“Now the salient characteristic of the decision tools employed in management science is that they have to be capable of actually making or recommending decisions, taking as their inputs the kinds of empirical data that are available in the real world, and performing only such computations as can reasonably be performed by existing desk calculators or, a little later electronic computers. For these domains, idealized models of optimizing entrepreneurs, equipped with complete certainty about the world - or, a worst, having full probability distributions for uncertain events - are of little use. Models have to be fashioned with an eye to practical computability, no matter how severe the approximations and simplifications that are thereby imposed on them…
The first is to retain optimization, but to simplify sufficiently so that the optimum (in the simplified world!) is computable. The second is to construct satisficing models that provide good enough decisions with reasonable costs of computation. By giving up optimization, a richer set of properties of the real world can be retained in the models… Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science.”

— Herbert A. Simon

Source: 1960s-1970s, "Rational decision making in business organizations", Nobel Memorial Lecture 1978, p. 498; As cited in: Arjang A. Assad, ‎Saul I. Gass (2011) Profiles in Operations Research: Pioneers and Innovators. p. 260-1.

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Herbert A. Simon58

American political scientist, economist, sociologist, and p… 1916–2001

Milton Babbitt (1916–2011) American composer

Quoted in Classic Essays on Twentieth-Century Music, ISBN 0028645812.

“If we accept values as given and consistent, if we postulate an objective description of the world as it really is, and if we assume that the decision maker's computational powers are unlimited, then two important consequences follow. First, we do not need to distinguish between the real world and the decision maker's perception of it: he or she perceives the world as it really is. Second, we can predict the choices that will be made by a rational decision maker entirely from our knowledge of the real world and without a knowledge of the decision maker's perceptions or modes of calculation. (We do, of course, have to know his or her utility function.)
If, on the other hand, we accept the proposition that both the knowledge and the computational power of the decision maker are severely limited, then we must distinguish between the real world and the actor's perception of it and reasoning about it. That is to say, we must construct a theory (and test it empirically) of the processes of decision. Our theory must include not only the reasoning processes but also the processes that generate the actor's subjective representation of the decision problem, his or her frame.”

Herbert A. Simon (1916–2001) American political scientist, economist, sociologist, and psychologist

H.A. Simon (1986), " Rationality in psychology and economics http://www.kgt.bme.hu/targyak/msc/ng/BMEGT30MN40/data/JoBus-86-rationality-HSimon.pdf," Journal of Business, p. 210-11” <br class="br">1980s and later

“The Competent Manager: A Model for Effective Performance offers an empirical, total system approach that determines which characteristics of managers enable them to be effective in various management jobs.”

Richard Boyatzis (1946) American business theorist

Introduction text.
Competent manager (1982)

“To an outsider, the most significant innovation in the global warming controversy is the overt reliance that is being placed on models. Back in the days of nuclear winter, computer models were invoked to add weight to a conclusion: “These results are derived with the help of a computer model.” But now, large-scale computer models are seen as generating data in themselves. No longer are models judged by how well they reproduce data from the real world—increasingly, models provide the data. As if they were themselves a reality. And indeed they are, when we are projecting forward.”

Michael Crichton (1942–2008) American author, screenwriter, film producer

Aliens Cause Global Warming (2003)

“As a result, the topic became – primarily in the USA – prematurely known as ‘computer science’ – which, actually, is like referring to surgery as ‘knife science’ – and it was firmly implanted in people’s minds that computing science is about machines and their peripheral equipment. Quod non”

Edsger W. Dijkstra (1930–2002) Dutch computer scientist

Dijkstra (1986) On a cultural gap http://www.cs.utexas.edu/users/EWD/transcriptions/EWD09xx/EWD924.html (EWD 924). <br class="br">1980s <br class="br">Context: A confusion of even longer standing came from the fact that the unprepared included the electronic engineers that were supposed to design, build and maintain the machines. The job was actually beyond the electronic technology of the day, and, as a result, the question of how to get and keep the physical equipment more or less in working condition became in the early days the all-overriding concern. As a result, the topic became – primarily in the USA – prematurely known as ‘computer science’ – which, actually, is like referring to surgery as ‘knife science’ – and it was firmly implanted in people’s minds that computing science is about machines and their peripheral equipment. Quod non [Latin: "Which is not true"]. We now know that electronic technology has no more to contribute to computing than the physical equipment. We now know that programmable computer is no more and no less than an extremely handy device for realizing any conceivable mechanism without changing a single wire, and that the core challenge for computing science is hence a conceptual one, viz., what (abstract) mechanisms we can conceive without getting lost in the complexities of our own making.

“Without real experience in using the computer to get useful results the computer science major is apt to know all about the marvelous tool except how to use it. Such a person is a mere technician, skilled in manipulating the tool but with little sense of how and when to use it for its basic purposes.”

Richard Hamming (1915–1998) American mathematician and information theorist

One Man's View of Computer Science (1969)

“The accounting methods based on mathematical models, the use of computers for computations and information data processing make up only one part of the control mechanism, another part is the control structure.”

Leonid Kantorovich (1912–1986) Russian mathematician

"Mathematics in Economics: Achievements, Difficulties, Perspectives," 1975

“[Computer science] is not really about computers -- and it's not about computers in the same sense that physics is not really about particle accelerators, and biology is not about microscopes and Petri dishes…and geometry isn't really about using surveying instruments. Now the reason that we think computer science is about computers is pretty much the same reason that the Egyptians thought geometry was about surveying instruments: when some field is just getting started and you don't really understand it very well, it's very easy to confuse the essence of what you're doing with the tools that you use.”

Hal Abelson (1947) computer scientist

Source: Introductory lecture to Structure and Interpretation of Computer Programs http://www.youtube.com/watch?v=zQLUPjefuWA

“The formal structure of a decision problem in any area can be put into four parts: ( 1 ) the choice of an objective function denning the relative desirability of different outcomes; (2) specification of the policy alternatives which are available to the agent, or decisionmaker, (3) specification of the model, that is, empirical relations that link the objective function, or the variables that enter into it, with the policy alternatives and possibly other variables; and (4) computational methods for choosing among the policy alternatives that one which performs best as measured by the objective function.”

Kenneth Arrow (1921–2017) American economist

Source: 1970s-1980s, The Economics of Information (1984), p. 55

“Machines as simple as thermostats can be said to have beliefs, and having beliefs seems to be a characteristic of most machines capable of problem solving performance. However, the machines mankind has so far found it useful to construct rarely have beliefs about beliefs, although such beliefs will be needed by computer programs that reason about what knowledge they lack and where to get it. Mental qualities peculiar to human-like motivational structures, such as love and hate, will not be required for intelligent behavior, but we could probably program computers to exhibit them if we wanted to, because our common sense notions about them translate readily into certain program and data structures. Still other mental qualities, e. g. humor and appreciation of beauty, seem much harder to model.”

John McCarthy (1927–2011) American computer scientist and cognitive scientist

" Ascribing Mental Qualities to Machines http://www-formal.stanford.edu/jmc/ascribing.html" (1979) Sect. 1: Introduction. Reprinted in Formalizing Common Sense: Papers By John McCarthy, 1990, ISBN 0893915351 <br class="br">1970s

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