Herbert A Simon Archives – The Rabbit Hole

Key Takeaways

How does one age, gradually replacing action by reflection?
In describing my life as mazelike, I do not mean that I have made a large number of deliberate, wrenching decisions to go off in one direction or another. On the contrary, I have made very few. Obvious responses to opportunities and circumstances, rather than studied decisions, have put me on the particular roads I have followed.
My aspirations do not extend to achieving a single consistency in my life. It will be enough if I can play each of my roles creditably, borrowing sometimes from one for another, but striving to represent fairly each character when he has his turn on the stage.
He did know the difference between memorizing and understanding, and did not give up on a topic until he understood it clearly.
Here he learned another important practical truth: You do not change people’s opinions by defeating them with logic. People do not feel obliged to agree just because they cannot reply at the moment.
In essence our failure was a vivid demonstration, which I have never forgotten, that theories, however plausible and “obviously” valid, can be destroyed totally by the obstinate facts of the real world.
Everything had to be explored, tested, before it could be accepted or rejected.
During my first two years as an undergraduate, and a little less austerely during the third year, I lived as an intellectual. From 6:00 in the morning, when I rose, until 10:00 at night, when I went to bed, seven days a week, I was immersed in books and talk of books. That included mealtimes and most of my socializing hours. The survey courses provided a conversational common denominator, so that there was always shoptalk at the refectory table.*2
Organizational Golden Ages, whether in government, universities, or business firms, seldom endure beyond the generation of people who create them.
It helped me understand that new ideas do not fly solely on their own wings; the scientist is a communicator as well as a discoverer—sometimes even a missionary.
My career was determined for me in a very casual way. The branching points in the maze of my life offered easy choices. Other people in my environment presented me with opportunities. When the opportunities were attractive, I took them. Two or three such choices (hardly decisions, for I did not search for alternatives) set me on a definite path.
Again it was obvious which branch of the maze I should follow.
The important lesson I learned from this analysis was that my conclusions depended at least as much on certain assumptions about boundary conditions as on the central assumptions of economic rationality that lie at the core of neoclassical theory. By boundary conditions I mean the assumptions that have to be made about which indirect effects of a change in taxes the human actors would take into account in making their decisions and which they would ignore.
Interdisciplinary adventure is easiest in new fields.
Rationality, then, does not determine behavior. Within the area of rationality behavior is perfectly flexible and adaptable to abilities, goals, and knowledge. Instead, behavior is determined by the irrational and nonrational elements that bound the area of rationality. The area of rationality is the area of adaptability to these nonrational elements. Two persons, given the same possible alternatives, the same values, the same knowlege, can rationally reach only the same decision. Hence, administrative theory must be concerned with the limits of rationality, and the manner in which organization affects these limits for the person making a decision.
It was built around two interrelated ideas that have been at the core of my whole intellectual activity: (1) human beings are able to achieve only a very bounded rationality, and (2) as one consequence of their cognitive limitations, they are prone to identify with subgoals.
I learned that there is no use lecturing to a class unless the class is listening. And they will only listen if you are saying something that they think they can understand and that seems relevant. They will listen better if you talk LOUDLY. If you pace up and down, you can tell from their moving heads whether they are following you (like the crowd at a tennis match). You can also get feedback by keeping your eye on the prettiest girl in the class to see whether she is attentive.
Teaching is not entertainment, but it is unlikely to be successful unless it is entertaining (the more respectable word would be interesting).
You start every class by giving students the opportunity (or better, the obligation) to ask questions about their reading, about previous sessions, or about anything. You take each question seriously, and answer it without making a jackass of the student who asked it (no matter how foolish the question).
Ever since, I think I have included that among my own selection criteria; intelligence shines through the eyes.
For me, mathematics has always been a language of thought. I don’t know precisely what I mean by that (and explicating the meaning is today one of my important research goals), but I can try to explain. When I am working on a problem, I am sure that I do not usually think in words, but in terms of a more abstract representation that is perhaps partially pictorial or diagrammatic and partially symbolic. Mathematics—this sort of non-verbal thinking—is my language of discovery. It is the tool I use to arrive at new ideas. This kind of mathematics is relatively unrigorous, loose, heuristic. Solutions reached with its help have to be checked for correctness. It is physicists’ mathematics or engineers’ mathematics rather than mathematicians’ mathematics.
I could never persuade Tjalling that ideas have to be arrived at before their correctness can be guaranteed, and that the logic of discovery is quite different from the logic of verification.
How do these criteria apply to the life of science? I advise my graduate students to pick a research problem that is important (so that it will matter if it is solved), but one for which they have a secret weapon that gives some prospect of success. Why a secret weapon? Because if the problem is important, other researchers as intelligent as my students will be trying to solve it; my students are likely to come in first only by having access to some knowledge or research methods the others do not have.
I have probably never quite gotten over the “Look, Ma, no hands” syndrome. Success is especially pleasant when it is effortless—but it seldom is. To save appearances, one simply redefines work as fun (which, unaccountably, it usually becomes).
For most of us—those of us who have not won million-dollar lotteries, or suffered sudden crippling accidents—life is much like the chess game. We make hundreds of choices among the alternative paths that lie before us and, as the result of those choices, find ourselves pursuing particular, perhaps highly specialized, careers, married to particular spouses, and living in particular towns. Even if we point to a single event as the “cause” of one of these outcomes, closer scrutiny of the path we have trod would reveal prefatory or preparatory events and choices that made the occurrence of the critical event possible.
My nose was clearly sensitive to where the action was,
At school and church, I was a nonconformist in certain minor ways, and learned to bear the embarrassment that nonconformity brings with it.
Arthur Koestler’s Darkness at Noon (1941).
At first I did not recognize that when you are in a position of authority you cannot debate freely with people in your organization without some of them believing that they may endanger their careers if they disagree with you too vigorously. Perhaps they are right—I like to think not in my case, but self-deception is easy. People who agree with you are apt to seem a little more intelligent than those who don’t. Power does corrupt.
Lee Bach persuaded us, by example, to set the goals of GSIA sky-high, stretching the limits of the possible. And as aspirations were attained, goals moved higher. Second, Lee always found a way to reconcile technique (we were loaded with that) with common sense (sometimes in short supply). Third, Lee was always more interested in getting the job done, and done well, than in placing blame when something went awry along the way. High aspirations, common sense, and responsibility for getting results. It seems simple enough.
I warned you that I would say little about Lee that would tell you how to be a good manager, and I have made good my warning. The principles of good management are simple, even trivial. They are not widely practiced for the same reason that Christianity is not widely practiced. It is not enough to know what the principles are; you must acquire deeply ingrained habits of carrying them out, in the face of all sorts of strong urges to stray onto more comfortable and pleasant paths, to respond without inhibition to provocations, and just to goof off. Lee had the self-discipline actually to apply the principles, to behave like a good manager and leader. Not many of us do.
From observing Elliott Smith I learned that being a decent person is terribly important, but being a “nice guy” is not important at all.
To avoid constraining our ability to innovate, we did not seek national accreditation until our reputation was so well established that the accrediting body could not put pressure on us to conform to conventional ideas.
Bracketing satisficing with Darwinian may appear contradictory, for evolutionists sometimes talk about survival of the fittest. But in fact, natural selection only predicts that survivors will be fit enough, that is, fitter than their losing competitors; it postulates satisficing, not optimizing.
Soon I was transformed professionally into a cognitive psychologist and computer scientist, almost abandoning my earlier professional identity. This sudden and permanent change came about because Al Newell, Cliff Shaw, and I caught a glimpse of a revolutionary use for the electronic computers that were just then making their first public appearance. We seized the opportunity we saw to use the computer as a general processor for symbols (hence for thoughts) rather than just a speedy engine for arithmetic. By the end of 1955 we had invented list-processing languages for programming computers and had used them to create the Logic Theorist, the first computer program that solved non-numerical problems by selective search. It is for these two achievements that we are commonly adjudged to be the parents of artificial intelligence. Put less technically, if more boastfully, we invented a computer program capable of thinking non-numerically, and thereby solved the venerable mind/body problem, explaining how a system composed of matter can have the properties of mind. With that, we opened the way to automating a wide range of tasks that had previously required human intelligence, and we provided a new method, computer simulation, for studying thought.
Work that too far anticipates its appropriate zeitgeist tends to be ignored, while work that fits the contemporary zeitgeist is recognized promptly.
he had an unerring instinct for important (and difficult) problems.
There has been no definable boundary between the sociability of work and of leisure.
In retrospect it seems easy, but the road was not without buried mines that had to be detected and removed.
My training as an economist has been of help in one important way: It convinced me that the only information that is of value in a financial market is information that other people don’t have. This means that I don’t have to pay daily, or even monthly, attention to the stock market, since it tells me nothing about whether I should buy or sell. Hence, the turnover on my investments is very low, to the discouragement of the brokers with whom I do business (and from whom, also, I never take tips or advice). Nothing that I learned while serving on the Finance Committee of the Carnegie Mellon Board of Trustees has shown me that this strategy is wrong. It satisfices; perhaps it even optimizes.
Time is the tyrant. One cannot be loyal to two occupations any more than one can to two lovers. Whenever I found that one of my hobbies was seriously taking attention from my research, I dropped it. That happened to chess, and then painting, in the late 1950s. In both cases, I found that I was aspiring to professional competence, which obviously would have required an unlimited commitment. It was time to call a halt.
had only one reservation: He seemed to enjoy power too much, a worrisome trait in a leader. (Leaders should exercise power, but enjoying it is another, and more dangerous, matter.)
Innovating means not simply generating ideas but disseminating them.
The distinction between the scientific and the professional is largely a distinction between analysis and synthesis. Professionals not only analyze (understand) situations, they act on them after finding appropriate strategies (synthesis). In business, they design products and marketing channels, organize manufacturing processes, and find new financial instruments; in engineering, they design structures and devices and processes; in medicine, they design and prescribe treatments and perform operations. But analysis had driven synthesis from all these curricula.
As long as I looked at the whole of Carnegie first, and its parts second, I could be useful. I think I have usually been able to do this, but I would be surprised if there have not been some lapses.
We could have no comparative advantage in the liberal subjects in competition with the Ivy League schools unless we offered something different and arguably better than they did. If we had no comparative advantage, we would not achieve quality; and if we did not achieve quality, we should not be in the business.
It would seem to me that every scientist would have to think so, for the whole purpose of science is to find meaningful simplicity in the midst of disorderly complexity.
Seeds of desire, once planted, do grow, even in rather stony soil.
The research strategy was the one we have followed through the whole history of A.I. and cognitive science: As we gain an understanding of simpler processes and task domains, we tackle more complex ones. So, in the past ten years, I have moved on to learning processes; to problem representation, including imagery; and to the processes of scientific discovery.
A still heavier obligation, not always acknowledged, is to leave to future generations as wide and interesting a range of options as our generation inherited from our forebears.
If the quality of a research problem rests on the importance of the questions it addresses and the availability of ideas and techniques that hold out a promise of progress, then the study of mind is a most promising research domain.
Having spent much of my scientific life in such travel, I can offer one piece of advice to others who wish to try an itinerant existence: It is fatal to be regarded as a good economist by psychologists, and a good psychologist by political scientists. Immediately upon landing on alien shores, you must begin to acquire the local culture, not to deny your origins but to gain the full respect of the natives. When in economics, there is no substitute for talking the language of marginal analysis and regressions—even (or especially) when your purpose is to demonstrate their limitations. When in psychology, you must be able to understand references to short-term memory and latencies and spreading activation.
If there are goals, they do not so much guide the search as emerge from it. It needs no summing up beyond the living of it.
Now let’s return from gold seeking to problem seeking. Our metaphor suggests that one way to find a problem, and perhaps even its solution, is to try to solve some other problem.
One heuristic that has been of first importance to my work is missing, however, from the programs I have described in this chapter: To make interesting scientific discoveries, you should acquire as many good friends as possible, who are as energetic, intelligent, and knowledgeable as they can be. Form partnerships with them whenever you can. Then sit back and relax. You will find that all the programs you need are stored in your friends, and will execute productively and creatively as long as you don’t interfere too much. The work I have done with my more than eighty collaborators will testify to the power of that heuristic.

What I got out of it

This book is a great example of how we can take multidisciplinary learning and integrate it into our lives in a functional and meaningful way. He followed his curiosity and it led him to some amazing places and to a life well lived.