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Monday, March 16, 2015
Sunday, July 13, 2014
Tuesday, March 12, 2013
Thursday, February 21, 2013
Agile Scrum: James Grenning - The Father of Planning Poker
Sunday, January 20, 2013
Complexity Theory for Design & Process
- Defining and Measuring Complexity
- Modeling Complexity
- Managing Complexity
- Reducing Complexity
- Application (Examples of applying to different disciplines)
Of the five components, we spent a considerable amount of time up front on defining and measuring complexity - due to lack of a generally excepted definition for the term "complexity". Of course, this inability to settle on a consensus around the term, reminded me of the literature review of The Structure of Scientific Revolution, by Thomas Kuhn.
In my blog on Structure, as the book is affectionately called by Kuhn, I postulated about how the notion of scientific development can be reduced to three distinct phases: pre-paradigm, normal science, and revolutionary science. In this instance, complexity and the science around it, fits Kuhn's model of the pre-paradigm phase. In other words, complexity is marked by deep debates over legitimate methods, problems, and standard of solutions. At any rate, since we didn't settle on a specific definition for the term, we used a set of characteristics to describe whether or not something was complex. What follows are a few of the characteristics we settled on to describe complexity:
- Interactions: A large number of components with different relationships; Systems consisting of large networks of individual components, each typically following simple rules with no central control or leader; collective action of vast numbers of components that give rise to the complex, hard-to-predict and changing patterns of behavior
- Emergence: A New Kind of Science - Stephen Wolfram; Randomness = Complexity; The notion of "computational equivalence" and "computational irreducibility"; There is a pretty cool youtube video on Wolfram's notion of complexity. http://www.youtube.com/watch?v=_eC14GonZnU. It is pretty long, but exciting to watch.
- Adaptation: Systems that tend to change over time (maybe because of some stimulus) - also described as "Complex adaptive systems"; "Self Organizing"; and "Resilience"; Systems adapt—that is, change their behavior to improve their chances of survival or success—through learning or evolutionary processes
- Signaling and Information Processing: Systems produce and use information and signals from both internal and external environments
In the meantime, how would YOU describe complexity? Drop me a comment and let me know what you think.
A few good references on complexity:
- "Complexity: Theory and Applications," Nam P. Suh
- "Complexity: A Guided Tour," Melanie Mitchell
- "Measures of Complexity: A Nonexhaustive List," Seth Llyod
Sunday, December 30, 2012
Thomas S. Kuhn: The Structure of Scientific Revolutions
First and foremost, let me give a very special thanks to Dr. Ertas and Dr. Tate for a magnificent first semester in the PhD Program at Texas Tech University. In a very short period of time, they have managed to reignite my burning desire for Science Technology Engineering and Mathematics (STEM). Specifically, they lit a fire with this excellent book entitled, "The Structure of Scientific Revolutions," by Thomas S. Kuhn.
Thomas Samuel Kuhn obtained his B.S. degree in physics from Harvard University in 1943, where he also obtained M.S. and Ph.D. degrees in physics in 1946 and 1949, respectively. However, after three years of what he would denote as "total academic freedom" as a Harvard Junior Fellow, he would switch from physics to the history (and philosophy) of science. The dramatic change would come as a result of an experimental college course that would challenge some of his basic conceptions about the nature of science. Kuhn would eventually deduce that whatever he had previously learned through different didactic mediums, scientific training, and just plain ol' self interest did not line up with the enterprise notion of historical studies. It would be this disconnect that would be the catalyst for Kuhn's change and ultimately the genesis of "The Structure of Scientific Revolutions."
"Structure," as it is affectionately called by Kuhn, is arguably one of the most cited books on the Philosophy of Science and has been reviewed many times. Accordingly, I'd like to take this opportunity to deposit a few observations of my own. My first observation was that the literary content of the book was difficult to read. This was, in part, due to the esoteric nature of the subject, the complex vocabulary, and the requisite knowledge in astronomy and physics. In fact, this book challenged me to revisit the works of Galileo, Copernicus, Newton, and Einstein before I could fully appreciate the historical, scientific, and philosophical nature of this work. At any rate, after revisiting their contributions, I was able to fully appreciate Structure and gain a deeper insight into Kuhn's position on the Philosophy of Science.
Secondly, it became really obvious early on in the book that Kuhn's contribution to the Philosophy of Science did not necessarily come as a by-product of his background as a Physicist, but was heavily influenced by his exploration as a Historian. I found this both fascinating and intriguing: Fascinating in the sense that, on the surface, Kuhn's pursuit in a "hard" science - like physics - did not yield the same level of passion or insight into the philosophy of science that the History of Science did; Intriguing in the sense that collaborating across discipline boundaries, in this instance History, Physics and some argue Sociology, seems to aid in the process of gaining a deeper understanding of the subject matter. Moreover, this school of thought - a model that transcends traditional disciplinary boundaries to address large problems - is in direct line with my PhD work in Transdiciplinary Design Process and Systems. It is this "Transdiciplinary" lens that will enable me to take a more holistic view of a problem space.
Finally, to the matter at hand, "The Structure of Scientific Revolution," by Thomas S. Kuhn. Without giving too much of the book away, Kuhn does a really good job of building the case against the school of thought that tout science as an accumulation of individual discoveries and inventions. Afterward, he lays the groundwork for what we know today as a revolutionary process where brand new ideas reach a consensus and are adopted while old ideas reach a tipping point and become discarded.
In the book, the notion of scientific development can be reduced to three distinct phases: pre-paradigm, normal science, and revolutionary science. The pre-paradigm phase, as Kuhn puts it, "is regularly marked by frequent and deep debates over legitimate methods, problems, and standard of solutions." For the most part, this is not an exercise in conciliation, rather, an exercise to define a school of thought that is likely to lay the foundation for normal science.
Once normal science begins, "puzzles" are presented and solved iteratively within the context of the dominant paradigm. It is important to note, Kuhn's intentional use of the word puzzle here. It has been recorded that many scientist were taken aback by this word usage, which may explain why Kuhn spent an entire chapter to defending it. At any rate, as long as there is "plenty to do" (i.e. legitimate puzzles to solve) and the existing paradigm do not reveal anomalies — facts that can not be reconciled within framework of the existing paradigm — normal science continues . In the event that anomalies are revealed and accumulated to the point where the paradigm breaks down, this phenomenon is considered a crisis. It is at the point of crises where the conditions are right for Revolutionary Science and a new paradigm can be established.
One final thing to note, invariably two competing paradigms will co-exist for quite some time and will try to rationalize one's paradigm through the others. Kuhn speak to this in terms of what he calls incommensurable — that is, it is not possible to understand one paradigm through the conceptual framework and terminology of another rival paradigm.
Overall the book was an excellent read - especially after I did the background work. I am glad that Dr. Ertas and Dr. Tate put forth the effort to include Kuhn's work into the curriculum. Not only do I now have a burning desire for STEM, I now have a profound appreciation for the Transdiciplinary program - from a theoretical and a practical perspective.
In the book, the notion of scientific development can be reduced to three distinct phases: pre-paradigm, normal science, and revolutionary science. The pre-paradigm phase, as Kuhn puts it, "is regularly marked by frequent and deep debates over legitimate methods, problems, and standard of solutions." For the most part, this is not an exercise in conciliation, rather, an exercise to define a school of thought that is likely to lay the foundation for normal science.
Once normal science begins, "puzzles" are presented and solved iteratively within the context of the dominant paradigm. It is important to note, Kuhn's intentional use of the word puzzle here. It has been recorded that many scientist were taken aback by this word usage, which may explain why Kuhn spent an entire chapter to defending it. At any rate, as long as there is "plenty to do" (i.e. legitimate puzzles to solve) and the existing paradigm do not reveal anomalies — facts that can not be reconciled within framework of the existing paradigm — normal science continues . In the event that anomalies are revealed and accumulated to the point where the paradigm breaks down, this phenomenon is considered a crisis. It is at the point of crises where the conditions are right for Revolutionary Science and a new paradigm can be established.
One final thing to note, invariably two competing paradigms will co-exist for quite some time and will try to rationalize one's paradigm through the others. Kuhn speak to this in terms of what he calls incommensurable — that is, it is not possible to understand one paradigm through the conceptual framework and terminology of another rival paradigm.
Overall the book was an excellent read - especially after I did the background work. I am glad that Dr. Ertas and Dr. Tate put forth the effort to include Kuhn's work into the curriculum. Not only do I now have a burning desire for STEM, I now have a profound appreciation for the Transdiciplinary program - from a theoretical and a practical perspective.
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