how we learn reading room: right distance

Tim Wu, The Master Switch, 2010 [ ]

https://drive.google.com/open?id=1IhN9QUg3y1ghWhNkBxPbDs63W0KmRBSp

https://drive.google.com/file/d/1IhN9QUg3y1ghWhNkBxPbDs63W0KmRBSp/view

pp.19-20

Through circumstance or luck, they are exactly at the right distance both to imagine the future and to create an independent industry to exploit it.

Let's focus, first, on the act of invention. The importance of the outsider here owes to his being at the right distance remove from the prevailing currents of thought about the problem at hand. That distance affords a perspective close enough to understand the problem, yet far enough for greater freedom of thought, freedom from, as it were, the cognitive distortion of what is as opposed to what could be. This innovative distance explains why so many of those who turn an industry upside down are outsiders, even outcasts.

p.20

The disruptive innovation, conversely, threatens to displace a product altogether. It is the difference between the electric typewriter, which improved on the typewriter, and the word processor, which supplanted it.5

p.20

But to be clear, it is not mere distance, but the right distance that matters; there is such a thing as being too far away.

(Wu, Tim, The master switch : the rise and fall of information empires / Tim Wu., 1. telecommunication--history., 2. information technology--history., 2010 )

(The Master Switch: The Rise and Fall of Information Empires, Tim Wu, 2010.)

____________________________________

“It takes time to gain experience and familiarity that

lead to the fineness of granularity wherein the sweet

spots lie. And, no, we haven't found a solution to

time travel. But the history of technology is full of

discoveries of how to move [slower], finer, smoother.

That is the heart of your quest—to find ways to

accelerate the rate and quality of gaining experience

that get you to the fine level. What all of this says

is that to be successful, we need to innovate around

the whole package, not just one part.”;

── Bill Buxton, February 06, 2008

Innovation & Design :

A Familiar Problem,

• gradual granularity refinement

http://www.bloomberg.com/bw/stories/2008-02-06/a-familiar-problembusinessweek-business-news-stock-market-and-financial-advice

• https://www.billbuxton.com/BW%20Assets/02a.%20A%20Familiar%20Problem%20Published.pdf

____________________________________

Nathan Rosenberg, Inside the black box: technology and economics, 1982

p.129

16 The role of highly specialized producers, and the question of what constitutes the optimum degree of specialization from the point of view of technological innovation, are highly important issues that are still not very well understood. Specialist producers tend to be very good at improving, refining, and modifying their product. They tend to be weak in devising the new innovation that may constitute the eventual successor to their product. They tend, in other words, to work within an established regime, but they do not usually make the innovations that establish a new regime. Thus, the buggy makers did not contribute significantly to the development of the automobile; the steam locomotive makers played no role in the introduction of the diesel, and indeed expressed total disinterest, until it was finally introduced by General Motors; and the makers of piston engines did not play a prominent role, in England, Germany, or the United States, in the development and introduction of the jet engine. The severely circumscribed technological horizons of specialized producers-to some extent an inevitable occupational hazard-may help to account for what one recent book on the aircraft industry describes as "an apparent proclivity on the part of once successful manufacturers to remain too long with the basic technology of their original success." Almarin Phillips, Technology and Market Structure: A Study of the Aircraft Industry (Heath Lexington Books, Lexington, Mass., 1971), p. 91. The point is that intimate familiarity with an existing technology creates a strong disposition to work within that technology, and to make further modifications leading to its improvement rather than its displacement.

(Inside the black box./ Nathan Rosenberg, 1. technological innovations., 2. technology─social aspects., HC79.T4R673 1982, 338'.06, first published 1982, )

____________________________________

Clifton Leaf, The truth in small doses : why we're losing the war on cancer ── and how to win it, 2013

p.188

Brain Druker, now director of Oregon Health & Science University's (OHSU) Knight Cancer Institute

“In part, I don't know that could have done what I did had I not trained in the Harvard system, made the connections that I did, and gotten the background I did. On the other hand”, he says, “I probably couldn't have done what I did if I didn't leave the Harvard system.”

One of the problem that I have with the Harvards, the Stanfords, the

Johns Hopkinses, is that it's almost the same as it is at the big drug

companies, where there's this herd mentality: there's “a way” of approaching

a problem and this is the way we approach it. And if you don't approach

the problem this way, then what you're doing is of less value and will

never work. It becomes a cookie-cutter approach to every problem, based

on what a few of the top leaders are doing. A new technology comes on

board and you see this enormous stampede where every lab at Harvard

will have that technology and they'll be doing [the same types of

experiments]. And for me, I needed to get off that treadmill and say,

“You go do what you're doing. I have this idea I want to test out.”

And that worked out for me.... Sometimes [it's important] just getting

out of that mix and being able to explore.

The funding system, however, makes it profoundly difficult for most scientists to do what Druker did, to go “explore”.

(Clifton Leaf, The truth in small doses : why we're losing the war on cancer ── and how to win it, 2013, )

____________________________________

Allen curve

correlation between distance and communication is called the Allen curve because Allen found that frequency of communication between engineers drops off exponentially as the distance between them increases. After about 50 meters, there's very little communication among groups of engineers.

to ensure that everyone is within 50 meters.

source: ???

____________________________________

Frans Johansson, The Medici effect: what elephant & epidemics can teach us about innovation, 2006

pp.146-147

It is not that the network is holding you back on purpose. There is no conspiracy. But your network will promote, support, and highlight ideas that are valued within it. And it squashes or removes ideas that are not. This inherent characteristic creates a difficult paradox for anyone pursuing an intersectional idea: If we wish to succeed at the intersection of fields, we have to break away from the very networks that made us successful. Why is it that some of the greatest obstacles on the road to the Intersection can come from people within our own discipline, from our customers, our organizations, our own cultures, or our other close relationships? To answer these questions, we must understand why we build networks in the first place.

(The Medici effect: what elephant & epidemics can teach us about innovation, Frans Johansson, 2006, 658.4063 Johansso, )

____________________________________

Mihaly Csikszentmihalyi, Isabella Selega Csikszentmihalyi, edited by, ‘Optimal experience: psychological studies of flow in consciousness’, 1988

Mihaly Csikszentmihalyi, The flow experience and human psychology

p.29

When we step beyond motivations based on pleasure, power, and participation, we open up consciousness to experience new opportunities for being that lead to emergent structures of the self. This is autotelic motivation, because its goal is primarily the experience itself, rather than any future reward or advantage it may bring. Paradoxically, however, new ideas, artifacts, and technologies of great usefulness are often discovered in activities that had no practical goals in view, but were engaged in exclusively for the enjoyment they provided (Huizinga [1939] 1970; Caillois 1958). The flow experience is the prototype of such intrinsically states of consciousness.

(‘Optimal experience: psychological studies of flow in consciousness’, edited by Mihaly Csikszentmihalyi and Isabella Selega Csikszentmihalyi, Cambridge university press, library call# 153 Optimal, 1988, )

____________________________________

Douglas Hofstadter & Emmanuel Sander, Surfaces and essences: analogy as the fuel and fire of thinking, 2013

p.342

The research of psychologist Michelene Chi long ago confirmed that categories constructed by experts in a given domain are very different from those constructed by novices, and that experts don't rely on the same cues as novices do in categorizing new situations.

p.342

Novices pay attention mostly to superficial aspects, simply because to them, those are the most salient qualities.

p.342

For example, novices in physics will tend to group together all problems involving pulleys, or all problems involving springs, whereas people who have more experience in physics will tend to group together problems that involve the same physical principles, such as the conservation of energy.

p.342

Only as an individaul's knowledge of a particular domain increases can there be a gradual evolution from categorization based on obvious features to categorization based on more abstract ones. When people eventually attain a high enough level of abstract knowledge of the important types of situations that frequently arise in a domain, then they are able to reliably apply this abstract knowledge by analogy to new situations whose façade are very different from the situations that they encountered during their learning phase.

p.342

The reason novices are drawn to objectively superficial features is simply that those are the only features they are able to perceive.

p.343

All of these categories are of course utterly invisible to the “novice”.

p.343

For an expert in the domain, the deep features are not elusive or hidden; rather, they are the most salient features!

p.343

We are thus brought back once again to the idea that the features people tend to notice in any domain are as deep as their perception allows, which is a function of the set of categories they have evolved over their lifetime.

p.343

It's for this reason that the deepest clues available are what guides a person who is searching for analogies ([ associations, links, relationships, similiarities, commonalities, likeness, proximity ]) between fresh situations and ones in memory. If a novice is not guided by deeper features, it's because novice-level knowledge doesn't afford glimpses of such features. It's not what is superficial but what is salient that catches one's attention, and this applies equally to novices and to experts. The difference, however, is that as one gradually acquires greater expertise in any domain, the identifying features of deeper categories gradually grow more salient. This is a genuine principle of cognitive economy, for it states that no matter what one's level of expertise is, when searching in memory for an analogous case, one goes as deep as one's expertise allows.

p.349

What they really mean is not the letter itself, but the role that it plays.

p.382

To choose one analogy over another is to favor one viewpoint over another. It amounts to looking at things from a particular angle, to taking a specific perspective on a situation. An insightful analogical take on a situation gives you confidence in your beliefs about the situation while also revealing new facts about it. A teacher, a lecturer, a lawyer, a politician, a writer, a poet, a translator, or a lovr may pass hours or days in search of the most convincing analogy, like a goldsmith crafting a beautiful chalice for maximal effect. Such individuals work very hard and very conciously to induce in their listeners or readers the same point of view, or the same emotion or feeling or judgement, as they have.

p.383

You feel that you are deliberately creating an analogy to advance a certain point of view, but actually it's the other way around: your point of view comes from a myriad of hidden analogies that have given you a certain perspective on things.

p.390

A category's familiarity has to do with how much one has been exposed to it, with the amount of knowledge one has of it, and with the degree of confidence one has in one's knowledge about it. One feels more comfortable with cars than rockets because one has seen many more of them, because one knows much more about them, and because one has greater clarity about how to get into and out of them, about what their control devices (steering wheel, brake, etc.) will do, and so forth. One is also, for similar reasons, far more familiar with gravity than with electromagnetism.

p.434

A key challenge for educators is thus to take into account the way people manage to adroitly sidestep the formal encoding of situations by exploiting the way their familiar categories, built up over years of interactions with the world, work.

p.435

A categorization can be outright wrong, can be partially correct, can be profoundly influenced by the knowledge, prior experiences, prejudices, or goals, conscious or unconscious, of the person who makes it, and can depend on the local context or the global culture in which it is made.

pp.339-340

By contrast, when in real life we are faced with a new situation and have to decide what to do, the source situations we retrieve spontaneously and effortlessly from our memories are, in general, extremely familiar. We all depend implicitly on knowledge deeply rooted in our experiences over a lifetime, and this knowledge, which has been confirmed and reconfirmed over and over again, has also been generalized over time, allowing it to be carried over fluidly to all sorts of new situations. It is very rare that, in real life, we rely on an analogy to a situation with which we are barely familiar at all. To put it more colorfully, when it comes to understanding novel situations, we reach out to our family and our friends rather than to the first random passerby.

p.361

They borrow a neat little “package” of various facts about phenomena that they ‘do’ know, taking (or mistaking) those facts for universal truths, and indeed, some of the facts in the packet will turn out later to be inapplicable to the new phenomena. And yet the best of such analogies contain so many grains of truth that they open up whole new perspectives, despite various incorrect assumptions that have been unwittingly imported from other domains. This kind of partly-insightful, partly-defective analogy-making is a hallmark of all humans, and will be discussed extensively in the next two chapters.

p.390

p.449

you begin with a “familiar” idea (that is, familiar to a sophisticated mathematician but most likely totally alien to an outsider), you try to distill its essence, and then you try to find, in some other area of mathematics, something that shares this same distilled essence. An alternative pathway towards abstraction involves recognizing an analogy between two structures in different domains, which then focuses one's attention on the abstract structure that they share. This new abstraction then becomes a “concrete” concept that one can study, and this goes on until someone realizes that this is far from the end of the line, and that one can further generalize the new concept in one of the two ways just described. And thus it goes...

p.452

Geniuses do not deliberately set off with the goal of concocting a wildsounding analogy between some brand-new phenomenon, shimmering and mysterious, and some older phenomenon, conceptually distant and seemingly unrelated; rather, they concentrate intensely on some puzzling situation that they think merits deep attention, carefully circling around it, looking at it from all sorts of angles, and finally, if they are lucky, finding a viewpoint that reminds them of some previously known phenomenon that the mysterious new one resembles in a subtle but suggestive manner. Through such a process of covergence, a genius comes to see a surprising new essence of the phenomenon. This is high-level perception; this is discovery by analogy.

(Surfaces and essences: analogy as the fuel and fire of thinking, Douglas Hofstadter & Emmanuel Sander, 2013, )

____________________________________

John Malcolm Blair, The control of oil (hardcover), 1976

pp.390-391

John L. Enos

French inventor, Eugene Houdry

the study of catalysis

developed the first practical catalytic cracking process.

1927, successfully produced motor gasoline from a heavy petroleum fraction.

inventors of continous thermal cracking processes,

Aided financially by Mobil and Sun, Houdry established the Houdry Process Corporation, which by 1936 had overcome the difficulties in the design of equipment and was in commercial operation. Since Houdry process was only semicontinuous, the next stage was to transform it into a fully continuous operation. While several processes were developed by Houdry and others, the nation's largest oil company used its scientific resources to avoid the payment of royalties: “Standard Oil (N.J.) ... deliberately tried to invent around the Houdry patents.”48

p.391

John L. Enos

In almost all cases the inventions were made by men close to the oil industry but not attached to the major firms.49

p.391

Edwin Mansfield

Using data for nine major petroleum companies, “the evidence seems to indicate the answer is no.” Petroleum is thus no exception to the conclusion for industry generally: “Although there is a certain threshold size , which varies from industry to industry, that must be exceeded if many kinds of development projects can be undertaken effectively, a firm's R & D expenditures generally do not increase in proportion to its size in the range much above this threshold size.”51

p.392

Edwin Mansfield

Mansfield also sought to determine whether the research and development work carried on by the eight largest oil companies differed from that of large, established firms generally, which he described as follows: “... the bulk of their R & D seems to be directed at relatively safe, short-term objectives, the radical advances often come from outside their laboratories, and they seem to be better at adapting, developing, and improving the novel inventions of others than coming forth with their own.”53

p.392

Edwin Mansfield

From his examination of the oil companies he concluded: “... the bulk of the R & D projects carried out by these firms is regarded as being relatively safe from a technical point of view, the median probability of technical success being at least 75 percent in most of the firms .... only a small percent of the money goes for basic research, and most of the R & D projects are expected to be finished and have an effect on profits in 5 years or less.”54

(The Control of Oil., John Malcolm Blair 1914─, 1. petroleum industry and trade., 2. petroleum industry and trade──United States., 3. energy policy──United States., HD9560.6.B55, 338.2'7'282, 1976, )

____________________________________

Clayton M. Christensen, Innovator's dilemma, 1997, 2000 [ ]

pp.85—86 n11

11. Makers of early hybrid ocean transports, which were steam powered but still outfitted with sails, used the same rationale for their design as did the Bucyrus Erie engineers: Steam power still was not reliable enough for the transoceanic market, so steam power plants had to be backed up by conventional technology. The advent of steam-powered ships and their substitution for wind-powered ships in the transoceanic business is itself a classic study of disruptive technology. When Robert Fulton sailed the first steamship up the Hudson River in 1819, it underperformed transoceanic sailing ships on nearly every dimension of performance: It cost more per mile to operate; it was slower; and it was prone to frequent breakdowns. Hence, it could not be used in the transoceanic value network and could only be applied in a different value network, inland waterways, in which product performance was measured very differently. In rivers and lakes, the ability to move against the wind or in the absence of a wind was the attribute most highly valued by ship captains, and along that dimension, steam outperformed sail. Some scholar (see, for example, Richard Foster, in Innovation: The Attacker's Advantage [New York: Summit Books, 1986]) have marveled at how myopic were the makers of sailing ships, who stayed with their aging technology until the bitter end, in the early 1900s, completely ignoring steam power. Indeed, not a single maker of sailing ships survived the industry's transition to steam power. The value network framework offers a perspective on this problem that these scholars seem to have ignored, however. It was not a problem of KNOWING about steam power or having access to technology. The problem was that the customers of the sailing ship manufacturers, who were transoceanic shippers, could not use steam-powered ships until the turn of the century. To cultivate a position in steamship building, the makers of sailing ships would have had to engineer a major strategic reorientation into the inland waterway market, because that was the only value network where steam-powered vessels were valued throughout most of the 1880s. Hence, it was these firms' reluctance or inability to change strategy, rather than their inability to change technology, that lay at the root of their failure in the face of steam-powered vessels.

____________________________________

Mark Stefik and Barbara Stefik, Breakthrough, 2004 [ ]

pp.181-182

Radical innovations are the ones that lead to widespread change and usually encounter widespread resistance. Disruptive change provokes obstacles. The more radical the changes, the greater the obstacles they provoke. Widespread change takes a long time, typically decades. The big challenges for radical innovations are often economic and social.

p.182

innovations face three kinds of obstacles:

difficult to innovate (the “long road”),

challenge conventional thinking,

require widespread changes before they become practical.

pp.183-184

Antibodies to Innovation

Robert Kahn

Although the industry now takes packet switching and many other technologies for granted, they faced huge resistance before they caught on. Kahn6:

There are a lot of invention that don't make it into the market simply because there are forces that don't allow it. For example, packet switching did not get adopted in the late 1960s or early 1970s when it first was worked on. When you look back now, 30 years later, virtually every communication system that has been built in the world since then has been built using packet switching. It is used not only for computer communications but for managing internal resources as well.

Packet switching didn't get adopted right away because it was too challenging or too threatening or so counter culture that nobody was basically able to make a decision to use the technology. I think this is a genetic problem with most innovation: The more serious the innovation the more likely that there will be the resistance to its acceptance fighting a push for its acceptance. It's as if the system has antibodies.

A lot of things I've been interested in have been about Infrastructure. Changes to infrastructure tend to upset whole areas of business. Consider what happens if you put a railroad or a light rail into an area. Right away the land around it becomes extremely valuable as compared to other land just by virtue of access to the infrastructure. New infrastructure tends to induce broad changes and often causes many kinds of push back.

There are many other examples of technologies that were difficult to adopt at first. Why didn't time-sharing computing get adopted right off the bat? When you look at the big computer companies in the early days, they were places like GE, Honeywell, IBM, and Burroughs. Time-sharing systems were very threatening to IBM back in the early days, because, instead of selling lots of different machines they would end up selling one that could be shared. Time-sharing had a potential to undercut their business. Yet eventually the economics of the whole field tended to force this as a long-term direction. I am sure you could think of lots of examples where a new technology created competition for some entrenched part of a current market and was resisted.

(Stefik, Mark., Breakthrough : stories and strategies of radical innovation / Mark Stefik and Barbara Stefik., 1. technological innovation., 2. inventions., 2004, pp.183-184)

____________________________________

Semyon D. Savransky., Engineering of creativity, 2000 [ ]

p.143

In his book for children ...And Suddenly the Inventor Appeared [6] Altshuller* writes, “If one chooses to develop a completely new technical system when the old one is not exhausted in its development, the road to success and acceptance by society is very harsh and long. A task that is far ahead of its time is not easy to solve. And the most difficult task is to prove that a new system is possible and necessary.” In other words, the inventor must be cautious because the public may not accept designs that are too advanced so support for further development will be limited. There are a few factors related to company practices and operations that also have to be considered in making the decision to proceed with new product or process development. These factors can be acquired by consulting with management, plant engineering, production, marketing, technical, and sales personnel. Introducing several incremental improvements to an existing system is often a good strategy. In the theory of innovation, this strategy is known as the diffusion process.

* He used the pseudonym H. Altov in some books.

6. Altov, H. (Altshuller, G. S.), ... And Suddenly the Inventor Appeared. Detskaya Literatura, Moscow, 1984, 1987, 1989 (in Russia); TIC, Worcester, 1996 (in English).

( Savransky, Semyon D., Engineering of creativity : introduction to TRIZ methodology of inventive problem solving / by Semyon D. Savransky., 1. engineering--methodology., 2. problem solving--methodology., 3. creative thinking., 4. technological innovations., 2000, p.143)

____________________________________

Frans Johansson, The Medici effect: what elephant & epidemics can teach us about innovation, 2006

p.2

“Get this, they don't use hooks when fishing for marlin in Cuba”, one visitor says.

“So what do they use?” another asks.

“Rags. The lure is covered in rags. When the fish strikes the rag, it wraps around the fish bill and won't let go because of the friction. The fish don't get hurt and can be released, no problem.”

“That's pretty neat. Maybe we would use something like that....”

pp.146-147

p.148

Those firms operating in a laptop value network, for instance, will value efficient energy use and small size more than those operating within a desktop value network. These values will color everything that happens in these organizations, from the promotion of new ideas to the allocation of resources. They will therefore greatly affect the people in it.

p.149

Imagine what the value network of a decently successful musician could look like. She will have acquired hard-earned skills with certain instruments. She will have developed great relationships with her band members, producers, and distributors──all of them creating and selling a particular brand of music. Together they will have established contacts with editors and executives in music media, and they will have relationships with club and show owners. These are people who understand her music and can promote it. MOst important, the artist will have an established fan base, people who can be counted on to buy new CDs or attend concerts. All of these individuals, firms, and customers form a value network around a particular type of music──and the artist is caught in the middle. Her situation is not necessarily all that different from that of a major corporation.

p.149

Value networks are needed to succeed within a field. That's why we form them. And that is, as you may have guessed, where all the trouble starts.

p.161

1984, Richard Branson

In February of that year an American lawyer named Randolph Fields asked him if he would be interested in teaming up to start a transatlantic airline. Most people would probably have scratched their heads, wondering why anyone thought a music company executive would do such a thing. Branson, however, was intrigued by the idea and he immediately conducted the following market research.

p.161

First he called the reservation office for People Express, an airline that offered cheap fares between London and New York. He got a busy signal and couldn't get through to a customer representative despite calling all weekend.

p.161

Branson concluded that People Express either had a disasterous management team, in which case they could easily be outcompeted, or that they had more customers than they could handle, in which case there was room for another competitor.

pp.161-162

The following day Branson called Boeing to see if he could lease a jumbo jet for a year, assuming he could return it if this airline thing didn't work out. After a day of shuffling Branson back and forth between different managers, Boeing finally agreed. Armed with this “detailed” analysis, Branson called his business partners.

“What do you think about starting an airline? I've got a proposal here....”

“For God's sake! You're crazy. Come off it.”

“I'm serious.”

“You're not. You're mad.”

Six months later Virgin Atlantic made its first flight from London to New York City.

p.162

Tens of thousands of people knew more about airplanes, airlines, and travel than Branson. What gave him the confidence to take them on? His market research consisted of only two phone calls, and one of them didn't even go through!

p.162

Branson happened to see a connection between how Virgin ran its music business and how it would run an airline (great customer service).

p.162

By studying people like him, we can unearth some important clues about how to face our fears at the intersection of fields.

(The Medici effect: what elephant & epidemics can teach us about innovation, Frans Johansson, 2006, 658.4063 Johansso, )

____________________________________

Michael Michalko, Creative thinkering : putting your imagination to work, 2011

p.xviii Brian Arthur, The Nature of Technology

As Brian Arthur argues in his book The Nature of Technology, nearly all technologies result from combination of other technologies, and new ideas often come from people from different fields combining their thoughts and things. One example is the camera pill, invented after a conversation between a gastroenterologist and a guided missile designer.

( Creative thinkering : putting your imagination to work / Michael Michalko.,

1. creative thinking., 2. creative ability., 3. imagination., FB408.M485, 2011, 153.1'5--dc23, first printing, September 2011, )

____________________________________

Frans Johansson, The Medici effect: what elephant & epidemics can teach us about innovation, 2006

pp.74-75

p.74

Of course, in order for it to work we must be able to associate freely between the different backgrounds, as discussed in chapter 4. If we can manage that, though, we can often transplant old methodologies or frameworks into the new environment and generate unusual idea combination.

pp.74-75

Consider, for instance, what happened when an engineer became curious about the long loops we have in our kidneys. For many years physiologists had assumed that the loops had no special function and were a relic of the way the kidney had evolved. But they reminded the engineer of a countercurrent multiplier, an engineering device for increasing the concentration of liquids. And he was right, that is exactly what they are used for in our bodies.4

4. Edward DeBono, New Think: the use of lateral thinking in the generation of new ideas (New York: Basic books, 1968).

(The Medici effect: what elephant & epidemics can teach us about innovation, Frans Johansson, 2006, 658.4063 Johansso, )

____________________________________

Tony Schwartz with Jean Gomes and Catherine McCarthy., The way we're working isn't working: the four forgotten needs that energize great performance, 2010

p.217

saturation >> incubation >> illumination

A surprising degree of consensus has emerged during the past 100 years about the basic stages of creative thinking [and creative problem solving (CPS)]. In the late 19th century, Hermann von Helmholtz, a physicist and physiologist, become the first scientist to suggest that creative ideas emerge in three predictable stages. The first (1st) he said, is saturation, which is essentially the gathering of facts. The second (2nd) is incubation, which is the mulling over of the information, often unconsciously. The third (3rd) is illumination, when some new combination of the data leads to a breakthrough or an "Ah-ha!"

In 1908, the French mathematician Henri Poincaré suggested a fourth (4th) stage, which he named "verification," to describe the point at which a creative insight is rigorously tested for accuracy. More recent, several researchers have suggested an additional stage that precedes the other four (4). The psychologist George Kneller named this "first insight," which he characterized as the point at which creative challenge is defined. The five(5)-step process therefore look like this:

first insight >> saturation >> incubation >> illumination >> verification

p.218

Saturation, the gathering of information, involves immersing one's self in the known, which is foremost a left-hemisphere activity. This second stage in the creative process involves not just gathering the information but also reading through it, sorting, evaluating, organizing, outlining, and prioritizing. This tends to be laborious, methodical work, and it is sometimes short changed, but always at a cost.

As George Kneller puts it: “One of the paradoxes of creativity [is] that in order to think originally, we must familiarize ourselves with the ideas of others.” Information, in short, represents the raw material from which original thinking emerges ── and the more knowledge one has, the better the base.

(The way we're working isn't working : the four forgotten needs that energize great performance / Tony Schwartz, with Jean Gomes and Catherine McCarthy. — 1st Free Press hardcover ed., 1. performance., 2. work — psychological aspects., 3. organizational effectiveness., 4. personnel management., p.217, p.218)

____________________________________

( 3.) total cultural context (TCC) [ ]

p.15

[...]

There is a popular misconception that creative efforts of the individual may transcend time and place. (This concept, incidentally, is typically Western in its individual-centered origin.) No anthropologist will agree with this. In the first place, the creative individual, like others, in the product of a particular cultural context. In the second place, even if a practitioner of any one of the arts produces something totally foreign to this cultural context, such a creation has little chance of general acceptance. Anthropologist have found, through their study of many diverse societies, that among any given people both the form and the content of their art and literature show a high degree of consistency both historically and with reference to the total cultural context. Chinese and Americans ([and others]) are no exception.

Seen in this light, art and literature are much more than the cerebral-emotional products of creative individuals. They are fundamentally what may be described as mirrors--or as the psycho-analyst says, projective screens--of the society to which the creative individual belongs. We shall look first at art and literature, for these mirrors register not only the surface concerns of the people in question, but also their deeper yearnings which often are not consciously recognized.

[...]

(Hsu, "Americans & Chinese," [DS 721.H685 1970], p.15)

("Americans and Chinese," Francis L. K. Hsu, 1970, The Natural History Press, p.15)

____________________________________

Clifton Leaf, The truth in small doses : why we're losing the war on cancer ── and how to win it, 2013

p.206

In actual practice, however, the path to discovery is often not much of a path at all. Good, solid science is just as likely to swerve from chance observation to a question, to still more questions, and not arrive at a hypothesis until long after the information-gathering is done. Discovery has often leaped from the wreckage of experimental error. Or it has emerged from the melee of random thought. Good science follows hunches and instinct and serendipity as often as it does any best-laid plan.

p.206

Good science is sometimes “ignorance-driven”, to use the phrase of Sir John Sulston, the Cambridge geneticist who shared the Nobel Prize in medicine in 2002.

p.206

Hypotheses and rigorous experiments follow in due course much of the time. But more important than any postulate is the scientist's ability to wonder──to ask inspired questions and draw tenuous connections from far-flung clues. And still more critical than that is his or her willingness to pursue the mystery, by whatever means, to wherever it might possibly go. “My first studies of the worm lineage didn't require me to ask question (other than ‘What happen next?’)”, Sulston wrote in his memoir.

p.206

Throughout the history of science it has not been the isolated hypothesis that has changed the world, but rather the person tenaciously following, exploring, proving, and expounding upon it.

(Clifton Leaf, The truth in small doses : why we're losing the war on cancer ── and how to win it, 2013, )

____________________________________

Arthur Koestler, The Act of Creation, first published in 1964

p.653

(pdf page 652/752)

ceteris paribus, on the nature of the challenge

Familiar situations──that is, the novelty and unexpectedness of situation. Familiar situation are dealt with by habitual methods; they can be recognized, at a glance, as analogous in some essential respect to past experiences which provide a ready-made rule to cope with them. The more new the features a task contains, the more difficult it will be to find the relevant analogy, and thereby the appropriate code to apply to it. We have seen (Book One, VIII, XVII) that one of the basic mechanisms of the Eureka process is the discovery of a hidden analogy; but ‘hiddenness’ is again a matter of degrees.

p.653

(pdf page 652/752)

How hidden is a hidden analogy, and where is it hidden? And what does the word ‘search’, so often used in the context of problem-solving, is apt to create confusion because it implies that I know beforehand what I am searching for, whereas in fact I do not. If I search for a lost collar-stud, I put a kind of filter into my ‘optical frame’ which lets only collar-studs and similar shapes pass, and rejects everything else──and then go looking through my drawers. But most tasks in problem-solving necessitate applying the reverse procedure: the subject looks for a clue, the nature of which he does not know, expect that it should be a ‘clue’ (Ansatzpunkt, point d'appui), a link to a type of problem familiar to him.

p.654

(pdf page 653/752)

Instead of looking through a given filter-frame for an object which matches the filter, he must try out one frame after another to look at the object before his nose, until he finds the frame into which it fits, i.e. until the problem presents some familiar aspect──which is then perceived as an analogy with past experience and allows him to come to grips with it.

p.654

(pdf page 653/752)

This search for the appropriate matrix, or rule of the game to tackle the process, is never quite random; the various types of guidance at the fumbling, groping, trying stages have been discussed before. Among the criteria which distinguish originality from routine are the level of consciousness on which the search is conducted, the type of guidance on which the subject relies, and the nature of obstacle which he has to overcome.

Arthur Koestler, The Act of Creation, first published in 1964

filename: Arthur-Koestler-The-Act-of-Creation.pdf

____________________________________

Arthur B. VanGundy, Managing group creativity, 1984 [ ]

p.49

Considering the first thought that pops into your mind can frequently result in a remote association that you wouldn't have made if you had been more deliberate in your approach. Thus people who impulsively jump to conclusions quite often have a fertile internal creative climate.

(VanGundy, Arthur B., Managing group creativity / Arthur B. VanGundy, 1. problem solving, group, 1984, HD 30.29 .V35 1984, )

____________________________________

"You need to understand how the human mind works. The mind has three elementary phases it goes through when it's thinking: saturate, incubate, and illuminate. Although they generally occur in order, all three are continuous processes, so your mind is constantly cycling through all three phases. The saturation phase occurs when the mind if first exposed to something. When you're planning a new mission, you're saturating your mind with facts, assumptions, insights and/or sensory cues - ergo, the saturation phase. the next phase is incubation. This is a critical phase if you ever want to come up with something innovative. The mind needs time to incubate. During this phase the mind subconsciously sorts through all of the inputs and begins to recognize patterns and snap those patterns together to come up with concepts and ideas. This is why you may have heard people say, 'I need to sleep on it' before making a major decision. It's not the sleep per se that they need: it's the time to allow their mind to sort through information and search for patterns. The recognition of patterns that occurs during the incubation phase produces the illumination phase, also known as 'eureka' moments, when your mind begins to translate those patterns and form the into actionable ideas. Saturate, incubate, illuminate - it's how the mind works, and it's probably the main reason why you have lost so much sleep over the years. The best thing you can do is to keep a pen and paper by your bed. Writing down your thoughts while you're incubating and illuminating should help to temporarily get the off your mind and back to sleep." (Page 70) (THE MISSION, THE MEN, AND ME: LESSONS FROM A FORMER DELTA FORCE COMMANDER, by Pete Blaber)

____________________________________

Semyon D. Savransky., Engineering of creativity, 2000 [ ]

p.135

In spite of the fact that there are only two reasons for inventions, there are various motivations. Some of them have been summarized by Edward and Monika Lumsdaine [1] as the following:

• As a response to a threat --> radar, weapons

• As a response to an existing need --> can opener

• As a response to a future need --> high-temperature ceramics

• For the fun of it -- as an expression of creativity

• To satisfy intellectual curiosity

• As a response to an emergency --> Band-aid

• To increase one's chance of survival and security

• To increase comfort and luxury in lifestyle

• Better problem solving --> hydraulic propulsion system

• Turning failure into success --> Post-It notes

• To overcome flaws --> “Magic” tape

• Accidentally, on the way to researching something else --> polyethylene

([ melted Hershey chocolate bar in a lab coat - microwave ])

• As a deliberate synthesis --> carbon brakes for aircraft

• Through brainstorming with experts or outsiders --> courseware

• From studying trends, demographic data, and customer surveys

• Through cost reduction and quality improvement efforts --> float glass

• Through finding new uses for waste products --> aluminum flakes in roofing

• Through continuous improvement of work done by others

• Through having new process technology --> proteins from hydrocarbons

• By finding new applications for existing technology

• Through having new material available

• To win a prize or recognition --> human-powered aircraft

• Meeting tougher legal and legislated requirements --> catalytic converter

• By having research funds available to solve a specific problem --> super-conductors

• By being a dissatisfied user of a product

• Responding to a challenge or assignment

• Because “it's my job” --> “I do it for a living”

• To improve the organization's competitive position

• To get around someone else's patent

([ also refer to as reverse engineering using blackbox method ])

•

p.137

Serendipity, or the principle of exploiting lucky breaks -- There are two types:

• a solver is stalled at a certain point in problem solving and a chance observation provides the answer: e.g., the famous case of rubber vulcanization by Charles Goodyear.

• a solver suddenly discovers a new principle unrelated to the work in which he is engaged but related to some other area, and then successfully applies this discovery to that area: e.g., discovery of the explosive properties of a potassium nitrate, charcoal, and sulfur mixture.

____________________________________

Nathan Rosenberg, Inside the black box: technology and economics, 1982

pp.142-143

p.142

This paper, then, is a kind of preliminary reconnaissance, the beginning of an attempt to develop a conceptual framework that will improve our understanding of the connections between science and economic performance.

p.142

In view of the obvious and compelling importance of this subject, I offer only a token apology for the fact that this paper is, at best, only the first small step on a long intellectual journey. I will argue that technology influences scientific activity in numerous and pervasive ways. I will attempt to identify some of the most important categories of influence and to sharpen our understanding of the causal mechanisms at work.

p.142

Of course, the influence of certain technological concerns on the growth of scientific knowledge has long been recognized. Torricelli's demonstration of the weight of air in the atmosphere, a scientific breakthrough of fundamental importance, was an outgrowth of this attempt to design an improved pump.2 Sadi Carnot's remarkable accomplishment in creating the science of thermodynamics was an outgrowth of the attempt, a half century or so after Watt's great innovation, to understand what determined the efficiency of steam engines.3 Joule's discovery of the law of the conservation of energy grew out of an interest in alternative sources of power generation at his father's brewery.4

pp.142-143

Pasteur's development of the science of bacteriology emerged from his attempt to deal with problems of fermentation and putrefaction in the French wine industry. In all these cases, scientific knowledge of a wide generality grew out of a particular problem in a narrow context.

p.143

elemental point: Technology is itself a body of knowledge about certain classes of events and activities.

It is a knowledge of techniques, methods, and designs that work, and that work in a certain ways and with certain consequences, even when one cannot explain exactly why.

p.143

gives only a very limited sense of the nature and extent of the interplay between science and technology. Indeed, that sense is totally suppressed in the prevailing formulation of our time,

p.143

it is common to look at causality as running exclusively from science to technology, and in which it is common to think of technology as if it were reducible to the application of prior scientific knowledge.

p.143

Thus, it seems to be quite worthwhile to examine the science ─ technology interaction with greater care.

p.144

As a result, technology has served as an enormous repository of empirical knowledge to be scrutinized and evaluated by the scientist.

(Inside the black box./ Nathan Rosenberg, 1. technological innovations., 2. technology─social aspects., HC79.T4R673 1982, 338'.06, first published 1982, )

____________________________________

Nathan Rosenberg, Inside the black box: technology and economics, 1982

The six other factors [prevalent factor identified as important in the innovations] were found to be of importance are:

(1) “Top person: the presence of an outstanding person in a position of authority” (25.1 per cent);

(2) presence of some other indispensable person, who was of crucial importance due to his or her specialized knowledge (14.7 per cent);

(3) “Realization of the potential usefulness of a discovery” (6.2 per cent);

(4) “good cooperation” (4.9 per cent);

(5) “availability of resources” (8.2 per cent); and

(6) “Help from governmental sources, including resarch associations and public corporations” (5.3 per cent), (Langrish et al., 1972, p. 69).

Five categories of variables were found to be most important in distinguishing successes from failures:

(1) successful innovators were seen to have a much better understanding of user needs.

(2) successful innovators paid more attention to marketing and publicity.

(3) successful innovators performed their development work more efficiently than failures but not necessarily more quickly.

(4) successful innovators made more use of outside technology and scientific advice, not necessarily in general but in the specific area concerned.

(5) the responsible individuals behind the successful innovations were usually more senior and had greater authority than their counterparts in unsuccessful projects (Rothwell, et al., 1974, pp. 285─6).

([ see the Wright brothers, for example, as a case study in innovation ])

p.202

Langrish, Gibbons, Evans and Jevons, Wealth from Knowledge (1972)

p.203

The authors concluded that “perhaps the highest-level generalization that it is safe to make about technological innovation is that it must involve synthesis of some kind of need with some kind of technical possibility” (Langrish et al., 1972, p. 57).

p.204

“Need identification” was the second most prevalent factor identified as important in the innovations examined.8

8 The six other factors, and the percentage of innovations examined in which they were found to be of importance are: “Top person: the presence of an outstanding person in a position of authority” (25.1 per cent); presence of some other indispensable person, who was of crucial importance due to his or her specialized knowledge (14.7 per cent); “Realization of the potential usefulness of a discovery” (6.2 per cent); “good cooperation” (4.9 per cent); “availability of resources” (8.2 per cent); and “Help from governmental sources, including resarch associations and public corporations” (5.3 per cent), (Langrish et al., 1972, p. 69).

p.204

For major innovations, the recognition of a discovery's usefulness was found to be far more important than was true in the total sample (occurring in 14.4 per cent of the case of major technological innovations, the third most prevalent), while “need identification” accounted for only 6.1 per cent (tied for 4th place). The relative importance of the two factors was reversed in the minor innovations, as the need factor occurred in 18.3 per cent, and discovery-push was of importance in only 5 per cent of the cases, a finding similar to that in the Battelle study's analysis of research events (see below).

p.222

Subsequently, an analysis of groups of innovations was carried out in an effort to focus upon the variables influencing the degree of commercial success. Five categories of variables were found to be most important in distinguishing successes from failures:

(1) successful innovators were seen to have a much better understanding of user needs.

(2) successful innovators paid more attention to marketing and publicity.

(3) successful innovators performed their development work more efficiently than failures but not necessarily more quickly.

(4) successful innovators made more use of outside technology and scientific advice, not necessarily in general but in the specific area concerned.

p.236

The need for a more positive public policy is well recognized both by numerous scholarly studies that have documented the discrepancy between high social returns and low (or even negative) private returns with respect to investment in knowledge production, and the diverse and elaborate systems of public support of knowledge-producing activities that have emerged in all advanced industrial societies. Attempting to deal with such problem has, for example, produced quite different organizational arrangements in America with respect to such diverse sectors as medicine, aircraft, atomic energy, and agriculture. There are, in addition, many forms of knowledge that are urgently required for successful social policy, that will not produced through any plausible system of private market incentives.

p.236

The point is that in certain areas, such as alternative energy or anti-pollution technologies, industry may simply lack sufficient R&D resources or the necessary market-generated incentives. In many industries and areas of substantial social need, we simply do not have the basic knowledge of scientific and technical phenomena to proceed intelligently; our limited understanding of such complex ecosystems as San Francisco bay, for example, or of the effects upon human health of long-term exposure to certain industrial wastes, greatly hampers the development of optimal antipollutant technologies and regulations. It is important to understand that the record of postwar American technical dynamism is a direct outgrowth of scientific and technical research in a very few areas (such as electronics), often funded and justified by defense requirements. This knowledge is clearly transferable in certain cases ─ semiconductors are an obvious example ─ to the civilian sector, but it is limited in its range of applicability. Integrated circuits will not immediately eradicate urban blight.

(Inside the black box./ Nathan Rosenberg, 1. technological innovations., 2. technology─social aspects., HC79.T4R673 1982, 338'.06, first published 1982, )

____________________________________

Mark Stefik and Barbara Stefik, Breakthrough, 2004 [ ]

p.61

Stuart Card

Having a method of collecting new kinds of data allowed Card to see something that had gone unnoticed before. Having a theory enabled him to understand what to look for in the data and also guided his thinking toward a solution.

p.65

These approaches are like colors on a palette in that they can be mixed to form variations and combinations.

1. Theory-driven invention. A tag line for this approach might be “Eureka!” or “According to my theory ...” This approach uses a theory, a model, or an analogy as a tool for thinking. These tools for thought provide advantages and shortcuts to insights leading to invention.

2. Data-drive invention. The tag line for this approach might be “That's strange!” An inventor notices an anomaly or something surprising in the data. Paying attention in this way creates an advantage, leading to insights and invention.

3. Method-driven invention. The tag line for this approach might be “Now I can see it!” Researchers have a new instrument that enables them to observe things not visible before.20 The new instrument give them advantages in observation, leading to insights and invention. ([ two examples given in the book is the telescope, and the microscope ])

4. Need-driven invention. The tag line for this approach is “Necessity is the mother of invention.” An inventor learns about an unresolved need or problem in the world and searches for a way to satisfy it or solve it. This approach fosters invention because the problem rests at the back of the mind as an unresolved challenge. It becomes a backdrop for interpreting experiences all day long. In effect, an inventor thinks about whatever ideas or observations show up as elements of possible solutions.

p.48

The data-driven approach notices patterns and anomalies in data.

p.49

Figure 3.1

Four ways of inspiring discovery and invention. In the theory-driven approach, a mental model or theory provides a way of thinking that leads to insight and invention. In the data-driven approach, an anomaly in data reveals a surprising possibility. In the method-driven approach, instrumentation enables previously unknown observation, discoveries, and invention. The need-driven approach identifies problems and seeks solutions.

p.50

Method-driven is about how information is gathered; data-driven is about how it is analyzed for pattern; theory-driven is about how it is understood and interpreted. In this way, these three methods correspond to three stages in gathering and processing information to create knowledge. The need-driven method relates to purpose──the sense that invention is not just about curiosity but also about making a difference in the world.

p.267

2. The four (4) approaches were suggested to us by Joshua Lederberg in a personal communication dated October 12, 2001. He carried out an analysis of his own research and that of close colleagues. All four (4) approaches were well represented, and most of the research was dominated by one approach. For need-driven invention, Lederberg cites his need to isolate auxotrophic mutants (bacteria requiring specific substances for growth and metabolism) as inspiring his invention of a penicillin method and also his invention of replica plating. For the data-driven approach, he notes that anomalous data led to the discovery of virus-mediated transduction (transfer of genetic material from one bacterial cell to another) and also the discovery of plasmids and lysogeny (the fusion of nucleic acid of a bacteriophage with that of a host bacterium). For the method-driven approach, he cites the design of instrumentation for exobiology (used in a Mars mission) and a use of replica plating to prove pre-adaptive occurrence of mutants. For theory-driven approach, he cites his own review of the natural history of bacteria, which persuaded him that sex (the exchange of genes) was a likely process. This led to his Nobel Prize. Lederberg notes that sex in bacteria also involved a need element and a method element. To understand the implications of the first intimation that genes are encoded in DNA (Avery et al. 1944) required better insight into whether bacteria had genes. Also, the method of nutritional selection was used to pick out rare genotypes from mixed populations. As our conversations with Lederberg pursued and refined the understanding of the four (4) approaches and related them to famous scientists and inventors, Lederberg exclaimed “How delightful to find this deep connection between Einstein, Edison, and others who have inspired me!”

to George Pake, the founder of PARC, who passed away on March 4, 2004.

(Stefik, Mark., Breakthrough : stories and strategies of radical innovation / Mark Stefik and Barbara Stefik., 1. technological innovation., 2. inventions., 2004, )

____________________________________

Mark Stefik and Barbara Stefik, Breakthrough, 2004 [ ]

pp.144-145

Mark Stefik

At that time I was a second-year graduate student in computer science. Preparing for my thesis, I was spending a lot of time in Joshua Lederberg's genetics laboratory in the medical school. Researchers in Josh's lab were always conducting experiments where they were digesting DNA, that is, cutting DNA into fragments using enzymes. Jerry Feitelson and I came up with the idea of writing a computer program to infer the DNA structure from the data.

Researchers in the lab were doing enzyme digests all of the time. Figuring out the segment structure was reasonably difficult, so people might spend hours doing it for each experiment. We thought that a good first project for me would be to automate the reasoning for these problems.

I started out by interviewing people in the lab about how they solved the problems. There was an underlying set of rules that governed how the DNA molecules were split apart by enzymes. My program was supposed to look at the digestion data and figure out how the segments were arranged in the original molecule. In any given experiment, a molecule might be digested by more than one enzyme. There were also experimental techniques called “partial digests” where the enzymatic processes were interrupted before they ran to completion. The partial digests gave intermediate-sized segments, which were clues about which pieces were next to each other.

At first things seemed to go quite easily. I interviewed people, wrote down their rules of reasoning, and programmed them in the computer. The program would re-assemble representations of the segments into representations of larger molecules. But as I explored more data, something began to bother me about the way the program worked. The more data the program had──the more clues it had about the segment structure──the longer it took. This seemed completely wrong to me. A puzzle should get easier when you have more clues. I set up an appointment to ask Lederberg for help.

I sweated for two weeks. I have tremendous admiration for Josh. In my mind he was high on a pedestal. I did not want to go and ask him a stupid question. Finally, on the afternoon of our meeting an hour before our appointment, I figure it out. I needed to reorganize the program so that it used the enzyme data as contraints or data for pruning rules rather than as clues for assembly. Having Josh tell me this WOULD have been embarrassing since he had pioneered the Dendral algorithms that used this approach for organic chemistry problems.

There was actually a saving grace to the interview. After staring at these problems for so long I came upon a new kind of experiment for elucidating DNA structure and was eager to tell Josh about it. I thought that it would make it easier to solve more complex structure problems than the ones being done in his laboratory. My idea was to do a partial digest with one enzyme, and then a complete digest in the other direction with another one. I was pretty proud of my idea.

When I met with Josh and told him my idea, the most amazing thing happened. He scratched his chin for and moment and said “That's interesting.” Then, as I remember it, he went to a whitebord and started listing the variables were could control: one, two, or three enzymes, complete digests versus partial digests, two and conceivably even three dimensional arrangements of the gels, and the order in which the digests were performed. He took my single variation on their experiments and in two or three minutes generated a whole family of additional experimental variations. I was dumfounded.

Josh showed me a NEW WAY TO THINK about problems. You could call what he did a kind of dimensional analysis. This left a lasting impression on me. Now when I get stuck I look for ways to generate variations. I will always remember that afternoon.

to George Pake, the founder of PARC, who passed away on March 4, 2004.

(Stefik, Mark., Breakthrough : stories and strategies of radical innovation / Mark Stefik and Barbara Stefik., 1. technological innovation., 2. inventions., 2004, )

____________________________________

* Graham Wallas, The Art of Thoughts, 1926

preparation <==> incubation <==> illumination <==> verification

preparation <==> incubation

/\ /\

|| ||

\/ \/

illumination <==> verification

xx=> (preparation) <=xx

|| ||

\/ \/

(verification) (incubation)

/\ /\

|| ||

XX=> (illumination) <=xx

- preparation

- incubation

- illumination

- verification

- illumination

- incubation

- preparation

Psychological Review

2010, Vol. 117, No. 3, 994-1024

Incubation, Insight, and Creative Problem Solving: A Unified Theory and Connectionist Model

Sébastien Hélie (and) Ron Sun

2010

page 995 (pdf 2/31)

Creative Problem Solving: Four Stages

The role of creativity in problem solving has been acknowledged since Wallas's (1926) seminal work. According to Wallas, humans go through four different stages when trying to solve a problem: preparation, incubation, illumination (i.e., insight), and verification. The first stage, preparation, refers to an initial period of search in many directions using (essentially) logic and reasoning. If a solution is found at this stage, the remaining stages are not needed. However, if the problem is ill defined and/or complex, the preparation stage is unlikely to generate a satisfactory solution. When an impasse is reached, the problem solver stops attempting to solve the problem, which marks the beginning of the incubation phase. Incubation can last from a few minutes to many years, during which the attention of the problem solver is not devoted to the problem. The incubation period has been empirically shown to increase the probability of eventually finding the correct solution (e.g., Dodds, Ward, & Smith, in press; S. M. Smith & Dodds, 1999). The following stage, illumination, is the spontaneous manifestation of the problem and its solution in conscious thought.1 The fourth stage, verification, is used to ascertain the correctness of insight solution. Verification is similar to preparation because it also involves the use of deliberative thinking processes (with logic and reasoning). If the verification stage invalidates the solution, the problem solver usually goes back to the first or second stage, and this process is repeated.

filename: helie-sun-psycrev2010-f.pdf

____________________________________

Edward de Bono, Lateral Thinking, 1970

p.5

It is emphasized that there is not antagonism between the two sorts of thinking. Both are necessary. Vertical thinking is immensely useful but one needs to enhance its usefulness by adding creativity and tempering its rigidity. Eventually this will done at school but until that time it may be necessary to do it at home.

This book is not intended to be read through at one sitting but worked through slowly over months or even years. For that reason many of the principles are repeated at intervals throughout the book in order to hold the subject together and prevent it fragmenting into mere techniques. In using the book, it is important to remember that practice is far more important than understanding the process.

p.6

The conflict method for changing ideas works well where the information can be evaluated in some objective manner. But the method does not work at all when the new information can only be evaluated through the old idea. Instead of being changed the old is strengthened and made ever more rigid.

p.6

The most effective way of changing ideas is not from outside by conflict but from within by the insight rearrangement of available information.

p.7

Insight, creativity and humour are so elusive because the mind is so efficien. The mind functions to create patterns out of its surroundings. Once the patterns are formed it becomes possible to recognize them, to react to them, to use them. As the patterns are used they become ever more firmly established.

p.7

Creativity also involves restructuring but with more emphasis on the escape from restricting patterns. Laternal thinking involves restructuring, escape and the provocation of new patterns.

p.7

In order to be able to use creativity one must rid it of this aura of mystique and regard it as a way of using the mind in a way of handling information. This is what lateral thinking is about.

p.7

New ideas are the stuff of change and progress in every field from science to art, from politics to personal happiness.

p.7

This leads to changes in attitude and approach; to looking in a different way at things which have always been looked at in the same way.

p.24

There comes a time when one cannot proceed further without restructuring the pattern without breaking up the old pattern which has been so useful and arranging the old information in a new way.

The trouble with a self-maximizing system that must make sense at each moment is that the sequence of arrival information determines the way it is to be arranged.

p.25

As with the plastic pieces there is often an alternative way of arranging available information. This means that there can be switch over to another arrangement. Usually this switch over is sudden. If the switch over is temporary is gives rise to humour. If the switch over is permanent it gives rise to insight. It is interesting that the reaction to an insight solution is often laughter even when there is nothing funny about the solution itself.

pp.25-26

In each of these situations an expectation is generated by the way the information is put together. Then suddenly this expectation is thwarted but at once one sees that the unexpected development is another way of putting things together.

Humour and insight are characteristic of this type of information handling system. Both processes are difficult to bring about deliberately.

p.28 (pdf 28/ 211)

Summary

The mind handles information in a characteristic way. This way is very effective and it has huge practical advantages. But it also has limitations. In particular the mind is good at establishing concept patterns but not at restructuring them to bring them up to date. It is from these inherent limitations that the need for lateral thinking arises.

p.30

The movement and change the lateral thinking is not an end in itself but a way of bringing about repatterning.

p.30

Vertical thinking is analytical, lateral thinking is provocative

One may consider three different attitude to the remark of a student who had come to the conclusion: “Ulysses was a hypocrite.”

1. “You are wrong, Ulysses was not a hypocrite.”

2. “How very interesting, tell me how you reached that conclusion.”

3. “very well. What happens next? How are you going to go forward from that idea?”

pp.35-36

It is always possible to describe a logical pathway in hindsight once a solution is spelled out. But being able to reach that solution by means of this hindsight pathway is another matter. One can demonstrate this quite simply by offering certain problems which are difficult to solve and yet when solved, the solution is obvious. In such cases, it is impossible to suppose that what make the problem difficult was lack of the elementary logic required.

It is characteristic of insight solutions and new ideas that they should be obvious after they have been found. In itself, this shows how insufficient logic is in practice, otherwise such simple solutions must have occurred much earlier.

p.38

A particular way of looking at things may have developed gradually.

p.38

A pattern may develop in a particular way because it was derived from the combination of two other patterns but had all the information been available at one time the pattern would have been quite different.

p.38

A pattern may persist because it is useful and adequate and yet a restructuring of the pattern could give rise to something very much better.

p.39

Had all four pieces been presented at once this final pattern is the one that would have resulted, but owing to the sequence of arrival of the pieces it was the other pattern that developed.

p.39

Lateral thinking is both on attitude and a method of using information

The lateral thinking attitude regards any particular way of looking at things as useful but not unique or absolute. That is to say one acknowledges the usefulness of a pattern but instead of regarding it as inevitable one regards it as only one way of putting things together. This attitude challenges the assumption that what is a convenient pattern at the moment is the only possible pattern. This attitude tempers the arrogance of rigidity and dogma.

p.39

The lateral thinking attitude involves firstly a refusal to accept rigid patterns and secondly an attempt to put things together in different ways. With lateral thinking one is always trying to generate alternatives, to restructure patterns. It is not a matter of declaring the current pattern wrong or inadequate.

p.39

Lateral thinking is never a judgement.

p.39

One may be quite satisfied with the current pattern and yet try to generate alternative patterns. As far as lateral thinking is concerned the only thing that can be wrong with a pattern is the arrogant rigidity with which it is held.

pp.41-42

Problem solving

A problem does not have to be presented in a formal manner nor is it a matter for pencil and paper working out. A problem is simply the difference between what one has and what one wants. It may be a matter of avoiding something, of getting something, of getting rid of something, of getting to know what one wants.

There are three-types of problem:

• The first type of problem requires for its solution more information or better techniques for handling information.

• The second type of problem requires no new information but a rearrangement of information already available: an insight restructuring.

• The third type of problem is the problem of no problem. One is blocked by the adequacy of the present arrangement from moving to a much better one. There is no point at which one can focus one's efforts to reach the better arrangement because one is not even aware that there is a better arrangement. The problem is to realize that ‘there is a problem’ to realize that ‘things can be improved’ and to define ‘this realization as a problem’.

The first type of problem can be solved by vertical thinking. The second and third type of problem require lateral thinking for their solution.

Penguin books

first published by Ward Lock education 1970

published in Pelican books 1977

published in Penguin books 1990

Edward de Bono, Lateral Thinking : a textbook of creativity, 1970

____________________________________

Allison Fallon., The power of writing it down : a simple habit to unlock your brain and reimagine your life, 2020

p.15

writers who have trusted me with their stories and their writing process

we were cultivating awareness.

We were starting to see things more clearly.

We were standing outside of our stories, outside of our circumstances, and seeing them from a new perspective.4

p.153

The great thing about this is that awareness is the beginning of change.

awareness is the beginning of change.

p.153

In fact, in therapeutic models of change, the step before the first step is called precontemplation. Precontemplation is the stage where in the person who needs to change hasn't even recognized the problem yet.

(The power of writing it down : a simple habit to unlock your brain and reimagine your life / Allison Fallon., summary: “for anyone feeling stuck and looking to make sense of life, author and writing coach Allison Fallow shares a simple practice and proven method to reclaiming your narrative, increasing your emotional and spiritual health, and discovering more clarity and freedom in ‘The Power of Writing it down’” ── provided by publisher., (print) (ebook) (hardcover)

(ebook), subject: writing ── psychological aspects. | behavior modification | written communication., BF456.W8 F35 2020 (print), BF456.W8 (ebook), 158.1/6──dc23, 2020, )

____________________________________

Daniel Goleman, Working with emotional intelligence, 1998

hardcover

658.409

Goleman

pp.327-328

Gauging Readiness

Extensive research (on more than 30,000 people) by James Prochaska, a University of Rhode Island psychologist, establishes four levels of readiness people go through during a successful behavior change.

■ Oblivious: As G. K. Chesterton, the British pundit, put it, “It isn't that thy can't see the solution ── they can't see the problem”. People at this stage aren't ready at all; they deny they have any need to change in the first place. They resist any attempt to help them change ── they just don't see the point.

■ Contemplation: People at this stage see that they need to improve and have begun to think about how to do so. They are open to talking about it but not quite ready to pursue development whole heartedly. Ambivalence is rampant; some wait for a “magic moment” of readiness, while others leap into action prematurely but meet failure because they are halfhearted. People at this stage are as likely to say they intend to take some action “next month” as they are to say they'll do it “in the next six months”. Prochaska notes that it's not unusual for people “to spend years telling themselves that someday they are going to change”. They substitute thinking for acting. Prochaska cites the case of an engineer who spent five years analyzing the factors that had made him passive and shy ── but didn't think he understood the problem well enough to do anything about it.

■ Preparation: Here people have begun to focus on the solution ── on how to improve. They are on the verge, eager to develop an action plan. They are aware of the problem, see that there are ways to solve it, and palpably anticipate doing so. People are sometimes propelled to this heightened stage of readiness by a dramatic event ── a heart-to-heart talk with a supervisor, a disaster on the job, a crisis in their personal life. One executive was jolted into bolstering his self-control competence when the police stopped him on the way home from a business dinner and arrested him for driving drunk. At this point people are ripe for change; this is the time for formulating a specific, detailed plan of action.

■ Action: Visible change begins. People embrace the plan, start practicing its steps, and actually change how they act ── their emotional patterns, the way they think about themselves, and all the other facets of transforming a long-standing habit. This stage is what most people think of as “making the change”, though it builds on the earlier steps in getting ready.

Daniel Goleman, Working with emotional intelligence, 1998

hardcover

658.409 Goleman

other books by Daniel Goleman

Emotional Intelligence;

Vital Lies, Simple Truth;

The Meditative Mind;

co-author, The Creative Spirit.

____________________________________

Clayton M. Christensen, Innovator's dilemma, 1997, 2000 [ ]

p.188

One of the dilemmas of management is that, by their very nature, processes are established so that employees perform recurrent tasks in a consistent way, time after time. To ensure consistency, they are meant NOT to change — or if they must change, to change through tightly controlled procedures. THIS MEANS THAT THE VERY MECHANISMS THROUGH WHICH ORGANIZATIONS CREATE VALUE ARE INTRINSICALLY INIMICAL TO CHANGE.

____________________________________

Adam Grant., Think again : the power of knowing what you don't know, 2021

p.1

Montana

Mann Gulch

August afternoon in 1949

Missouri River

Wagner Dodge

The flames stretch as high as 30 feet in the air.

p.2

Over the next eight minutes they traveled nearly 500 yards, leaving the top of the ridge less than 200 yards away.

p.2

With safety in sight but the fire swiftly advancing, Dodge did something that baffled his crew. Instead of trying to outrun the fire, he stopped and bent over. He took out a matchbook, started lighting matches, and threw them into the grass.

p.2

What the smokejumpers didn't realize was that Dodge had devised a survival strategy: he was building an escape fire. By burning the grass ahead of him, he cleared the area of fuel for the wildfire to feed on. He then poured water from his canteen onto his handkerchief, covered his mouth with it, and lay facedown in the charred area for the next fifteen minutes. As the wildfire raged directly above him, he survived in the oxygen close to the ground.

p.2

Tragically, twelve of the smokejumpers perished.

p.2

Why did only three of the smokejumpers survive? Physical fitness might have been a factor; the other two survivors managed to outrun the fire and reach the crest of the ridge.

p.3

We don't just hesitate to rethink our answers. We hesitate at the very idea of rethinking.

p.4

Questioning ourselves makes the world more unpredictable. It requires us to admit that the facts may have changed, and what was once right may now be wrong.

p.4

Reconsidering something we believe deeply can threaten our identities,

p.5

No one had taught Dodge to build an escape fire. He hadn't even heard of the concept; it was pure improvisation.

p.5

Many experts had spent their entire careers studying wildfires without realizing it was possible to stay alive by burning a hole through the blaze.

p.6

Just before Dodge started tossing matches into the grass, he ordered his crew to drop their heavy equipment.

p.6

running uphill on rocky ground with

Grant, Adam M., author.

Think again : the power of knowing what you don't know / Adam Grant.

Viking, 2021

includes bibliographical references and index.

subjects: thought and thinking | questioning. | knowledge, theory o. | belief and doubt.

LCC BF441.G693 2021 (print)

DDC 153.4/2--dc23

2021

Adam Grant., Think again : the power of knowing what you don't know, 2021

____________________________________

how we learn reading room

Tuesday, February 1, 2022

right distance

No comments:

Post a Comment

737 rudder issue

Search This Blog