Abstract
This chapter attempts to characterize the current “equilibrium” state of thinking with respect to probability and statistics for systems-based problems. This chapter looks at questions still to be addressed: What are the roles of experts and the enormous amount of drill and other convergent approaches in education and training, including the presupposition of “universals” assumed pedagogically? How does this education and training provide a world view that assists in “bridging the gap” between finite samples and infinite populations—even though the bridges are corrigible? How does one deal with such “deterministic” subjects as chaos theory when unknown initial conditions provide room for developing probabilistic models? Does Taleb’s contention of the incomputability of Black Swans result from the “wobble” inherent in extreme value distributions, or can they be and have they been successfully applied with qualifications? How does one use nonlinear reasoning to understand differently the so-called “fallacy of affirming the consequent” when so many theories are praised for their successes? This chapter also asks how competition can be encouraged and what decision procedures work best with robust simulation outcomes. This chapter specifically addresses how many of the concepts covered in this book including robust simulation, instabilities in extreme value distributions, and linear reasoning upset a very long-standing Western tradition of believing that there is but a unique solution, a singular truth to be achieved.
In theology or philosophy, you may (with due intellectual modesty) adopt as personal working positions the ideas of your inherited culture; but you cannot deny others the right to adopt different working positions for themselves, let alone pretend that your experience “proves” the truth of one such set of opinions, and the necessary falsity of all the others. (From p. 29, Toulmin, Stephen, 1992, Cosmopolis: The Hidden Agenda of Modernity, Chicago: University of Chicago Press)
The study of the confirmation procedures as they are practiced in the sciences is … often the study of what scientists will and will not give up in order to gain other particular advantages. (From p. 212 in Kuhn, Thomas, 1977, The Essential Tension: Selected Studies in Scientific Tradition and Change, Chicago: University of Chicago Press)
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
See Taylor, C., R. Murnane, W. Graf, and Y. Lee, 2013, “Epistemic Uncertainty, Rival Models, and Closure,” Natural Hazards Review, February, pp. 42–51, volume 14, number 1.
- 2.
From p. 83 in Bernstein, Peter L., 1996, Against the Gods: The Remarkable Story of Risk, New York: John Wiley & Sons, Inc.
- 3.
Pertinent pages include pp. 84, 104 - ->Toulmin, Stephen, 1992, op. cit.
- 4.
On how rational numbers as those referenced must be used for “univariate” alpha distributions in which the slope is less than 2 and in some cases less than 1, see p. 15 in Nolan, John P., 2009, Stable Distributions: Models for Heavy Tailed Data, accessed on the Internet 2/27/13.
- 5.
Written communication, Melissa Dresler, 7/22/13.
- 6.
See, for instance, pp. 225, 234 in - ->Kuhn, Thomas, 1977, op.cit.
- 7.
See pp. 226–227 in - ->Kuhn, Thomas, 1977, Ibid.
- 8.
See p. 234 in Kuhn, Thomas, Ibid.
- 9.
On pp. 112–113, in - ->Flyvbjerg, Bent, Nils Bruzelius, and Werner Rothegatter, 2003, Megaprojects and Risk: An Anatomy of Ambition, Cambridge, UK: Cambridge University Press, Funtowicz and Ravetz are used to define “peers” either as scientists and experts who are colleagues working within the “paradigm of the official expertise” or those who are enriched “at the very least” by the contribution of other scientists and experts and who are “technically competent but representing interests outside the social paradigm of the official expertise.” In - ->Flyvbjerg, Bent, 2001, Making Social Science Matter: Why social inquiry fails and how it can succeed again, Cambridge, UK: Cambridge University Press, Hubert Dreyfus is used on pp. 16–18 to define (level 4) “proficient performer: beyond analytical rationality” and “expert.” Experts proceed intuitively, synchronically, and holistically to achieve a high level in situations in order to make decisions. Of course, there are libraries of works that show that experts can make mistakes, and these include mistakes on large-scale political judgments as shown in Tetlock, P. E., 2005, Expert political judgment, Princeton, N. J.: Princeton University Press. The definitions that Flyvbjerg, Dreyfus, and colleagues used do not require that experts be infallible. One finds the 10,000 h rule used for outlier performance in Gladwell, Malcolm, 2008, Outliers: The Story of Success, New York: Back Bay Books, Little Brown and Company. Of course, there are many who have spent 10,000 h on some tasks and still not achieved a high level of competence.
- 10.
For this view for - ->earthquake portfolio evaluations, see J. Lemaire and C. Tillman. 1993, “Models for Earthquake Insurance and Reinsurance Evaluations,” Proceedings of the Second International Symposium on - ->Uncertainty Modeling and Analysis, Los Alamitos, California: IEEE Computer Society Press, April.
- 11.
From p. 37e in Wittgenstein, Ludwig, 1967, Remarks on the Foundations of Mathematics, Cambridge, MA: the M. I. T. Press, first published in 1956, edited by G. H. von Wright, R. Rhees, G. E. M. Anscombe, and translated by G. E. M. Anscombe.
- 12.
See p. 222 in Kuhn, Thomas, 1977, op. cit.
- 13.
Quoted on p. 333 in Isaacson, Walter, 2007, Einstein: His Life and Universe, New York: Simon & Schuster.
- 14.
See pp. 138, 288 in - ->Taleb, Nassim Nicholas, 2012, - -> Antifragile: Things that Gain from Disorder, New York: Random House.
- 15.
For describing - ->chaos as entering when the number of variables in a nonlinear model exceeds 3 and also when the topic has yet to be explored enough, as with immune systems and ecosystems, see p. 11, Strogatz, Steven H., 1994, Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, Cambridge, MA: Perseus Books Publishing, LLC.
- 16.
These simplifications are similar to the formalizations in - ->Peirce, Charles, 1901, 1903, in “Abduction and Induction,” pp. 150–156; in Charles - ->Peirce, 1955, ibid., p. 151; and Wikipedia, “Abductive reasoning,” accessed 12/14/2013. Note that Peirce’s discussion of Kepler’s discoveries, which are not easily encapsulated in two or three lines, compares with the discussions of discoveries in healthcare discussed in Chap. 7.
- 17.
These simplifications are similar to the formalizations in Peirce, Charles, 1901, 1903, in “Abduction and Induction,” pp. 150–156; in Charles Peirce, 1955, ibid., p. 151; and Wikipedia, “Abductive reasoning,” accessed 12/14/2013. Note that Peirce’s discussion of Kepler’s discoveries, which are not easily encapsulated in two or three lines, compares with the discussions of discoveries in healthcare discussed in Chap. 7.
- 18.
Written communication, Melissa Taylor Dresler, 7/22/13.
References
Bernstein, P. L. (1996). Against the Gods: The remarkable story of risk. New York: Wiley.
Flyvbjerg, B. (2001). Making social science matter: Why social inquiry fails and how it can succeed again. Cambridge: Cambridge University Press.
Flyvbjerg, B., Bruzelius, N., & Rothegatter, W. (2003). Megaprojects and risk: An anatomy of ambition. Cambridge: Cambridge University Press.
Gladwell, M. (2008). Outliers: The story of success. New York: Back Bay Books, Little Brown and Company.
Isaacson, W. (2007). Einstein: His life and universe. New York: Simon & Schuster.
Kuhn, T. (1977). The essential tension: Selected studies in scientific tradition and change. Chicago: University of Chicago Press.
Lemaire, J. & Tillman, C. (1993, April). Models for earthquake insurance and reinsurance evaluations. In: Proceedings of the second international symposium on uncertainty modeling and analysis. Los Alamitos: IEEE Computer Society Press.
Nolan, J. P. (2009). Stable distributions: Models for heavy tailed data. Accessed on the internet 27 Feb 2013.
Peirce, C. (1901, 1903). In abduction and induction. In Peirce Edition Project (ed.), The essential Peirce, volume 2: Selected philosophical writings, (pp. 1893–1913). Bloomington, Indiana University Press.
Strogatz, S. H. (1994). Nonlinear dynamics and chaos: With applications to physics, biology, chemistry, and engineering. Cambridge, MA: Perseus Books Publishing, LLC.
Taleb, N. N. (2012). Antifragile: Things that gain from disorder. New York: Random House.
Taylor, C., Murnane, R., Graf, W., & Lee, Y. (2013). Epistemic uncertainty, rival models, and closure. Natural Hazards Review, 14(1), 42–51.
Tetlock, P. E. (2005). Expert political judgment. Princeton: Princeton University Press.
Toulmin, S. (1992). Cosmopolis: The hidden agenda of modernity. Chicago: University of Chicago Press.
Wittgenstein, L. (1967). Remarks on the foundations of mathematics, Cambridge, MA: the M. I. T. Press, first published in 1956, edited by G. H. von Wright, R. Rhees, G. E. M. Anscombe, and translated by G. E. M. Anscombe.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Taylor, C.E. (2015). Remaining Questions: Conclusions and Queries. In: Robust Simulation for Mega-Risks. Springer, Cham. https://doi.org/10.1007/978-3-319-19413-4_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-19413-4_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19412-7
Online ISBN: 978-3-319-19413-4
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)