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Why greatness cannot be planned : the myth of the objective
Stanley K., Lehman J., Springer Publishing Company, Incorporated, New York, NY, 2015. 141 pp. Type: Book (978-3-319155-23-4)
Date Reviewed: Jan 15 2016

The authors argue for serendipitous discoveries based on novelty and uniqueness. This happens when the structure of the search space is completely unpredictable (pp. 8, 97) (and not fixed [1]), that is, when the eventual objective is ambitious, rather than “sufficiently modest” (p. 7), and is more than one stepping stone away, so that such an objective can distract you from its own stepping stones.

The authors properly note that in search and discovery, “it’s difficult to see farther than one stepping stone away, no matter our intelligence” (p. 29). In other words, the authors are concerned with complex systems [2] for which reductionism does not work. The authors include excellent and rather detailed examples of such systems including education (chapter 7), innovation and grants for scientific research (chapter 8), and scientific publications, especially but not only in artificial intelligence (chapter 11), and show that objective-based approaches for these systems lead to failures. In many cases, such approaches are associated with assessments used by the “gatekeepers” leading to “a quick convergence to a mediocre dead end” (p. 72). In probably all cases, novelty and “interestingness” are discouraged.

The authors observe that “we don’t know which stepping stones might lead to something interesting” (p. 17), but only much later, on page 98, refer to the perhaps most famous example: the Macintosh computer. To quote Steve Jobs,

Because I had dropped out and didn’t have to take the normal classes, I decided to take a calligraphy class [...]. I learned about […] what makes great typography great. It was beautiful, historical, artistically subtle in a way that science can’t capture, and I found it fascinating. None of this had even a hope of any practical application in my life. But 10 years later, when we were designing the first Macintosh computer, it all came back to me. And we designed it all into the Mac. It was the first computer with beautiful typography. If I had never dropped in on that single course in college, the Mac would have never had multiple typefaces or proportionally spaced fonts. [...] Of course it was impossible to connect the dots looking forward when I was in college. But it was very, very clear looking backward 10 years later. [3]

This perfectly illustrates the authors’ position that a great invention is defined by “the realization that the prerequisites are in place ... just waiting to be combined and enhanced” (p. 37). In other words, this is a creative composition [4] of perhaps commoditized “stepping stones.”

Time and again, we read that “the more complicated the problem is, the less likely it is that the myth of the objective will hold true” (p. 70). One cannot but agree, although regretfully the authors do not refer to Hayek [2], do not mention the examples of failed planned economies, and do not say that sometimes the problem itself is not known. The authors do mention that some “useless” results from pure mathematics led to interesting and very useful applications in chemistry, physics, and computer science including public key cryptography (and secure online commerce), and elsewhere (pp. 85-86). I would add category theory here: an “abstract nonsense” that appeared to be very useful as a foundation for understanding complex systems [5].

More generally, Yuri Manin, one of the great mathematicians of the 20th (and 21st) century, sees the process of mathematical creation “as a kind of recognizing a preexisting pattern,” in contrast to “the sportive view,” which emphasizes only problem solving and “is not the way to see mathematics.” In Manin’s opinion, after acquiring a general vision of the vast territory and focusing on a part of it, a mathematician tries to recognize “what is there” and “what has already been seen by other people” and finally starts “discerning something nobody has seen” [6]. This activity reminds me of the authors’ observation that “science needs to be a treasure hunter and a stepping stone collector” (p. 83); to quote F. A. Hayek [2], “the systematic construction of new patterns is the business of mathematics.”

I found useful the authors’ (re)interpretation of natural evolution (chapter 10) as a minimal criteria search in which competition, which is only local and never global, is the least interesting of the evolutionary forces since it tends to diminish diversity. The minimal criteria (constraints) are those of survival and reproduction. Novelty search with local competition has been programmed by the authors. They also properly note that natural evolution is a large-scale open-ended creative system notably lacking (human) guidance or design, in excellent agreement with Hayek [2].

Summing up, I would certainly recommend this well-written book, despite it being somewhat repetitive. The penultimate sentence of the book sums it up well: “Anyone can say that performance should improve, but who has the courage to see the beauty of an idea?”

More reviews about this item: Amazon, Goodreads

Reviewer:  H. I. Kilov Review #: CR144103 (1604-0226)
1) von Mises, L. Human action: a treatise on economics. Yale University Press, New Haven, CT, 1949.
2) Hayek, F. A. The theory of complex phenomena. In: The critical approach to science and philosophy (In honor of Karl R. Popper). Free Press of Glencoe, New York, NY, 1964, 332–349.
3) Jobs, S. Stanford University Commencement Address, June 12, 2005. http://news.stanford.edu/news/2005/june15/jobs-061505.html. Accessed 01/09/2016.
4) Kilov, H. Finding work: an IT expert as an entrepreneur. In Proc. of the OOPSLA 2002 Workshop on Behavioral Semantics (Serving the Customer) Kilov, H., Baclawski, K., Eds. Northeastern University, Boston, MA, 2002, 108–120.
5) Ehresmann, A.; Vanbremeersch, J. P. Memory evolutive systems: hierarchy, emergence, cognition. Elsevier, Amsterdam, Netherlands, 2007.
6) Manin, Y. Good proofs are proofs that make us wiser. The Berlin Intelligencer, http://www.ega-math.narod.ru/Math/Manin.htm (01/09/2016).
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