Wednesday, August 6, 2003

How Did We Think in the Last Millennium? (我們前一千年的的思想)

How Did We Think in the Last Millennium? (我們前一千年的的思想)
[創意組織 ]

How Did We Think in the Last Millennium?

WHAT will the new millennium bring? To forecast the future, we should process the past. The last thousand years have been astonishing in their extremes. Humanity was wondrously transformed--from knights on horseback to kids on computers--but the price paid was very high. So much collective suffering; so much individual agony. If how we think helps to define how we live, then it should be useful to look at the thought processes that led to the triumphs, as well as the ravages, of civilization. Our future may depend on our ability to think, and perhaps think differently than we have in the past. So let's attempt to understand the nature of thinking itself--rational versus creative thinking; deductive versus inductive thinking; logic versus perception; analysis versus synthesis; game theory, heuristics, algorithms, the "expert systems" of artificial intelligence. What does each contribute to our intellectual and material advancement, and how do they further (or inhibit) our personal, social and political relations? If we can think more clearly, shouldn't we be able to live more happily? Understanding thinking--its categories and applications--is the specialty of our panel. What's particularly interesting is how the diversity of their fields affects the direction of their thinking.


Edward de Bono, author of over fifty books, including Lateral Thinking: Creativity Step by Step and De Bono's Thinking Course, is an international authority in both creative thinking and the direct teaching of thinking. Edward calls for design, synthesis, and creativity in human thinking.

Dr. Edward Feigenbaum, a professor of computer science at Stanford, is often called the father of expert systems, which are software programs that incorporate the best human thinking. Ed explains how artificial intelligence can assist our thinking.

Graham T.T. Molitor, a prolific author about the future, is vice president and legal counsel of the World Future Society. Graham believes that our brains will ultimately be enhanced through advances in genetics and neuroscience.

Dr. Sherwin (Shep) Nuland, a surgeon and medical ethicist at Yale University School of Medicine, is the author of How We Die, a poetic book describing the end of the human lifecycle. Shep sees human beings as mostly irrational by nature.

Dr. Brian Skyrms, a professor of philosophy and social science at the University of California at Irvine, is the author of Evolution of the Social Contract. Brian examines the nature and tools of thinking.

ROBERT: Edward, you've taught creativity and thinking to schools and corporations throughout the world. What are your notions about how we handled these matters over the last millennium? Why such extremes?

EDWARD DE BONO: On the whole, our thinking has been rather disastrous. The three Greeks--Plato, Aristotle, Socrates--really wrecked Western thinking, which has been concerned only with truth, analysis, judgment, argument. This type of thinking has led to persecutions, wars, discrimination, pogroms. What we've left out is "What can be?" thinking. "What can be?" thinking is design, creativity, synthesis--putting things together to achieve something new. We've had a very limited thinking system--a system excellent in itself, but only as the front left wheel of a motor car is excellent. By itself, it's inadequate.

ROBERT: Ed, how can so-called expert systems help us understand human thinking?

ED FEIGENBAUM: Expert systems are part of a field in computer science called artificial intelligence, wherein scientists and engineers are attempting to create models of human thinking, primarily the models of thinking that Edward [De Bono] was just calling "the front left wheel" of the automobile--namely, logical thinking. Expert systems are attempts to model the knowledge and the expertise of first-class human professionals [for example, physicians], who are practicing their professions at very high levels of performance. This relates to the ultimate goal of artificial intelligence: to generate programs that are extremely intelligent--that is, beyond human capability.

ROBERT: Brian, as a philosopher you've explored the concepts of decision making and rational choice. What is a "social contract" and how can it help us understand the collective thinking of the last millennium?

BRIAN: The social contract is a metaphor for a kind of tacit agreement, or deal, that people make in order to form a society and live together in it. A lot of philosophers try to justify ethical rules by saying that they would be part of an ideal social contract. But we can also think about how the actual social contract of real institutions arises from evolutionary and learning processes. That's the sort of thing I'm interested in.

ROBERT: Shep, you're a surgeon who has written two extraordinary sensitive books, How We Die and How We Live. Do you see a shift in human thinking as we enter a new millennium?

SHEP: Not essentially. To me, human thinking is unfortunately irrational. We retreat to magical thinking at every opportunity. As much as I applaud attempts to make thought processes coherent and complete--to put four wheels on that automobile--I think ultimately we're dealing with a flawed creature and a flawed way of putting information and memories together.

ROBERT: Can't we improve our thinking?

SHEP: We certainly can improve it. That's what this is all about.

ROBERT: Good, we'll give it a shot. Graham, as a futurist, you usually look forward. But start by looking backward.

GRAHAM: The last thousand years had some extraordinary benchmarks. We came out of the depths of the Dark Ages and we launched this world of ours into the era of the Enlightenment. We spawned great scientists and inventors, like Leonardo Da Vinci--many of the things he conceived became reality. Then in the last two hundred years came the development of mechanization, mass production, electricity, nuclear energy--all of these powerful mechanisms that drive society and provide the foundations of our economy and the basis of our livelihoods.

ROBERT: But in what direction are these mechanisms taking us? Let's explore the nature of thinking by comparing those left and right front wheels--rational thinking and what we might call postrational thinking. Let's start with rational thinking. Brian, talk about some of its components, such as deductive and inductive thinking.

BRIAN: Deductive thinking, or deductive logic, is the kind of logic used in pure mathematics--that is, how we think about mathematical objects and their relations to one another. You don't have to know anything about the real world to understand deductive thinking.

ROBERT: It's like tenth-grade geometry, where we used axioms and rules of logic to develop proofs of theorems.

BRIAN: That's part of it, of course. But if you want to look at the real world and try to confirm your scientific theories or your medical diagnoses or what you think is the truth of a legal case, then you have to use inductive logic and inductive thinking. Inductive thinking deals with evidence.

ROBERT: It starts with data, the messy stuff in the world around us, and then we develop theories to explain that data, always testing the theories by doing experiments and making predictions.

BRIAN: In the real world, you cannot know the truth of any theory with the absolute certainty of formal logic.

ROBERT: Ed, in the work you've done in artificial intelligence, there are two concepts you use which I'd like you to define for us: heuristics and algorithms.

ED FEIGENBAUM: Well, first I should say that I see thinking as a discovery process, not a deductive process--discovery in a very large space of possibilities. Heuristics are those pieces of knowledge--tricks and rules of thumb--that allow us to prune that space of possibilities in order to get to acceptable solutions in a reasonable amount of time. These acceptable solutions aren't necessarily optimal, aren't necessarily the best, but they're good enough. Herbert Simon, one of the pioneers of artificial intelligence, coined the word "satisficing" to distinguish the process from optimizing. Now that's where algorithms come in. Algorithms are structured pieces of mathematical and logical thinking that computer scientists and mathematicians use that lead you step by step to an answer that is guaranteed to be the correct answer, but it could take a very long time to get there. Heuristics are shortcuts; you could call them elements of the art of good guessing, the knowledge that goes into pruning that big space of possibilities. It's what expert chess players know that novice chess players don't.

ROBERT: Chess is a wonderful field for analyzing algorithms and heuristics. You might think that since there are only sixty-four squares and thirty-two pieces, a supercomputer could consider all the moves in a normal game. But if this supercomputer were required to consider all the legal moves in a forty-move game of chess before making its first move, the universe would burn out before that first move could be made.

ED FEIGENBAUM: That's right. The total number of possibilities at the opening of a chess game is 1 followed by 120 zeros. It's impossible to calculate, so chess players use all kinds of heuristics. Here's one, for example: In the opening of a chess game, don't move the pawns at the edges of the board; focus on control of the center.

ROBERT: Edward, let's check the right wheel of your mental motor car--the other side of logic, analysis, and judgment.

EDWARD DE BONO: Something like ninety percent of all errors in thinking are errors of perception--this is indicated by work done by David Perkins at the Harvard Graduate School of Education--yet culturally we focus on logic. But logic can't even begin to be applied until there are concepts with which the logic can work, and these concepts are rooted in perception. Historically, we focused on logic because we assumed that the perceptions were given and obvious, but only in some cases is this true.

ROBERT: What is your perception of "perception?"

EDWARD DE BONO: Perception is a different system from logic. Perception works as a self-organizing information system. Logic works in what I call a passive surface system. And the differences are huge. I'll give you a practical example of the differences. Imagine the bottom of a diamond mine in South Africa, with illiterate workers who have never been to school in their lives, who come from seven different tribes, and so on. They used to have two hundred and ten major fights, disputes, grievances every month. So we started teaching them how to think. Those two hundred and ten fights a month dropped to just four. It made a huge difference to their lives: productivity is up, absenteeism is down, safety is up. One can teach thinking very directly. I'm involved in schools in many countries now, doing just that.

ROBERT: What's the theory underlying lateral thinking?

EDWARD DE BONO: Lateral thinking tells you that if you look at self-organizing information systems--how we think--they form patterns that are asymmetric, meaning that from the end of the pattern you can see all the way back to the beginning, but from the beginning of the pattern you cannot see all the way forward to the end. Lateral thinking is [a way to deal with this asymmetry], and it's based on the process of provocation--and we've coined a new word, "po," which means "provocative operation." For instance, in the case of river pollution, you put in a provocation by stipulating that factories should use their own pollution. It sounds illogical, but from that comes an idea which is now the law in many countries--that if you build a factory on a river, your water input has to be downstream from your own output, so that you're the first to get your pollution.

ROBERT: Provocations are intermediate steps for creating new ideas; they are deliberately unsettling and disturb the current equilibrium.

EDWARD DE BONO: Provocations allow us to jump from one equilibrium to another. Once you're there, you see in hindsight that such new ideas are of course obvious. There are various techniques of lateral thinking--random input is another; they're all based on asymmetric patterns in self-organizing systems.

ROBERT: How do hypotheses figure in your system of thinking?

EDWARD DE BONO: We can talk about testing hypotheses, but where do the hypotheses come from? Hypotheses are creative possibilities, and progress always comes from creating new possibilities. Indeed, Chinese culture, which was way ahead of the West two thousand years ago, came to a dead end, because they never developed the possibilities of hypotheses.

ROBERT: How do you break out of the normal, or traditional, way of thinking?

EDWARD DE BONO: You need to look at thinking as the operation of a self-organizing system. There are various tools, such as attention-directing tools. Let's give an example. One of the simplest tools we use in school is called the PMI--Plus, Minus, Interesting. I asked a class of thirty kids, "Would it be a good idea if you were paid to come to school every week?" Thirty out of thirty said, "Great we'd love it; we can buy candy, chewing gum, comics." I didn't argue with them; I didn't ask, "What about this, what about that?" Instead, we introduced the PMI, and they thought about my question in terms of plus points, minus points, and interesting points. At the end of the session, twenty-nine out of thirty had changed their minds. On their own, they had conducted a little perceptual scan; there was a bigger picture to see, and as a result their perceptions changed and their decision changed. Emotions changed, too, and that's key. If you change perception, you change emotions. Logic will never change emotions; perceptions will.

ROBERT: Brian, let's talk about game theory. This is a relatively new area of thinking that is often used in behavioral science.

BRIAN: Game theory is a misnomer. It's really the theory of strategic interaction. It was called game theory because games like chess are special examples of strategic interaction. But of course there are many such examples: war, international politics, coalition formation, oligarchies controlling prices, and so forth. These are all situations where what's good for me depends on what the other guys do. And what's good for them depends on what I do. You can't optimize your position without worrying about how the other guys are optimizing their positions.

ROBERT: So this kind of thinking doesn't occur in isolation; you have to be concerned about what the other person is thinking.

BRIAN: You have to model the other person's thinking, you have to model his thinking about your thinking, and so on. It can get very complicated.

ROBERT: But this is closer to the real world?

BRIAN: This is closer to the real world. The question is, How many levels up do you have to model before you can get a sufficiently good answer? Game theory is a kind of deep dynamic analysis that explains how people grope their way to a solution, so that when they are finally at a solution point, each is happy with what the other thinks, and with what the other thinks you think, and with what each is doing. These strategic interaction problems are solved not only by people but also by animals in all kinds of interactive systems.

EDWARD DE BONO: But there's an underlying point here, which is if you set out a strategy of "win-lose"--that is, I'll win because I'll make you lose--then your strategic thinking will follow that design. But if you set out a strategy of "win-win"--in other words, how can we both benefit?--your whole thinking structure will be different. It all depends on the underlying assumption.

BRIAN: Win-win is not always easy, because there may be different ways to win-win. If we want to coordinate something--say, if I want to meet you someplace, but we haven't decided where--win-win is when we both get to the same place. But I still have to worry about going to the place that you think I'm going to, and the same is true for you.

EDWARD DE BONO: Sure. But I meant that underlying game theory was the notion that one person wins and one person loses.

BRIAN: That was in the 1940s, when game theory was originally devised.1
{FOOTNOTE}1 Game theory is a new branch of mathematics that was conceived by John von Neumann, a mathematician, and Oskar Morgenstern, an economist, to solve problems in economics (e.g., optimum pricing strategies). Since then, game theory has been applied in politics (e.g., coalition building), military planning (e.g., strikes and counterstrikes), business (e.g., product positioning or plant locations)--situations in which there are a number of decision-making players who have similar, opposed or mixed interests.

But now, modern game theory deals mostly with situations of win-win or partial conflict and partial cooperation.

ROBERT: Graham, how much of the future is dependent upon ways of thinking? Wouldn't different mechanisms of thinking lead to different futures?

GRAHAM: Well, yes. But I think that the key to assessing the long-range future is recognizing that there are a thousand tiny threads that tie the tapestry of tomorrow together, and one must look back carefully to see what the precedents and benchmarks are. I take a little different approach to thinking. One gross measure has it that we use only approximately one to three percent of our brains. We may use no more than ten percent--which means that we can move up the scale, so that we can use, say, as much as ninety-seven percent of our brain capacity. Will we do that? I think the answer is yes. I go back and look at the crude surrogate for intellect--which is basically average brain size, the cubic centimeter measurement. For the first [hominids], it was about 500 cubic centimeters, and it's about three times that today. By the year 3000, with advances in genetics, my feeling is that the size of the human brain will increase drastically, up to as much as 2,000 cubic centimeters.

ROBERT: That three-percent brain utilization idea sounds to me like a popular misconception. And I question the wisdom, if not the ultimate technology, of brain enlargement.

SHEP: Wait. Why should brain size increase, if we're only using three to ten percent? Wouldn't cultural evolution simply mean that we'll begin using ten to fifteen to twenty percent, and therefore there's no evolutionary need for brain size to increase?

EDWARD DE BONO: The pinheads will be happy.

SHEP: Furthermore, the last significant evolutionary change in human brain size occurred twenty-five thousand to forty thousand years ago, and in spite of the enormity of the input that humanity has been subjected to, our brain size hasn't changed one bit since.

ED FEIGENBAUM: Graham [Molitor]'s argument completely ignores the growth of artificial intelligence. When computers are doing a great deal of our thinking, there will be no evolutionary pressures to increase our biological brains' capacity.

GRAHAM: Well, I'll go a step further. Right now, we can augment our visual and auditory capabilities through implants. There will be a lot more of that--and I agree with you a hundred percent that this is another technological trend.

EDWARD DE BONO: You can simulate a brain with only five neurons on a computer; that brain is capable of fifty billion thoughts. Five neurons, fifty billion thoughts. We've got a hundred billion neurons. So brain size, I think, is irrelevant. It's how we use what we've got that counts.

GRAHAM: Well, I said it was a crude surrogate. There's also the long-standing conundrum about whether genetics or environment is the controlling factor [in intelligence]--I say that both are.

ROBERT: I agree with that. But are you saying that evolution will not proceed in its normal way--that through genetic enhancements we'll be able to increase brain size?

GRAHAM: Well, the historical data tell us that we now have a brain roughly three times the size of our hominid predecessors. But several other things have to happen here. You have to increase the bone structure to support a larger head. You have to increase the size of the pelvis, to allow the head to pass through the birth canal.

ROBERT: But I don't think that brain size has any relationship to what we do with our brains. If we need amplification or artificial intelligence, it's right there. What we're doing with our current brain size has not been all that good.

EDWARD DE BONO: We need better software for our brains.

ED FEIGENBAUM: Exactly. As Robert mentioned earlier, there has been an enormous transformation in the past millennium, but not any in brain size or function; that is, there has been no change in the hardware--what we call the wetware. What has changed has been the introduction of an enormous number of new knowledge artifacts into our collective culture--artifacts that we store and use and build upon, such as new concepts, new vocabulary, new technologies, and so on.

EDWARD DE BONO: Here's an example of what I mean by better software. Our normal argument mode is a primitive and often barbaric method of thinking and should be supplanted by parallel thinking. Parallel processing in humans, not machines. One large corporation, using a framework I designed for parallel thinking, reduced discussion time on a national project from twenty days to two. Two days! Huge increases in productivity, just from using better thinking software.

ROBERT: What about the role of emotions and feeling in the thinking process? Aren't we leaving these out?

SHEP: Emotion--that brings me back to the notion of perception. It seems to me that perception, as Edward [De Bono] is describing it, is really the interpretation of observations; and the way we perceive comes from our background, the memories we have, our emotional state, the stake we have in observing something one way or another. The result is that the same observation will be interpreted, or perceived, in many, many different ways. For example, the Greeks noted that people with cancer became depressed, so they were certain that depression was the cause of cancer. Although [coincidentally] they may turn out to be partially right, this was a mistake in interpreting observation, which is a mistake in perception. How do we solve the problem of what people bring to the perception in the first place?

EDWARD DE BONO: That's the point; you're right. Perception is the aggregate of experience, emotions, momentary attitudes, and the like. We can develop methods of changing perceptions--for example, by encouraging different ways of looking at the same situation.

ROBERT: Are there dangers of programming thinking so carefully?

EDWARD DE BONO: No, no. These are just tools that open up a broader scan, and as a result your emotions change. So I agree that perceptions are the result of upbringing, background, chemical levels at the moment, but they're not immutable.

SHEP: The historical progress of science has been made on the basis of changed perceptions of the same observations or data.

EDWARD DE BONO: A hypothesis is a perceptual change. And it's sad that even in leading universities where I've been--Oxford, Cambridge, Harvard, London--so little time is spent on generating hypotheses. A senior executive in the CNRS--the Centre National de la Recherche Scientifique, in Paris--once said to me, "I want you to help my scientists generate hypotheses. They've been told that science is the analysis of data, and deductive conclusions. But without hypotheses, you can't get anywhere."

ROBERT: You're talking about inductive thinking.

EDWARD DE BONO: It's more. It's what you bring to the data. The analysis of data won't produce new ideas. The brain can see only what it is prepared to see. It's your hypothesis, your speculation, that says, "Let's look at this situation from this viewpoint; now what do we see?"

BRIAN: Hypothesis guides induction, but inductive logic doesn't give you the hypothesis.

ROBERT: Inductive logic evaluates the hypothesis.


ROBERT: Ed, are you a closet reductionist? Do you believe that thinking is completely knowable?

ED FEIGENBAUM: I'm not in the closet. I'm an out-front reductionist. Edward [De Bono] has said that thinking is software. I would say that thinking is software plus knowledge, running on an information-processing device. This device is the brain, and it can be understood, or known, at various levels. It's known at psychological levels; it's known at neurophysiological levels; it's known at molecular levels. It's complex, and although it's not completely known, it's completely knowable. There is no magic in our heads.

EDWARD DE BONO: I agree with that entirely. But one of the difficulties is that the universe changes. If you're looking at a passive information universe, the things you can know are very different from the things you can know if you're looking at a self-organizing information universe. Now, we know a lot about self-organizing systems. For instance, we know that provocation is a necessity, otherwise you get bogged down at a local equilibrium and you can never get more global.

ROBERT: If you have a self-organizing system with high complexity and emergent properties, it may be impossible to provide predictable explanatory mechanisms below the observable level, no matter how much analysis you do.

EDWARD DE BONO: You can analyze the behavior; you might be able to predict consequences, but you may not be able to predict exactly.

BRIAN: There are still dynamics that you can study. And there is still no magic.

ROBERT: We can't logically exclude the possibility that there may be other things that exist in the nature of reality that affect human thinking. There are religious views, spiritual views, other nonreductive theories of mind that deny that thinking can ever be totally reduced to computer programs. Do you believe that human-level thinking can be totally reducible to computer programs?

EDWARD DE BONO: No. Not computer programs, because computers don't work that way yet.

ROBERT: Yet? But ultimately, will they? This is the key question.

EDWARD DE BONO: Yes, sure.

SHEP: The discredited vitalist philosophers believed that no biological function was ultimately knowable. We now believe that all biological function is ultimately knowable. Human thought, just like human biology, is all ultimately explainable. I'm the ultimate reductionist.

BRIAN: The physical system is all that exists. The question is whether we can ever actually write down the state of the physical system in complete detail, and then write down the equations that govern it--so that we can predict what you'll be thinking five minutes from now. It's not at all clear that that will ever happen.

EDWARD DE BONO: I agree. I'd make an analogy to the relationship between the dancer and the dance. The dancer is the biological system, the dance is the performance. You can't necessarily predict the dance from the nature of the dancer, but the dance is dependent directly and solely on the dancer. Similarly, you can't necessarily predict thinking from the nature of the biological system, but thinking is dependent directly and solely on the biological system.

SHEP: Otto Loewi, who discovered acetylcholine, the chemical transmitter that excites muscle cells [and enables neurons to communicate in the brain], is supposed to have said, during a concert by the Guarneri String Quartet, that "there must be more to this than just a little acetylcholine." But that doesn't make the function unknowable at all. But speaking of transphysical things, let me ask Graham [Molitor] a question. Since all thought is value-tinged, and we're talking about methods of thinking, is there a role for philosophy, for theology, for examining the values of our society as we develop new methods of thinking?

GRAHAM: Well, philosophy and theology are regulatory mechanisms for controlling what is abroad in society. They are key, and they're responsible for major jumps--what scientists like to call paradigm shifts--in our values and our lifestyle. The most recent of these shifts occurred during the Renaissance, and we're in the middle of another one, which is mainly driven by computer science and artificial intelligence--all these things we've been talking about. If you think you're the ultimate reductionist, I'm probably the penultimate. We'll crack the genetic code, we'll understand how to encode life, and I see the same kind of principles applied to neural technology, to enhancing the brain. It will take a long time, but it will come.

ROBERT: I'll bring it back to the "perceptions" with which we started. Those of us schooled in science naturally come at the question of the contemporary relevance of philosophy or theology from a different perspective than do philosophers or theologians--or most ordinary people for that matter. We have to ask ourselves, Is our scientific method of thinking the sole system for accessing truth? Is our way the only way to view the world, examine reality, and understand thinking?

EDWARD DE BONO: Let's go back to the moral point. In England there's a school that accepts kids who are too violent to be taught in ordinary schools. When this school started teaching them broad perceptual thinking, the level of violence dropped to one-eighth of what it had been previously.

ROBERT: Let's take a prediction. One hundred years from now, what has happened to thinking?

EDWARD DE BONO: Every school in the world will be teaching my thinking methods. Kids will be much more productive, much more tolerant of one another, much more able to create value for themselves and for society.

BRIAN: We'll have better theories about some things. We'll have new tools that we can use. Look at the computing power you have on your desk right now, just running a word processor. You can analyze dynamical systems that nobody could analyze twenty years ago. Assisted thinking will lead to better and better predictions of complex systems.

SHEP: I think there'll be increasing recognition of the basic irrationality of human thought processes, and of the necessity for the kinds of changes that we've been talking about here.

GRAHAM: No matter how much we talk about the subjective or theoretical dimensions of existence, the basic sciences are what drive society. And by the year 2100 certainly, and probably before, the life sciences--particularly genetic engineering--will dominate society. It's the opening of a new era--with Dolly [the cloned sheep] and the complete description of the human genome being the major benchmarks--in which humankind will control its own evolution.

ED FEIGENBAUM: Not only will we have very powerful artifacts in the form of computers, and pattern-recognition machines to handle perception, but the construction of those machines will lead to a science of thought which is every bit as rigorous and useful for prediction as what we have now in chemistry and physics.


SO how do we assess the last millennium? Often the smarter we got, it seems, the stupider we acted. Rational, linear thought produced the most efficient social advancement, but also the most destructive human debasement. This is what happens when value-free analysis serves the capricious whims of conventional human nature. You get amplification: good gets better but bad gets worse. Genocide has frequently occurred alongside the most advanced science, several of the worst examples in our own twentieth century. So if we continue to be arrogant, bigoted, greedy and jingoistic, then rational thinking will continue to generate maximal trauma. Rational thinking makes good technology, but our cognitive processes must grow in order for humanity to prosper. Human thinking must change. We need novel, original ideas that can enable us to leap beyond the traditional boundaries of inquiry and establish new standards of value creation. We need synergy and harmony between rational and postrational thinking, the left and right wheels of our mental motor car working together. Our thinking must become creative and holistic as well as analytic and diagnostic. Try this combination of both kinds of thinking in your personal life, and your decision making will undoubtedly improve. It is the best thinking that brings us closer to truth.

Editor's Translations:

"On the whole, our thinking has been rather disastrous. The three Greeks--Plato, Aristotle, Socrates--really wrecked Western thinking, which has been concerned only with truth, analysis, judgment, argument. This type of thinking has led to persecutions, wars, discrimination, pogroms. What we've left out is "What can be?" thinking. "What can be?" thinking is design, creativity, synthesis--putting things together to achieve something new. We've had a very limited thinking system--a system excellent in itself, but only as the front left wheel of a motor car is excellent. By itself, it's inadequate."
[總體上, 我們的思想是相當慘敗的。 三個希臘人-- 柏拉圖, 阿里斯多德, 蘇格拉底-- 真正地擊毀了西方思想˙ 西方思想只關心真相, 分析, 評斷, 論據。 這類型思想導致了迫害, 戰爭, 歧視, 屠殺。 我們忽略了"什麼是可能的?" 思想。 "什麼是可能的?" 思想是設計, 創意, 綜合-- 彙集創新。 我們的思想系統非常有限-- 本質上可說是很優秀, 就像一個汽車的前面左輪子很優秀。 單獨, 它是不夠的。]
--- Edward DeBono

"Hypotheses are creative possibilities, and progress always comes from creating new possibilities. Indeed, Chinese culture, which was way ahead of the West two thousand years ago, came to a dead end, because they never developed the possibilities of hypotheses."
[假設是創意的可能性˙ 進展總來自創意可能性。 中國文化二千年前遙遙領先, 可是來到了死角, 因為他們從未發展假設的可能性。]
--- Edward DeBono

-- Bevin Chu

Explanation: How Did We Think in the Last Millennium?
Illustration(s): Edward de Bono, Edward Feigenbaum, Graham T.T. Molitor, Bruce Murray, Sherwin Nuland, Robert Lawrence Kuhn
Author(s): Dr. Robert Lawrence Kuhn
Affiliation: CLOSER TO TRUTH (CTT)
Publication Date: N/A
Original Language: English
Editor: Bevin Chu, Registered Architect

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