“We will learn that computers, amazing as they are, still cannot come close to being as effective as human beings. A computer isn't creative on its own because it is programmed to behave in a predictable way. Creativity comes from looking for the unexpected and stepping outside your own experience. Computers simply cannot do that.”

—  Masaru Ibuka

Masaru Ibuka in: The Corporate Board, (1992), Vol. 13, p. 30

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Masaru Ibuka 8
Japanese businessman 1908–1997

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“Creativity comes from looking for the unexpected and stepping outside your own experience. Computers simply cannot do that.”

Masaru Ibuka (1908–1997) Japanese businessman

Masaru Ibuka in: The Corporate Board, (1992), Vol. 13, p. 30

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“The objective of the Computer-Aided Design Project is to evolve a machine systems which will permit the human designer and the computer to work together on creative design problems.”

Douglas T. Ross (1929–2007) American computer scientist

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“Present-day computers are designed primarily to solve preformulated problems or to process data according to predetermined procedures. The course of the computation may be conditional upon results obtained during the computation, but all the alternatives must be foreseen in advance. … The requirement for preformulation or predetermination is sometimes no great disadvantage. It is often said that programming for a computing machine forces one to think clearly, that it disciplines the thought process. If the user can think his problem through in advance, symbiotic association with a computing machine is not necessary.
However, many problems that can be thought through in advance are very difficult to think through in advance. They would be easier to solve, and they could be solved faster, through an intuitively guided trial-and-error procedure in which the computer cooperated, turning up flaws in the reasoning or revealing unexpected turns in the solution. Other problems simply cannot be formulated without computing-machine aid. … One of the main aims of man-computer symbiosis is to bring the computing machine effectively into the formulative parts of technical problems.
The other main aim is closely related. It is to bring computing machines effectively into processes of thinking that must go on in "real time," time that moves too fast to permit using computers in conventional ways. Imagine trying, for example, to direct a battle with the aid of a computer on such a schedule as this. You formulate your problem today. Tomorrow you spend with a programmer. Next week the computer devotes 5 minutes to assembling your program and 47 seconds to calculating the answer to your problem. You get a sheet of paper 20 feet long, full of numbers that, instead of providing a final solution, only suggest a tactic that should be explored by simulation. Obviously, the battle would be over before the second step in its planning was begun. To think in interaction with a computer in the same way that you think with a colleague whose competence supplements your own will require much tighter coupling between man and machine than is suggested by the example and than is possible today.”

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“And programming computers was so fascinating. You create your own little universe, and then it does what you tell it to do.”

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“If you think about things that happen, as being computations... a computation in the sense that it has definite rules... You follow them many steps and you get some result. ...If you look at all these different computations that can happen, whether... in the natural world... in our brains... in our mathematics, whatever else, the big question is how do these computations compare. ...Are there dumb ...and smart computations, or are they somehow all equivalent? ...[T]he thing that I ...was ...surprised to realize from ...experiments ...in the early 90s, and now we have tons more evidence for ...[is] this ...principle of computational equivalence, which basically says that when one of these computations ...doesn't seem like it's doing something obviously simple, then it has reached this ...equivalent layer of computational sophistication of everything. So what does that mean? ...You might say that ...I'm studying this tiny little program ...and my brain is surely much smarter ...I'm going to be able to systematically outrun [it] because I have a more sophisticated computation ...but ...the principle ...says ...that doesn't work. Our brains are doing computations that are exactly equivalent to the kinds of computations that are being done in all these other sorts of systems. ...It means that we can't systematically outrun these systems. These systems are computationally irreducible in the sense that there's no ...shortcut ...that jumps to the answer.”

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