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Bruce LaDuke, Question Scientist, Integral Futurist, and Managing Director of Instant Innovation, LLC 12-31-08 Interview
 

Bruce LaDuke, Question Scientist, Integral Futurist, and Managing Director of Instant Innovation, LLC 12-31-08 Interview

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Bruce LaDuke, Question Scientist, Integral Futurist, and Managing Director of Instant Innovation, LLC in Indianapolis, IN talks about Integral Futuring and the three dynamics that contribute to the ...

Bruce LaDuke, Question Scientist, Integral Futurist, and Managing Director of Instant Innovation, LLC in Indianapolis, IN talks about Integral Futuring and the three dynamics that contribute to the current state of any society or social division: Knowledge Advance - The Center is Knowledge Creation, Social Context - The Center is the Balance of Interests and Economy (Includes education, industry, and economic development) - The Center is Supply and Demand. It is the combination of these three dynamics that creates the national or international social state. You can learn more about Bruce's work on the Blog HyperAdvance http://www.hyperadvance.com

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    Bruce LaDuke, Question Scientist, Integral Futurist, and Managing Director of Instant Innovation, LLC 12-31-08 Interview Bruce LaDuke, Question Scientist, Integral Futurist, and Managing Director of Instant Innovation, LLC 12-31-08 Interview Document Transcript

    • 1 Interview and transcription December 31, 2008 Bruce LaDuke, Question Scientist, Integral Futurist and Managing Director, Instant Innovation, LLC, Indianapolis, Indiana Overview of Integral Futuring Integral Futuring: a process approach to Knowledge Advance Overview of Integral Futuring Hi, my name is Bruce LaDuke and I’m from Indianapolis, Indiana. I work here in Indianapolis in a full time capacity in a large global corporation, but part time I’m a man of many hats. I work in several disciplines to help folks understand the problem space of escalating knowledge and the change of volatility associated with that; I call that space “HyperAdvance” – I have a blog by that name. I want to help you deal with the HyperAdvance that’s going on right now, today. In that context, we’re going to talk about seven different areas: the first area is questioning. I’m going to explain what questions are, not really looked at very much today but when you understand what the question is fully it takes you to the next space which is creativity and helps meld all creative methods, innovation methods, all the different creative approaches into one method which is based on questioning, and then that can be scaled up into knowledge management which is a view of how you work knowledge cooperatively around this creative method, how does everybody cooperate together in one accord; and then I scaled that up into a philosophy which is a global view of how all humans work knowledge and how all humans cooperate around knowledge, so it’s a knowledge philosophy, and then that piece can scale up into Futuring which is the impact of that knowledge working process, how do we cope? The whole change is happening exponentially, how do we cope with that change? Finally, knowledge is nothing without applying it, so all of these boxes below really support and enable enterprise, and I’ll talk a little about enterprise and how this flows into enterprise and some approaches for that and ways to think about it. Finally, AI, or Artificial Intelligence. If you understand the process humans use, and again it’s a process, if you talk to Artificial Intelligence scientists, a lot of them have a mathematical view, some of them might have a biological view of that particular discipline, this view I’m going to present today is a process driven view. If you understand this entire process, the discipline of AI kind of changes your thinking about it changes, it can be mapped the same way to the way humans do it; so, I’ll show you how Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 2 humans do it and then show you how a machine might be able to do the same thing and tie those two things together which is really what’s one solution. Hope it’s a fascinating journey for you and I do appreciate you taking the time to view it. Integral Futuring began in 1983…[03:09] I’m going to start with a simple method that I created in 1983 when I first got out of College, it’s called “Direct Categorization.” I was involved with graphic design and trying to come up with creative solutions for advertising, and my Professor at that time, Katy Kennedy, she’s very much a driver on more creativity, stronger solutions, how many creative ideas can you come with and how fast? All of that got me into a very strong fascination with this term “creativity.” So, I started to look at creativity across different disciplines, platforms, groups, and educational silos if you will. I studied many different disciplines and tried to understand different views on what creativity was and how it worked and at the end of all of those studies, hours and hours of study, I realized there is a two-fold thing going on: one is, everything we know if categorized, and I am using the categories who, what, when, where, why, how, as a kind of sample, but if you try to think of one thing you know that is not categorized. Just one thing, its impossible. Everything you know is categorized because knowledge is categorization. This is a fundamental premise to start with. If you say, I know something, well, what you know is a structure of thought, you know categories of information and all of that information being categorized is also one. Knowledge is not some broad thing that is scattered everywhere, although today you might argue that’s what it looks like. In reality, it wants to come together in categories and become one. That really is a different way of thinking and if you put the problems we’re having in our world today in perspective to that, you can see people are not treating knowledge as one, they are treating it as many things. This method then goes through and says, well, if we have all knowledge categorized, we also have things we know and things that are unknown. So, the known world, for example in this context I used it to come up with advertising solutions. In a certain format, what are the, for example if we were trying to make a diaper advertisement what are the knowns about that problem? What things are being done and what things are already being done? What are the approaches they’ve taken? What formats? What type of lighting? What type of media? All the different things that related to that problem statement that exists. So, you have knowns and then you have questions, or unknown. Questions really are the key that most folks in general have overlooked. If you look up the word “question” in Webster’s it defines it as “to ask a question.” Well, to ask a question is a question, it makes no sense. What is a question? Well, what I’ve learned in the process of digging into this method I learned was really knowledge in general which is one exists as categories and that category if we know it it’s structured, its categorized, and its all logical. However, today we may have silos for all that that want to come together into one, but in general there are categories for known information and everything we know can fit in there just nice and neat. Questions are out here on the leading edge of all the things that we know when we ask questions about reality. So, we’ll say, “Well, I don’t know that” or “I don’t know this” – there’s a question related to something that we know. Questions are seen today as individual things, but if you think of them as a field of questions that are juxtaposed against knowledge that you have like a ying and yang affect where knowledge is on one end and questions are on the other end as they cooperate, they Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 3 co-exist, that’s really what this direct categorization method says. It says questions and knowledge are in this cooperative infrastructure together and if I can learn how to structure questions, I literally create knowledge. That’s the fundamental premise behind everything, everywhere that’s ever done in terms of creativity, innovation, problem solving, all these words that are used are really about structuring questions. It sounds simple, but that thing scales up into this massive set of solutions. I’m going to take you through generally how this works. [08:42] Diagram: Knowledge Creation – A Five-Step Process This slide talks about it in a little more detail. There is a single process that all creative methods, all innovation methods, everything works by this single process in terms of creation of new knowledge. I would say, for example, a new painting is actually new knowledge, it’s a new approach to how to do an artistic solution, its an advance from the past solutions, so I’m not limiting this to technology or social systems, its everything. When I am talking about knowledge creation I am talking about any problem and any solution. It’s a Five-Step process where you define, it starts with a definition/solution or structure, again all knowledge is categorized and then that’s your context, every problem has a context, I think everybody knows every problem has a context. What people tend to miss is every problem also has this mass of questions that are related to that context, and by structuring those at the leading edge of this knowledge structure you actually create new knowledge. That’s how knowledge creation works. There’s a logical operation to structure it – connect/ structure/ define – and the result is a new, advanced definition/solution or structure. So when you take those varied questions and you structure them into a new knowledge context you’ve advanced society, you’ve created something new that people didn’t know. Some people would say if I take something somebody knows over here, and something somebody knows over here and I bring those two together that’s knowledge creation. That’s actually what’s called compiling where you take knowledge in silos and bring it into one category, or one categorical structure. Knowledge creation if you think of it as the sphere on the poster, knowledge creation is more of a new knowledge, or making the sphere bigger, making knowledge larger. Taking those questions that are about things that don’t exist, not questions about things that do exist, the questions about things that don’t exist and answering them, structuring them actually advances society. Today, people do this, but they do it in a very unconsciously competent way. As a matter of fact, it’s almost done blindly but it’s done quite well, it’s just that folks don’t realize that this is the process under all of it. This encapsulates every kind of problem solving, every kind of creativity, and all those methods, there’s really hundreds of methods and if you look at, for example, lateral thinking. If you drew a line out this way, lateral thinking would force you to think laterally out in the question space. Brainstorming would look randomly out in the question space. I’m trying to think of different methods, but every creative method you can imagine, questioning is a creative method, would somehow deal with “How do I deal with this question space?” And if you take those and look at them collectively, it’s that Five-Step process. [12:20] Diagram: People around the globe Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 4 This process then, I’ll use this three-arrow diagram to signify that Five-Step process wherever it appears. This diagram then shows you when we know that’s the fundamental of knowledge that its one, its categorized and that questions advance it, the structuring of questions advance that knowledge. What happens when you scale that up to society? How does society use that process? How does this work? This is a representation of this whole social knowledge base. How we as a global society work knowledge. There’s a body of knowledge, which today you could probably draw 2500 silos, draw a bunch of little spheres for countries or for knowledge groups, but let’s just assume its one categorized structure for simplicity’s sake. That it all makes sense and we all go to one source. That would be what I would call a social knowledge base, some people call it extrinsic knowledge, there’s a lot of different terms for it, but in basic Bruce terms its social knowledge base. There are people who would take knowledge out of that and learn it to instruct learners or learners might directly pull knowledge out of this social knowledge base, but in terms of learning the arrows are going toward the human, they are going out. Learning is the process of extracting knowledge from the social knowledge base in such a way that the learner might get it from the instructor or the instructor might get it from the social knowledge base or the learner might get it directly. So, it’s the extraction of knowledge that’s what learning is, extracting knowledge for your purposes, you may have goal behind that but ultimately learning in of itself is just knowledge extraction. Knowledge creation is the opposite and that’s the Five-Step process I showed you that involves questioning. Knowledge creation actually goes the other way and puts it in. People have questions in this space, a learner might say, “Well, I have a question about physics, I’m not a physics person, I need to understand quantum physics, help me understand that.” So, I have lots of questions, but the knowledge of quantum physics already exists, the learner just doesn’t know it. There are questions in the learning space about knowledge that exists and there are questions in the knowledge creation space about knowledge that doesn’t exist yet. There are two types of questions, that’s the fundamental division in questioning: knowledge creation questions and learning questions. Most folks, for example, Google is a learning question. When you do a query in Google you are asking Google to tell you something that exists. Tell me the answer to knowledge that’s in the Web, that’s already codified, that’s already in the social knowledge base. Tell me how that works. So, the learner goes to Google and says, “Help me answer this question” and extracts the existing knowledge. A knowledge creator will actually go and ask a question out in this question space that we talked about earlier and say, “What’s the next thing beyond string theory?” a quantum physics term “What happens after string theory?” That’s a question about knowledge that doesn’t exist yet. And by structuring those we create knowledge advance. People will call that as “it was a creative moment” or it was being innovative, and a lot of times they are stolen from, because the process happens in the background, people don’t even realize its happening. So, the idea gets taken and someone else goes and implements it. The whole process is kind of underground right now and blindness and underground economy… but the knowledge creator will go and learn this social context and I’ve drawn a little division, so they’ll learn one context very deeply. For example, physics; they’ll learn it to the point that they know the structure of the knowledge that exists then they’ll ask questions about, “Well, what about what doesn’t exist?” and they’ll structure those questions into new knowledge and advance the field. Essentially by doing that, getting back to this picture Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 5 here, they make the sphere larger. They increase the size of human knowledge. Its social advance, that’s how society advances. We advance society through questioning. The little question mark is so huge its inside everything and it ties everything together and makes this one thing that all of a sudden all of our social systems become a lot clearer because we realize we’ve ignored this thing called the question, entirely. The knowledge creator has to choose whether or not they’re going to express that new knowledge. So, after they formed it by structuring questions, they have a decision: do I keep it in my head? And keep it to myself, or do I express it? That decision then goes, if they decide to express it, has to be accepted into the social knowledge base. Because it is not just about that person, its about all of society saying, “We believe you, we think that’s true, we value that information so there’s this role of social acceptor that has to literally say, “Yes, society wants to bring that in.” Now if I’d use as an example Galileo, Galileo was the solar centric or astronomical advance and if you look at this person’s life, his advance was not accepted until after he died. He was literally fought his entire life; he was right, they were wrong, he was fought, he died. After he died, they realized, “Oh, well, this guy was right.” He had created new knowledge, he had answered a knowledge creation questions, he was right, and everybody in society didn’t accept it. So, this social acceptor has to actually see the value and the logic, so there has to be some connection between the person who creates it and the person who accepts it. There is a man named 1Michael Polanyi, who was a physicist and a philosopher, that had this concept called ‘tacit knowledge.’ His basic premise was that we know more than we can say. Now, that’s all wrong and that’s very much heretical, saying that because most folks, the entire knowledge management discipline is built on that concept. But that concept is incorrect, the reason it is incorrect is because that if you don’t know it and you cant say it then you don’t know it. Because its not categorized, its not structured, its not learned and in your knowledge base, which is your brain. It hasn’t been extracted from the social knowledge base or you haven’t created it and know it in your own mind. Knowledge is always expressible, what Polanyi was trying to express, was questions. And the things we need to extract are questions and the way to extract them is to identify them, then realize them, then structure them, and by doing that we create knowledge. So Polanyi’s concept, he was on to something but he didn’t take it far enough. He took it to, “Well, there’s 1 Michael Polanyi is a philosopher that died in 1976. Here are some sites on his life and work: http://www.missouriwestern.edu/orgs/polanyi/ http://en.wikipedia.org/wiki/Michael_Polanyi http://www.infed.org/thinkers/polanyi.htm This is the article Bruce LaDuke published that explains why his view of tacit knowledge is erroneous: Beyond Polanyi - e.Learning Age – Biz Media – Europe - Jul/Aug 2005. Most of the online links to this article have a page of irrelevant text attached. This is the formal link to get e.Learning Age article from back issues: http://www.encyclopedia.com/doc/1P3-872188591.html Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 6 something out there, but I don’t quite know how to say it…” Well, that’s a question! That is what he was trying to express. So, this cycle occurs and has occurred, and this knowledge base has been growing rapidly because we are compiling and connecting knowledge. The Internet is a compilation of knowledge, its not enabling yet, knowledge creation or HyperAdvance, as I’ll call it. But this entire process, an ignorant person just kind of says, I don’t want to be involved, they don’t participate, and I don’t mean that in a derogatory way, ignorance is non-participation. This system then moves over into enterprise and is applied. So, knowledge in of itself is not applied, knowledge is an enabler. Application occurs within enterprise and I’m using that term very broadly to say social systems, business systems, educational systems, military systems, military projects all the project level or system level or organizational level activities, that’s all enterprise. Performance is what we do inside of enterprise. So, knowledge just enables us to do things. It’s not a doer; you don’t just do things because you know them, you have to apply them. So this system of knowledge working enables enterprise performance that’s essentially how the system works. [22:12] Diagram: Empiricism - Rationalism That whole thing was very philosophical and I’m going to show you the philosophical view of this. Now, in philosophy there is this age-old argument about two thousand years old there is Empiricism versus Rationalism. Is my knowledge based on my experience or is my knowledge based on in my mind? Is it rational? That question has been the debate of philosophers through the centuries and lots of different frames and perspectives they’ve looked at that. Let’s look at that same problem through the perspective of the question. This slide shows on the one side Empiricism and on the other Rationalism and the Empirical disciplines like chemistry and biology and physics are all going into reality and they are trying to find information about reality, they pull knowledge based on observation from reality and that logic that they pull it from is actually converging. It is a known fact in creative methods and cognitive science circles that some knowledge is converging and some is diverging. The knowledge that is converging is science, chemistry, biology, and physics, zoology all of the natural sciences are converging. That logic is commonly the process for processing that logic is commonly known as scientific method. Scientific method is a form of the Five-Step process I just showed you. It actually is not as complete as that five step process, if you start looking at all of this together its really all one process. The scientific method is proven, it is reliable, you know it’s going to work because it is structuring hypotheses into new knowledge using converging logic and helps us interpret our reality. So, through scientific method we discover and we create new scientific discoveries, which is new knowledge. The part that’s missing in this Empiricism versus Rationalism argument, the part that’s missing is the rational method. There is no method today; I mean there are thousands of methods today, for how to advance rational thought. There’s no standard. There’s no scientific method. But there is this entire body of expanding logic. For example, technology is an expanding logic and this is associated with creativity or invention. It might be art; art is expanding and continually becomes broader and becomes a more broad experience, more and more categories of art, more and more experiences of art. The same thing with technology, technology becomes greater and greater, expansive inventions, more solutions. Rational thinking, which is in the mind, is the same structure, the same Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 7 categories only they expand. They expand outward and there’s also a processing of that knowledge that occurs on the front end by that five step process and that is what I would call Rational Method, which is my Five-Step process. It’s a process for how we take knowledge structure, answer questions, and expand knowledge. That’s all fairly complicated, but the simple part of this is that whether you’re in science or technology you’re dealing with two different kinds of logic and you are still answering questions, you’re still building a knowledge base, you’re still using the same simple process I described earlier to structure questions to advance that. You might have silos of knowledge that need to be compiled, you might have disciplinary silos that use different terms, different definitions that don’t connect, but its all one knowledge base in science and one knowledge base in technology and art and those diverge or converge based on the type of knowledge it is and the same method advances both. There’s one method for questioning and structuring questions that applies to everything. That solves Empiricism versus Rationalism. [26:49] Diagram: Singularity But if you then go to today and help me bring this into context of the world today and what’s happened. Today, we’re in an unconsciously and incompetent way, we’re advancing knowledge fast. One person might say well the Internet has advanced knowledge; no, its brought knowledge together which in part is an advance because we’ve operated all these little silos advancing those little silos, making the little spheres bigger. But the Internet said, “Bring all this stuff into one big sphere, let’s look at it together, let’s work around that knowledge together.” When that happened all human knowledge compiled its only a fraction of the knowledge that exists. The deep Web is underneath the Internet with 98% of the information in the world but if we talk about that as one thing and its all come together, now the next logical step is “Now that we’ve got it all together, how do we work together? How do we cooperate around that knowledge, how do we build that knowledge together?” This slide shows environmental factors associated with that. What’s happening down here is this term comes from a government study called NBIC convergence, which is Nanotechnology, Biotechnology, Information Technology and Cognitive Science. All of those categories of science and information technology again they’re two different things, really, and cognitive science, there’s really a whole picture of human knowledge is represented in those four terms. They realized in this government study that they are coming together, that things like Biosynthetic are crossing lines across Nanotech and Biotech and creating joint solutions, that when you get down to doing things very small these lines all collapse and information, nanotech, biotech, cognitive approaches they all become one thing and they converge and at the same time – this didn’t come from the study this is something I realized - that at the same time knowledge is advancing in all of those areas toward this point in time that Ray Kurzweil says is singularity which is the paradigm shift if you will, it’s where we go into a whole different frame. From this knowledge working perspective what’s happening is these knowledge bases are being compiled, they are becoming one, they’re working together, the cognitive science is starting to come together and build a process for how this becomes one and advances, and knowledge is moving up at the same time on a curve that makes it very unmanageable; the volume of it, the chaos, the complexity, volatility, change, risk, just general upheaval. There are negative factors associated with the Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 8 upheaval of that knowledge advance upward toward singularity. Singularity is really the point in time where the knowledge convergence, the end big convergence, meets knowledge advance at this highest level and in my opinion, what that is, is the understanding that all of that complicated thing that we thought was so hard has come together and now we have a simple process for working one knowledge base that is interconnected in one category and one knowledge and everything that looks so terribly hard, became really simple. That knowledge of questions really drives the plane upward toward singularity, we’re going to have to understand that what’s happening to cause this advance is human beings at the moment, or it could be systems doing it, but at the moment, human beings are making new connections and moving this forward and it’s going faster and faster and its converging and they’re compiling, all that’s happening at the same time but up here at the top at the pinnacle of all this, singularity is where knowledge creation and the process for how we as a human race do this knowledge working thing comes together and we do it as one. So, and I hope everyone’s with me, it can be kind of complicated, bear with me. [31:35] Diagram: Enterprise This is the same picture only with a little different frame. Here is your singularity curve, this is knowledge advancing, people making connections and answering questions and structuring them, so it moves forward toward singularity. What happens is, we deal with this balance issue: there’s economy, which is the center of economy, which is supply and demand, there is social context, which is a balance of interests, that’s the center of it, this is things like governance, government, legitimacy, public policy, [economy] this is things like business, education, a feeder pool to business, economic development, and then Knowledge Advance, and the center of that is our Knowledge Creation process. The problem in society today, is that we have economic and social enterprises that are operating by, and let’s leave this aside for a minute [pointing to the Enterprise diagram] but there’s a process these enterprises operate against and they might get heavy on the economic side. For example, in a capitalistic system, enterprise is very heavy; in a socialistic system, social context is very heavy. In a communistic system, they might try to suppress both. The whole system of Knowledge Advance, economy and social context is one system, it all works together to advance the human race around one knowledge. Again, if you think of knowledge as one, which it is, we’re trying to get to, this thing becomes a single effort, not my effort, your effort, or this group, or this organization, we’re really trying to do this all together. If you realize that those three (Knowledge Advance, Economic, Social Context] are happening at the same time, the goal is to, in a balanced way and in a cooperative way, move forward society toward singularity. And that is what this Question Science does, it takes economics, social context, and Knowledge Advance and says, hey, how do those three work together to move forward society in a cohesive way where we’re all seeing the same thing and doing the same thing? They do that through enterprises. Enterprises are where we take knowledge that has advanced and we apply it. We might ask questions, come up with decisions, we might say and do things, and we might have a result and measure the impact, and in our networked world there is a dialogue around all of those. There are a lot of representations for enterprise and this is one interpretation of how enterprise looks. But Enterprise is the ‘do’ and over here [pointing to the Knowledge Advance, Economic, and Social Context Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 9 area of the map] is the ‘know’ and what we have to do is learn the balance between the, now we know something new, we’re working new knowledge together, how do we then take that to our networks and apply it in an enterprise fashion to accomplish something either in society or economy to achieve a goal and to keep the whole foresight, and balanced approach, and adaptable method so we can actually deal with this curve [the curve toward Singularity]? What’s happening today is, even right now as we speak, economics has gotten off center, we’ve lost our balance economically, so to speak, and the socialist countries say, “Well, that’s the problem, you are economically centric”, well, you can also get too far off on the Social Context piece and be more worried about governance than Knowledge Advance, or not doing it cooperatively. You could say, “Well, we don’t want to work with you, we don’t want the knowledge to be one, we want the knowledge to be two, or three, or five thousand, we want it all to be separate” so things like intellectual property warfare, knowledge warfare in the military, all of those things are symptoms of seeing knowledge separately. It’s the battle for knowledge that’s existing, there’s this higher plane all of this goes to when you see the Question, there’s this higher plane you can go to that says, hey, wait a minute, time out. Everything that we are doing is this broad approach to one knowledge and lots of little factions dealing with it. Can we step back and see things like the Internet and the deep web, which is the databases under the Internet, and say, how do we work this together? How do we then take that new knowledge we’re working together and in a cooperative way apply it to Enterprise? I have a whole system for how to actually do Enterprise one way that it doesn’t matter if you’re in the military, or if you are in education, or if you are in business, it’s really one process for how to implement anything, and how do we make those connections, and how do we take networks and enable people across all these networks and communities to do this cooperatively? There is an underlying thing, and I’m done with my slides, there is an underlying thing to all of this, which is really interesting which is, if you take that simple singular process of knowledge creation and say, well, that’s how it all works, everything’s created that way, I might need to learn by extracting knowledge, but how does the machine fit into all of this? If you talk with Artificial Intelligence folks, which I’ve had a lot of conversations with, I respect them highly and they are very intelligent, but they are very mathematically focused for the most part, some process, mostly its an either information technology or mathematical approach. If you talk to those folks about process, its kind of this foreign world, how does knowledge work? Well, it doesn’t matter; the problem with “AI” - Artificial Intelligence – our problem of AI is an IT problem. It’s a technology problem. I would argue that that Singular process I’ve just showed you, that Five-Step process, works in human or machine. It doesn’t matter, if you talk about this term “machine learning” – what it really means is, a machine extracting knowledge from another machine or from a human, that is what machine learning is. If you confuse learning with knowledge creation, and you start calling this Question structuring, learning, then it gets really bizarre and confusing and everybody gets totally confused. Intelligence – the word ‘Artificial Intelligence’ – intelligence is really knowledge stored that can be retrieved. When I was a High School student, we had an IQ show, where everybody got on and answered questions, it was like a panel contest between schools and whose the most intelligent? One thing we were judged by was how much information they had stored in their minds and could retrieve. We have social knowledge bases in our minds, we’ve stored information, knowledge, Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 10 which I would say are the same thing and arguable by a lot of folks, but knowledge and information need structure and they have structured knowledge and categorized it in their minds and they can pull it out of their mind and retrieve it and give it back to the person as an answer. That’s intelligence. Some folks get intelligence mixed up with enterprise in the Artificial Intelligence circles; they think intelligence is goal-centered activity. That’s performance. That’s enterprise. That’s doing. Intelligence is just being able to recall information that you’ve stored. How much have you stored and how much can you recall? So when the students answered the questions, the ones that answered the most win and they are deemed most intelligent. In computer system terms, this whole thing extrapolates from a human process to a computer process. Artificial intelligence has already existed for years, we’ve been trying to create it but it has existed for years because all it is, is storing it and extracting it. We’re becoming more and more intelligent because we are compiling knowledge across all these domains into one knowledge based called the Internet and we’re making it available via Search which is a learning question, and we’re going to bring that forward into society, to people, make it available to individuals to use and apply in Enterprise, to be able to do things. So, the whole system that we have set up of networks, computers and hard drive on servers, server storage, that is really effectively creating machine intelligence and machine learning, Google is a form of machine learning. You can actually take information from a computer and put it into a human mind. So there is an interaction with Google, between an intelligent machine and a human being that needs to learn something from the intelligent machine. The Five-Step knowledge creation process transcends human beings and computers and we interact with computers, that’s how this whole process works, it’s an interactive thing between the computer, the machine and the human being and the groups of human beings. That is not your standard AI view. If you talk to AI Scientists, most of them are centered on things like expert systems, which is, how does a human being think and the cognitive science world does the same thing. They try to figure out how does a human being think and what’s happening in the neurons and how are all the synapses firing and all that, they are trying to figure out a non process centric view, which is impossible. That just causes frustrations, confusion of terms. You have to bring it up and look at, what’s the process humans use and then apply that to a machine. If you say that intelligence is just knowledge stored, then I can become more intelligent by bringing information into my brain or I can make the machine more intelligent by taking it into its brain, or by connecting machines, I can make machines more intelligent, and if I connect all machines, which is the concept of the deep web, I can actually go out to all the databases in the universe, in the world, I can bring all that knowledge into one and make all human knowledge accessible. That’s a fully compiled intelligence, that’s a social knowledge base, that’s one knowledge. If I have that, let’s say theoretically the deep web exists and we’ve brought all this information and all this logic now exists as one thing in human society, what happens with this Artificial Intelligence concept? There is an argument in Artificial Intelligence that’s called big AI or little AI? Is it about the whole social system of knowledge or the individual, the human being and how they know? Actually, it’s both. The human being interacts with this big integrated compiled sphere of intelligence to either learn or create knowledge. The machine can learn or create knowledge and the same Five-Step process that a human being uses to create knowledge, a machine could do. Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 11 [43:44] Diagram: Singularity If we go back to this Singularity document, and I’ll show you in the context of Artificial Intelligence, when the machine starts to create knowledge, to be able to take this fully compiled integrated knowledge down here, the social knowledge base and take it and advance it itself, so the machine can create new knowledge, that is Singularity. That is where we’re heading. That’s the whole “Ah, hah!” moment in human existence that’s going to occur when we realize that knowledge is one thing, we’re all moving toward working it together, we’re all moving toward this point in time when the machine can actually take over that process to the limits of its intelligence or storage capacities. How would the world change, if in fact, we have one knowledge and the machine could expand it? The machine could to the limits of its hardware capabilities make it larger? How would human beings deal with that machine and interact with it when knowledge is in effect, moving on its own? That is really true, what I call “knowledge creation” that is what Singularity is. We’re heading toward a point in time when we realize, “Oh gosh, its all one thing” and we’re going to move it together and we’re going to go toward this point called Singularity and the machine can literally take it over. There is an argument in these circles that talks about ‘intention.’ Intention is motivation; it is what moves us. Do I intend to do something? Did I intend to go to the store? The question of, the whole Terminator scenario, where the machine starts taking over and killing all the people, is really around, does a machine have intention? Can a machine form an intention to do something? I would argue that a machine does not have intention and cannot have intention. There are other folks who say it could. But in the context of say, it can’t decide to do something, a human being has to tell a machine, “Go make a bomb and kill people.” Or, “Go create a library and help people learn.” The human being intention is transferred to the machine and then things are done. Knowledge again, enables people to do things, it enables enterprise. If this machine can create knowledge expansively to the limits of what we can store, what would be possible? I think the Terminator scenario is impossible because I don’t think the machine can intend to do something. If the human being can take all that new knowledge that is being created and go apply it, go do something, go intend to do something, and create things. Essentially what happens in Singularity and machine knowledge creation is a space age, a space society. That’s the great big paradigm shift that’s what we’re all moving toward. So, I want to bring all that Sci-fi view back down to where you live because all of this is relevant to your enterprise. Individuals today are unaware of this cooperative process and how things are moving forward and how they need to balance all of these factors. What we really need is a cooperation between networks and communities, which is human minds coming together, and systems, which is machine intelligence coming together, and how do we cooperatively do all of this stuff? If you take the mind that, well, it doesn’t have to integrate, I’ll just do my thing and we’ll just build our economy – well, you can see what happens when we just build our economy we’re living it today [referring to the global stock market crash Oct 2008]. Or, we’ll just build our society we don’t need our economy, well, go and talk to the folks in a few of these countries that do that and you’ll say we live a lot better than they do. On the other hand, our system might not last because we go too far the other way. Let’s learn how to balance that, how to network people around one process and how to move forward intelligently knowing what we are moving Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 12 toward and what’s going to happen with this future state of knowledge working, and how do we, and not in a way that we fight knowledge wars, not in a way that we have intellectual property battles, but cooperatively as a human race, we have changed the entire paradigm into something that turns from my thing and your thing to a cooperative thing, we’re working together and it becomes cooperative – a term I use is ‘cooperative knowledge working’ – to be utilized or to enable enterprise in such a way that we’re aware of the future, aware of what’s coming and we can more effectively and together in a balanced way, in an agile way, we can move society forward. That’s essentially it, a lot of complicated processes but in the end it comes down to that one little thing: the question, that when you see it and face it, changes everything from the ground all the way up. So, I appreciate your time and thanks for allowing me this opportunity to share. With our generous thanks to Bruce LaDuke. The Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Floor Cleveland Ohio 44103 USA Copyright 2009 I-Open Creative Commons License Attribution-Noncommercial No Derivative Works 3.0 United States Organizations Articles • http://hyperadvance.com/blog/?page_id=6 • Journal of Medical Marketing (2009) 9, 131–139; doi:10.1057/jmm.2009.13; published online 5 June 2009, “A concise framework for medical education terminology” Erin Kingshill, Bruce LaDuke, Steve Willis. Journal of Medical Marketing. The article talks about the difference between communication, education, training, performance support, and performance: http://www.palgrave- journals.com/jmm/journal/v9/n2/abs/jmm200913a.html Related Interviews • Midtown Brews -- Futuring: The Knowledge-Question Cycle and Getting to Enterprise Fri Jul 10 21:37:07 EDT 2009 [01:16:56] http://www.livestream.com/midtownbrews • How Futuring helps us to know what do Now [03:19] Vimeo, Livestream • Connecting Knowledge to Enterprise [03:19] You Tube • Integral Futuring: cooperative knowledge working, a process approach to Knowledge Advance [49:32] Livestream http://www.livestream.com/iopen Biographical Information • Bio Page (With research overview papers, websites) • http://hyperadvance.com/blog/?page_id=5 Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA
    • 13 Examples of Work • http://hyperadvance.com/blog/?page_id=81 Contact Information Bruce LaDuke Greenwood, IN knowledgemachine@hotmail.com Mobile: Copyright 2009 Betsey Merkel and I-Open. Creative Commons 3.0 Attribution- Noncommercial-No Derivative Works. Institute for Open Economic Networks (I-Open) 4415 Euclid Ave 3rd Fl Cleveland, Ohio 44103 USA