never advance it (intelligence without knowledge creation).
If a person is deemed an expert because they advance a knowledge context, then knowledge context is being confused with knowledge creation, which is a separate and distinct process and skill with that process.
If a person is deemed an expert because they perform in a given situation, then expertise is a synonym with performance, so why use the term at all?

The term ‘expert’ encapsulates all of the confusion in knowledge working today. In short, we’ve confused all kinds of concepts like intellect, knowledge creation, social acceptance, and knowledge context. All of these are interactions that work together cooperatively in a single, cohesive system of knowledge working. They are not individual concepts that stand alone or can be interpretted outside of the context of the other knowledge interactions. Knowledge is one and questions are one–and the sum of interactions associated with these two is the whole of knowledge working.

Articles on the Fallacy of ROI

2010-12-09T18:44:00.000-08:00

Meaningful metrics beyond ROI – Parkin’s Lot

Why ROI Can Sometimes Lie – Adrian Mello/ZDNet

How to Improve Performance Management – CFO.com (A good article on overall measurement)

Sensing User Intention

2010-12-09T18:41:00.000-08:00

One of the coming waves in technology will be the ability for the machine to sense user intention. As technology moves into this realm, the line of fusion between mind and machine, or the ‘interface’ will become very thin.

HyperInstruments

HyperInstruments has a special interest in inventing musical instruments that “understand” the artistic intentions of the performer, allowing for the enhancement and extension of musical expression.

“We design these instruments for use by highly skilled performers, as well as for students, novices and amateurs. We also explore how new media technology can modify music itself, and how such concepts can in turn be applied to interactive intermedia art and entertainment forms, of which opera is a particularly sophisticated example.”

Current directions in the group are to develop creative experiences and “musical toys” for children from ages 6 to 12, and to design future performance spaces that measure and react to performer sound, gesture, and intention.

Noetic Spaces: The human mind and the sense of reality

The philosopher John Searle explains the difference between the mind and the computer is its’ existence or absence of intentionality.

The digital languages are inputted and outputted data through conduits of proxy systems. On the other hand, minds interpret the information by filtering it through people’s belief systems.
Searle defines “seeing” as “seeing as”, and “perceiving” as “perceiving as” according to the focus of each person’s attention. He states that the mood and state of minds filter information as to how and when we perceive things.

I assume it is because each person’s “semantic engine” or “conceptual apparatus” (both are metaphors of mind) are different according to their configurations (ways of thinking or personalities).
Then Searle’s states, “computers will never function as human minds because computers do not have intentionality.”

Examining the lexical item “intentionality” may be helpful to explain the meaning of “mind”. The lexical item “intend” is originated from the Old French, from Latin “intendere”. The Old French “in” means “toward”, and “tendere” means, “to stretch”.

It shows one of the natures of the” mind” which has plasticity and a scope of attention. The ancient Greek used a metaphor of mind-as-a slingshot, which may be to define mind as something which has intention, or mind as intention itself.

See Also:

Intending, and Artificial Intelligence – Larry Hauser
The next computer interface: your finger – ZDNet
Brain-Machine Interfaces – Nature

Levels of Intentionality

2010-12-09T18:40:00.001-08:00

User thinks or acts in accord with his or her own intention.

Computer interface records and responds to user intention from a device (e.g. a mouse)

Computer interface records and responds to user intention by interpretting motion from the user.

Computer interface records, responds, and anticipates user intention.

Computer records, responds, and anticipates intention from brain waves and the interface disappears.

Transfer human intention to computer.

Computer anticipates or predicts intention from a quantum dimension.

Computer develops its own intention.

On Changing

2010-12-09T18:39:00.001-08:00

—Alvin Toffler, 2004 International Conference on Complex Systems.

“None of the top 10 jobs that will be available in ten years exists today … these are jobs that will require workers to use technology that hasn’t been invented yet to solve problems that we haven’t even thought out yet.”
—Ian Jukes (futurist), in testimony before House Select Committee on Public School Finance (2003)

“Everything you learned is wrong… Assumptions that were valid yesterday can become invalid and, indeed, totally misleading in no time at all.”
—Peter Drucker, Fortune, Oct. 5, 1998

The Terrestrail vs. Spiritual Mind

2010-12-09T18:38:00.001-08:00

The Terrestrial Mind

Data – Meta-data and data are unstructured symbols in any form. Meta-data is simply a more granular set of symbols. Data is collected via the senses (experience) or by machine ‘probes’ (machine senses) and then, after it is recorded (stored), it can be processed either by the human mind or by computer.
Logical Structure – Information and knowledge are synonymous terms that describe any set of logically structured symbols. Knowledge is one and its structure is one. and technology (includes art). There is no information sub-structure. Structure, pattern recognition, connections, and association are also synonymous. Subcategories are and technology (including art).
Questions – The realization of a lack of knowledge structure. Structuring questions results in knowledge creation.
Language – The vehicle for expression, collaboration, and sharing of knowledge.
Behaviour – Actions based on knowledge. Doing. Includes performance. We need knowledge to do, but these two are not synonymous. Experience is the result of behavior.
Emotion – What moves us to choose and behave (externally). E- ‘motion’ > movement.
Consciousness – Varying levels of awareness of the terrestrial reality.
Terrestrial wisdom – Decision competency.

The Spiritual Mind

Spiritual Wisdom – Decision competency with spiritual guidance.
Motive – Why we choose (internally). Motion > Motive.
Belief – Temporary personal absolutes that determine interest and extend from motive.
Language – The vehicle for expression, collaboration, and sharing of belief that results in behavior.
Behaviour – Actions based on belief. Spiritual doing includes, e.g., selfless works or working miracles.
Emotions – Love.
Sprituality – Varying levels of awareness or realization of the spiritual reality. Results include, e.g., intuition, meaning (in terms of a sense of purpose).

Web 2,000,000.0

2010-12-09T18:35:00.000-08:00

The concept of Web 2.0 has been popularized as a new wave of online computer applications that allow the user to leave the confines of a desktop and rely on all kinds of web services instead. This term implies a linear transformation of computing technology. It also implies that the Google era is Web 1.0 and now we are ready for the next step in computing evolution.

But this terms holds an implication that is simply not true. In fact, the tranformation of technology is exponential, not linear. As such, we shouln’t expect a linear progression, but something that looks more like mind-boggling breakthroughs at each transformation. D-Wave recently announced that it would unveil the world’s first quantum computer with a 16 qubit processor capable of 64,000 simultaneous calculations in quantum space(s). See also here.

I don’t think the average person realizes the implications of such a technology. It has been speculated that a quantum computer desktop will have the computing power of all of the computers that exist in the world today. This is like comparing Google to Babbage’s computer.

And the transformation could occur very rapidly. We’re already seeing the weak signals of such transformation. On another front, MIT predicts that optical chips will arrive in 5 years. Photonics will liternally allow computing at the speed of light. The introduction of the Internet to our society resulted in a staggering transformation.

Are you ready for something even more staggering? It’s coming and it’s not Web 3.0. Fasten your seat belts…it’s going to be a wild ride.

Perception is not Reality

2010-12-09T18:33:00.001-08:00

When people, by various methods, attempt to better understand what people ‘like, prefer, perceive, etc.’…they are looking into the minds of those people to see how they see a thing or a concept. But what people like, think, perceive about a thing is not necessarily what it really is.

Rational and empirical logic dictates what a thing or concept is, not opinion. If you ask a person in the next room what they see and they tell you, e.g., that they see a cat, you are one step removed from seeing the cat yourself. It is possible they are not telling you the truth, or that they are mixing a cat up with a dog, or they don’t understand your language, etc.

Asking people what they perceive about a thing gives you what they see, not what it is. To know what it is you have to see it or experience it for yourself. Empiricism is the experience of reality and rationalism is the creation of knowledge from within itself. Both are based on logical connections and not opinion.

Working or managing against an opinion simply manages the politics or social environment that surrounds a thing, and doesn’t discover or create.

Teaching the Machine

2010-12-09T18:31:00.001-08:00

An interesting YouTube clip by Michael Wesch, Assistant Professor of Cultural Anthropology, Kansas State University.

Web 2.0 – The Machine is Using Us

Chimera

2010-12-09T18:30:00.001-08:00

In a move reminiscent of H.G. Wells Time Machine, Scientists recently announced that they have created a sheep that has 15% human cells and 85% sheep cells. See this Daily Mail article. This no doubt increases the debate on the ethics of genetic manipulation. Australian Artist, Patricia Piccinini’s “We Are Family, Venice” Art Exhibit Some of that applications of Genetics could be used to:

Merge human DNA with animal DNA, creating “chimeras,” and effectively blurring the lines between human and animal.
Enhance, e.g., plant or animal performance or resistance to disease by altering plant or animal DNA.
Enhance, e.g., human performance or resistance to disease by altering human DNA.
Print, or copy, human organs, which seems to be the current focus.
Create a non-human life form comprised of radically distinct DNA from that of humans, effectively splitting up the human race (See article, Genetic Upper Class: Could the Human Race Split? – Live Science …from the article Two Human Species In 100,000 Years? Stick With Wells – Technovelgy.)

This life form could be more, or less, advanced than humans. It is important to note that it is theoretically possible for humans to create a race of beings more advanced than themselves.

It is also important to note the double-edged sword of genetics. On the one hand, it has the potential to radically extend human longevity (which creates a whole new set of issues), but on the other hand it can create a genetic ‘time bomb’ that would throw off the natural balance and order of life on earth and could threaten the existence of the human race.

The Unpaved Road to Singularity

2010-12-09T18:27:00.001-08:00

Singularity is often associated with a smooth advance into a time of an unfathomable paradigm shift. It can be portrayed as a great hope, a great solution, a fix to the worlds problems….a clean, paved highway to the future.

On the contrary, as we draw nearer and nearer to singularity, we are entering one of the most volatile and dangerous times in modern human history. The road is one of the most challenging and dangerous roads that mankind has ever attempted to traverse.

Knowledge advance is an ideological magnifying glass. Human ideologies, with a very few exceptions, have endured for thousands of years. Yes, there have always been conflicts and wars, but knowledge advance gives the power of war to the individual and small group. What once took an army of soldiers, can not be done with machinery that fits in the trunk of a car….and the threats are becoming smaller and smaller.

The rise toward Singularity holds an obvious dichotomy with inherent risk on many different fronts:

The same technology that creates low cost water filtration for third world countries, has the potential to create a nano weapon that can fit in a shirt pocket and could annihilate large parts of cities.
The same industrialism that allows nations like India and China to move their populations out of poverty and into prosperity is producing pollution and environmental threats on a global scale.
Human population is booming, and planetary biodiversity is threatened.
Some countries are becoming desperate for immigration to keep their economies vibrant and other countries like China are trying to place limits on the number of children born.
The same medical advances that create cancer ‘smart bombs’ or ‘manufactured (instead of grown) food’ can create human engineered disease, self-replicating destructive nanobots.
Technologies like cloning could solve food production issues and can also totally destroy the balance of nature.
The same molecular economy that will create billions in wealth for various nations is also changing the balance of power in our world and these instabilities are increasing the threat of major war.

And there are not just physical conflicts and wars, but also conflicts and wars in the knowledge working space. Not only in the sense of cyber-terrorism, but inherent to the nature of knowledge itself. You see, knowledge, by its very nature, is one. Knowledge advances from a logical structure that can be represented categorically and all knowledge can be categorized into a single structure. This is possible, because it is the very nature of knowledge to be structured into one structure. As we move toward greater and greater knowledge working computer power, this ‘oneness’ of knowledge will become more and more apparent. Add to this the potential for ubiquitous computing and knowledge will begin to melt, as it already has, traditional national boundaries.

The open source vs. closed source argument in computer software is spreading into knowledge in general with the introduction of technologies like the wiki (Wikipedia). These conflicts are in their infancy. As computing power increases, it becomes increasingly more ‘discoverable’ by nations, groups, factions, and individuals. What took years to discover just 50 years ago, now takes only minutes, and we can expect this to increase. In addition, there is a rising level of conflict over who owns this ‘one knowledge.’ What exactly is ‘public knowledge’ and how does it relate to a particular national interest For example, how can a nation protect itself from technology of weaponry that becomes ‘public knowledge’ or knowledge that is easily accessed?

Also, collaboration is tearing down national boundaries at individual and small group levels and this new found cooperation is escalating into conflict with politcal power bases. It’s pretty easy today for, e.g., Russians, Chinese, Indians, Mexicans, and U.S. citizenry to collaborate to discover new knowledge. But the national interests these collaborations sit down in have, in most cases, not changed and this will create escalating conflict between governments and citizenry.

Seen as a whole, these problems are daunting if not just plain scary. But all of these problems have one thing in common and this commonality is also the key to their individual resolution. Every problem we have emerging in this post-information age culture is ‘Integral.’ Integral in the sense that a solution requires collaboration and contributions from several areas or facets of society in order to arrive at a resolution.
Just try to name one issue that an educational, governmental, or industrial enterprise today can solve ‘on their own.’ If you consider the ripple effect of our actions in a ubiquitous world, I dare say the stand alone issue is becoming extinct. For example:

It won’t be possible to solve Los Angeles pollution, if that polution is travelling across the pacific from China, unless we help, or cooperate, or dialogue with China to solve it.
It won’t be possible to remain profitable in an industrial sense without cooperating and dialoguing across nations on environmental impacts.
It won’t be possible to stop a nano bomb in a shirt pocket, unless we cooperate and create a dialogue between governments, militaries, academic researchers, and industries on a global scale.

The list of examples is a long one. Issues in all types of enterprises are largely global in nature, have increasing levels of risk inherent to the issues, and are integral.

We are leaving the time of national problems and entering a time when all problems require some type of dialogue or cooperation to solve them.

Dialogue is a group problem-solving discussion. It’s simply talking together to solve a problem. Futures generative dialogue, coined by Rick Smyre, is a dialogue that focuses on problems that are ‘coming’ as identified by trends and weak signals.

The answer to human survival, which we will struggle with more and more as we move toward Singularity, is in dialogue and cooperation between social institutions, enterprises, groups, facets, and individuals.

A Few Keys to Everything

2010-12-09T18:24:00.001-08:00

There is no such thing as tacit knowledge. Polanyi’s concept of knowledge that cannot be easily expressed is erroneous. All knowledge is logical and can be expressed or we don’t know it. What cannot be easily expressed is the question or areas of questions juxtaposed against knowledge.
The question is a perceived or realized lack of logical knowledge structure.Scholarship has largely skipped defining the question. We have question research going on, but no one seems to be simply defining what a question is. Understanding the definition of the question unlocks the human mind and knowledge working processes. There are two main types of questions, knowledge creation questions and learning questions. The knowledge creation questions realized a perceived lack of knowledge structure in knowledge overall while the learning questions realize a lack of knowledge structure in the individual or group intellect.
Knowledge creation puts knowledge into the social knowledge base, while learning draws it out.Seems simple enough, but this is largely confused in cognitive science, artificial intelligence, and knowledge management circles.
Knowledge working is not performance.Knowledge management is really a knowledge-centric variant of instructional design, which is performance-centric. Robert Mager impeccably defined performance years ago, but Mager did not tie knowledge working into his definition specifically. In a nutshell, knowledge management professionals aren’t seeing performance and performance experts aren’t connecting into knowledge working.
Artificial intelligence is a misnomer.Intelligence and knowledge creation are largely confused in scholarship. Knowledge creation is the source of all new knowledge. A person can be intelligent without ever creating new knowledge. Likewise, a knowledge creator isn’t by default intelligent. Intelligence is knowledge stored that can be retrieved. By this definition, any computer is already artificially intelligent, but no computer today can create knowledge. The term should be artificial knowledge creation. Singularity IS artificial knowledge creation.
Empiricism vs. rationalism solved.The answer to the age-old question of whether or not knowledge is empirical, or rooted in experience, or rational, which is thought built on thought is “both.” Scientific knowledge is empirical and convergent while technological knowledge is rational and divergent. Scientific method is a knowledge creation method for science, and a rational knowledge creation method I developed is called ”Directional Categorization.”
Three dynamics of society.There are three dynamics that comprise any social order. 1) Knowledge advance – the center is knowledge creation, 2) Social context – the center is the balance of interests (includes governance, government, values, ethics, legitimacy, etc.), and 3) Economy – The center is supply and demand (includes education as a feeder pool for industry, industry, and economic development. When these three dynamics are out of balance, social issue emerge. Knowledge advance is essentially social advance in science, technology, and spirituality. As such, this dynamic tends to drive the other two.

The Taxonomy of Life

2010-12-09T18:21:00.003-08:00

Knowledge <= Philosophy of

Empirical
- Scientific logic (Science – To know) <= Is convergent
  - Scientific disciplines
- Answering questions takes the form of Discovery <= Relies on scientific method
Rational
- Technology (Techno logic) <= Is divergent
  - Technological Disciplines
- Answering questions takes the form of Invention <= Does not yet rely on rational method
Social
- Balance of Interests
  - Social disciplines

Emotion

Emotional intelligence
Answering questions takes the form of maturity

Spirituality

Spiritual knowledge
Answering questions takes the form of enlightenment

Sustainability?

2010-12-09T18:21:00.001-08:00

This word sustainable means a lot of different things to different people. One simple definition might be ‘to keep going.’ A sustainable society being one that is able to keep going.

If we look at how we keep going, we could technically have a great war, which I’m in no way saying is a good thing, but still keep going.

Or we could theoretically totally destroy the environment of this earth we live on while we gain technology to enter a space age that allows certain people to travel to other planets and by this ‘keep going.’

Makes one start thinking about who ‘we’ is and just who will ‘keep going.’ Just what is to be sustainable? A subset of people? All people? The earth itself? Two people that can procreate? People remaining here on earth? People traveling to some other planet?

There are a lot of options to being sustainable. I just want to expand thinking on this term.

The Death of Modern Philosophy

2010-12-09T18:19:00.001-08:00

Philosophy is the discipline concerned with the questions of how one should live (ethics); what sorts of things exist and what are their essential natures (metaphysics); what counts as genuine knowledge (epistemology); and what are the correct principles of reasoning (logic). (en.wikipedia.org/wiki/Philosophy)

Under this definition above, understanding knowledge and how it differs from experience ‘solves’ a great many of the philosophical issues that have been debated since Plato. Solving this is, in a way, the death of Philosophy as we know it.

The ‘missing link’ to this solution is simply an understanding of where knowledge comes from and how it is formed, which is the recognition and structuring of questions into logic. This single process is the same for scientific knowledge or rational knowledge, but as a global society, we’ve simply mixed these two up.
We have some surety in scientific method, which is a rigorous way of structuring questions about our physical reality into converging logic, but we do not have a corresponding ‘rational logic method,’ which would be a rigorous way of structuring rational questions into expanding rational logic.

Because we don’t have this test, we are basically trashing our global rational knowledge base with duplication, overlap, error, information overload, undo complexity, etc.

What is coming soon is a mechanized way to structure rational knowledge. Cirilab Speed Read (http://www.cirilab.com/) is a good example of what this is going to look like (just imagine this capability multiplied by 1 million+).

Once we have a mechanized equivalent to scientific method, knowledge will become much, much ‘smaller’ because the duplication, overlap, error, etc. will be quickly eliminated. At this point we will realize how little we ‘really’ know because we’ve basically been running in semantic circles creating circular and erroneous logic.

This automated logic will also enable the convergence of nano/bio/info/cognitive knowledge (the NBIC Convergence). Rational knowledge will quickly come into one, which is the natural state of knowledge.
The current model of knowledge is built on the concept of ‘expertise’ which is unruly and erroneous. It is a political basis for knoweldge instead of a logical basis. Mechanized rational logic combined with 1 million+ more computing power, would enable an individual to taxonomize the entire Internet as we know it today and would take the politics as we know it today out of this process.

Again, this entire transformation is based a simple understanding of how knowledge is formed. This understanding will lead to automatic taxonomy of rational knowledge and will bring about the simultaneous death of modern philosophy and rise of singularity, which is essentially a new level of philosophy.

What is Design?

2010-12-09T18:17:00.001-08:00

Every single thing that mankind ever built or created, be it intellectual or physical, was designed. Design is inherent to ‘making things,’ which is industry. But what is design? Design is the intersection of form, function/purpose, and aesthetics. All designs have some mix of these three. A piece of artwork leans heavily toward aesthetics, while a building leans heavily toward function/purpose. Both of these examples, and all designs, have form because they are ‘things made.’

Sometimes the simplest designs are the most profound. Is that a function of design? …to reduce complexity? Designs are a compilation of options of form, function/purpose, and aesthetics. Anything made could be comprised of many different options. The design is simply the choices made among these options.

TRIZ methodology lists 39 engineering parameters:

Weight of moving object
Weight of nonmoving object
Length of moving object
Length of nonmoving object
Area of moving object
Area of nonmoving object
Volume of moving object
Volume of nonmoving object
Speed
Force
Tension, pressure
Shape
Stability of object
Strength
Durability of moving object
Durability of nonmoving object
Temperature
Brightness
Energy spent by moving object
Energy spent by nonmoving object
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
Complexity of control
Level of automation
Productivity

These parameters, and more, combine with aesthetics to comprise an engineering design. In one sense, a design is the solution to a problem of function/purpose. We ‘make things’ to serve a function/purpose. All problems are compound entities made up of ‘sub-problems.’ When we solve these sub-problems, which are basically decisions of what components to include in the solution, we start to solve the larger problem with a design.

No problem is stand alone, but all problems and all designs that solve them, are comprised of component parts. Behind all of these decisions is logic. In choosing component parts, we are making logical decisions based on some criteria we have gathered. Even if the decision is to defy logic, as in some works of art, this is a logical decision.

Design then, is a compound solution of form, function/purpose, and aesthetics that is created using logical processes to make decisions.

Collective Intelligence – Creating a Prosperous World at Peace

2010-12-09T18:16:00.001-08:00

I contributed a section to the book Collective Intelligence – Creating a Prosperous World at Peace entitled: “Knowledge Creation in Collective Intelligence.” There are lots of really top notch contributors in this book and I’d highly recommend it.

The Division of Mental Labor

2010-12-09T18:13:00.000-08:00

When Adam Smith created his ‘pin factory’ example, he launched the concept of the division of labor. Before Smith’s concept, production of a ‘thing’ was done in it’s entirety by one individual from beginning to end.

If a spinning wheel was being manufactured, one person made that wheel from beginning to end. Adam Smith realized that it was more efficient for one person to make one part over and over and to send that part down an ‘assembly line’ until the whole was created by the last person. He use the manufacture of sewing pins as an example.

People tend to think of this as a point in time and not a progression. The division of labor was born and it continues to exist. But what was born was the division of physical labor. And this matured into vast complexities and methodologies for how to effectively and efficiently manufacture ‘things.’

But it didn’t stop there. As computers matured and connected, suddenly it had become possible to share mental tasks. The concept is commonly referred to as ‘crowd sourcing.’ Essentially, individuals began to divide and share ‘mental labor.’

In our day this ‘mental division of labor’ is becoming a deep discipline similar to what has already emerged for the division of physical labor.

When this full progression from the perfection of physical on to the perfection of mental is complete, we will realize that the division of labor concept itself is painfully outdated.

We will learn that the development of physical and mental sourcing does not solve the rapidly growing social crises.

Adam Smith created the division of labor to solve moral issues of his day and in effect created even more moral issues than their were before. I see the same kind of blind zeal for the mental division of labor, but when it has run it’s course, we’ll only be a little better at managing collective knowledge and still fairly big newbies at running an integral society.

What is coming next is a new way of thinking and an entirely new social model–A Second Enlightenment. Just as in Smith’s day there were many great thinkers that ushered in the first enlightenment, we will have the same in this next era. The foundation for this shift is already being laid.

These are exciting times, and I wouldn’t miss any of this for the world.

Wikiopoly

2010-12-09T18:11:00.001-08:00

It’s not a very well-known fact, but 73.4 percent of the entries in Wikipedia are made by roughly 1400 people. You may have thought it was an open, global, knowledge base. In fact, it is a tightly controlled monopoly of view points.
A study done by Yair Amichai-Hamburger of the Sammy Ofer School of Communication in Herzliya, Israel found them to be very disagreeable to new ideas. In an article entitled Psychologist finds Wikipedians Grumpy and Closed-Minded, Amichai-Hamburger postulates that wikipedians contribute because “It is their way to have a voice in this world.” …and that their motive is egocentric and not altruistic.

The thought of a shared central knowledge base for all of humanity is an altruistic one, that just simply not what Wikipedia is.

The Threat of Machine Consciousness

2010-12-09T18:09:00.000-08:00

Consciousness has been defined along a continuum of definitions relative to the concept of self awareness.

Here is an example of this continuum:

Being

Awake
Sensory perception and response
Self-aware/sentient
Self-aware and environment-aware; Space/time orientation
Personal identity
Questioning
Sapient

Doing

Capable of attention
Capable of expectation
Capable of belief
Capable of feeling
Capable of motivation
Capable of originating intention
Capable of exercising intention
Capable of experience
Capable of action, prioritization or command of environment

Receiving (spiritual)

Life force
Universal causal force

Being, Doing, and Receiving

All of the above

These are just a few variations on this continuum and collectively, these represent the more subtle aspects of the human experience.

Most scholars on either the cognitive science or machine intelligence sides, see individual aspects of consciousness and not this continuum. And most theories of the mind and machine don’t differentiate between thinking, saying, and doing.

I believe it takes a multi-disciplinary understanding to see this continuum. And as I’ve posted many times before, this is also what causes scholarship to miss the ‘process’ behind human interaction with the social intellect–this because they focus on biological, mathematical, etc. (single discpline) approaches and are unable to see the systemic mental interactions. And this same single disciplinary approach also creates a blindness to the key that unlocks all mental understanding…the question.

So then, when we think of ‘machine consciousness,’ there is one key question: Are there any aspects of this continuum which the machine can never attain?

The answers to this question is the boundary of machine consciousness. In my personal opinion, the machine is incapable of belief and therefore will never feel or be motivated to create intention. But that said, human intention can be transferred to the machine and the machine is capable of physical action. My view is that the machine can evolve to exceed humanity many respects–smarter, faster, stronger, more agile, etc.; but that the machine can never believe, feel or originate intention.

Under this view, the main threat of increasing machine capabilities is as a tool in the hand of humans with ill-intentions projected on other humans–a magnification of the same threats that already exist today in technologies like drone aircraft or robotic weapons. The machine becomes an extension of human intension with far more destructive or beneficial power (physcial and mental) than the human can exercise on his or her own.

In this sense, the future struggle that is fast approaching is not in the realization of machine consciousness, but in the increasing power of the machine in the hands of human intention. And the key to human survival of this emerging conflict is to mature human relationships and human intention, which is far more formidable than the threat of an ill-intentioned machine.

Dimensions of Military Robotics

2010-12-04T08:08:00.001-08:00

Energy (to begin)

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