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On the Perception of Complexity and Its Implications

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Transdisciplinary Perspectives on Complex Systems

Abstract

This chapter explores the burden of complexity by considering the possibility that the system design community has been struggling with the consequences of a deep-rooted assumption concerning our core definition of a system.Recent research into individual and organizational mindsets suggests that “big assumptions” represent beliefs in our mental models of the world that are viewed as accurate representations of the way things are and are taken for granted as true. The intent of this chapter is to offer an alternative treatment of complexity in system design by extracting our community’s viewpoint—the mental construction we perceive the world through—such that we are able to look at it less subjectively. To do so, the chapter frames a normative comparative study to assess the ability of any viewpoint to successfully facilitate system design. The assurance of the design process and the correctness and completeness of the solution to resolve the need form the basis of the evaluation criteria. The study compares two viewpoints against the evaluation criteria: a prevailing viewpoint derived from our deep-rooted assumption, and a viewpoint built around an alternative view of systems. The results show that the prevailing viewpoint becomes increasingly unsatisfactory as systems exceed the capability and capacity of the practitioner to comprehend, and therefore brings into question the validity of our deep-rooted assumption for the design of complex systems. The analysis further suggests that the system design community has been actively compensating for the insufficiency of its models, which can create a perception of complexity as significant to design. On the other hand, the alternative viewpoint demonstrates theoretical agreement with the evaluation criteria regardless of scale and scope and shows the potential for systematic solution derivation, suggesting that the alternate definition of systems might form a more suitable basis for the design of “complex” systems. The seemingly insurmountable problems we experience with the burden of “complexity” may have a path to resolution, but only if we choose to accept the implications that our struggles may be self-imposed.

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Notes

  1. 1.

    Calvano and John assert that “complexity poses a major challenge to our ability to achieve successful systems.”

  2. 2.

    Naturally, the heliocentric viewpoint has since expanded with our improved understanding of gravity and the effects of extra-solar celestial bodies on the orbital motions within our solar system.

  3. 3.

    Does this suggest the importance of being cautious whose vantage point we construct around?

  4. 4.

    There is a distinction between an abstract value (something that is of significance) and the specific, measurable instance it takes on within a context (its set-point).

  5. 5.

    Change in the sense of “an act to make something different.”

  6. 6.

    Conformal includes the notion of what is sufficient. Therefore, non-conformal implies insufficiency.

  7. 7.

    The reference describes the use of technology as something that “enhances” the human.

  8. 8.

    This perception should be disambiguated from the measurement of complexity. A perception of complexity intrinsically carries with it the notion of significance to some end.

  9. 9.

    Prior to the 1940s, discussions of “complexity” seemed focused on mathematical systems.

  10. 10.

    We have demonstrated the ability to emulate these behaviors on a small scale under controlled conditions—swarm robot demonstrations, for instance. But what happens when we attempt a system beyond our capability and capacity to comprehend its completeness?

  11. 11.

    Perhaps this apparent “deducibility” is a consequence of sufficient experiential knowledge and practitioner pattern-matching?

  12. 12.

    Perhaps we should consider a more apt name for Helbing’s referenced science?

References

  1. Parunak, H., & VanderBok, R. S. (1997). Managing emergent behavior in distributed control systems. Anaheim, CA: ISA-Tech. Retrieved from http://pdf.aminer.org/000/333/760/integrative_technology_engineering_emergent_behavior_into_materials_and_systems.pdf

  2. Mogul, J. C. (2006). Emergent (mis)behavior vs. complex software systems. 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006, New York, pp. 293–304. doi: 10.1145/1217935.1217964.

  3. Kilner, S. Complexity metrics and difference analysis for better application management [whitepaper] [Online]. [Cited: January 2, 2015]. http://www.databorough.com/downloads/White_Papers/Complexity-Metrics-and-Difference-Analysis-White-Paper.pdf

  4. Kreimeyer, M., & Lindenmann, U. (2011). Complexity metrics in engineering design. Managing the structure of design processes (Vol. XIII). New York: Springer.

    Book  Google Scholar 

  5. Houghton Mifflin Company. (1985). The American heritage dictionary (2nd College ed.). Boston: Houghton Mifflin Company.

    Google Scholar 

  6. Calvano, C. N., & John, P. (2004). Systems engineering in an age of complexity. Systems Engineering, 7(1), 25–34.

    Article  Google Scholar 

  7. Deshmukh, A., & Collopy, P. (2010). Fundamental research into the design of large-scale complex systems (AIAA 2010–9320). 13th AIAA/ISSMO multidisciplinary analysis optimization conference. AIAA 2010–9320. Fort Worth, TX: AIAA/ISSMO.

    Google Scholar 

  8. Collopy, P. (2012). A research agenda for the coming renaissance in systems engineering (AIAA 2012–0799). 50th AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition. Nashville, TN: AIAA.

    Google Scholar 

  9. Sangiovanni-Vincentelli, A. (2010). Managing complexity in IC design. Complexity workshop presentation preceding the DARPA Adaptive Vehicle Make (AVM) program. Spring 2010.

    Google Scholar 

  10. Pughat, A. (2012). Power, interconnect and complexity crises in future VLSI: From a designer’s point of view. International Journal of Electrical Engineering and Technology (IJEET), 3(2), 210–222.

    Google Scholar 

  11. Kubik, A. (2003). Toward a formalization of emergence. Artificial Life, 9(1), 41–65.

    Article  Google Scholar 

  12. Newman, D. V. (1996). Emergence and strange attractors. Philosophy of Science, 63(2), 245–261.

    Article  Google Scholar 

  13. Goldstein, J. (1999). Emergence as a construct: History and issues. Emergence, 1(1), 49–72.

    Article  Google Scholar 

  14. Emmeche, C., Koppe, S., & Stjernfelt, F. (1997). Explaining emergence: Towards an ontology of levels. Journal for General Philosophy of Science, 28, 83–119.

    Article  Google Scholar 

  15. Stepney, S., Polack, F. A. C., & Turner, H. R. (2006). Engineering Emergence. ICECCS 2006: 11th IEEE International Conference on Engineering of Complex Computer Systems (pp. 89–87). Stanford, CA: IEEE.

    Google Scholar 

  16. Fricke, E., & Schulz, A. P. (2005). Design for changeability (DfC): Principles to enable changes in systems throughout their entire lifecycle. Systems Engineering 4(8).

    Google Scholar 

  17. de Neufville, R. (2004). Uncertainty management for engineering systems planning and design. MIT Engineering Systems Symposium.

    Google Scholar 

  18. Hastings, D. E., Weigel, A. L., & Walton, M. A. (2003). Incorporating uncertainty into conceptual design of space system architectures. INCOSE International Symposium, 13(1), 1380–1392.

    Google Scholar 

  19. de Weck, O. L., & Jones, M. B. (2004). Isoperformance: Analysis and design of complex systems with known or desired outcomes. 14th Annual International Symposium of the International Council on Systems Engineering (INCOSE), Toulouse.

    Google Scholar 

  20. Project Performance International. Training Available On-Site. Project Performance International Web site. [Online] [Cited: May 12, 2015.] www.ppi-int.com/training/onsite-training.php

  21. Applied Technology Institute. ATI Courses. Applied Technology Institute Web site [Online]. [Cited: May 12, 2015]. www.aticourses.com/index.htm

  22. Kuhn, T. S. (1970). The structure of scientific revolutions. Chicago: The University of Chicago Press.

    Google Scholar 

  23. Elon Musk’s secret weapon: A beginner’s guide to first principles. Evantostudio (blog article) [Online] November 2013. [Cited: January 5, 2015]. http://studioblog.envato.com/elon-musks-greatest-weapon-laymans-guide-first-principles/

  24. Boyle, R. (1661). The skeptical chymist: Or chymico-physical doubts & paradoxes. London: J. Cadwell.

    Book  Google Scholar 

  25. Hill, J. H., & Petrucci, R. H. (1996). General chemistry. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  26. Cooper, G. R., & McGillem, C. D. (1967). Methods of signal and system analysis. New York: Holt, Rinehart and Winston.

    Google Scholar 

  27. Kegan, R., & Lahey, L. L. (2009). Immunity to change: How to overcome it and unlock the potential in yourself and your organization (leadership for the common good). Boston: Harvard Business School Publishing Corporation.

    Google Scholar 

  28. Dolling, L. M., Gianelli, A. F., & Statile, G. N. (Eds.). (2003). The tests of time: Readings in the development of physical theory. Princeton, NJ: Princeton University Press.

    Google Scholar 

  29. Barnett, P. (2015, January/February). Measures that matter. Corporate Finance Review, 5–10.

    Google Scholar 

  30. Ackoff, R. L., Magidson, J., & Addison, H. J. (2006). Idealized design: How to dissolve tomorrow’s crisis…today. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  31. Maier, M. W., & Rechtin, E. (2000). The art of systems architecting (2nd ed.). New York: CRC Press.

    Google Scholar 

  32. OK Go. (2014). The writing’s on the wall. You Tube [Music Video].

    Google Scholar 

  33. Routio, P. Normative Analysis and Preparing the Proposal. Arteology, the science of products and professions [Online]. [Cited: May 12, 2015]. www2.uiah.fi/projecti/metodi/179.htm#compare

  34. Crutchfield, J. P. (1994). Is anything ever new? Considering emergence. SFI Working Paper.

    Google Scholar 

  35. Estefan, J. A. (2008, May 23). Survey of model-based systems engineering (MBSE) methodologies [Online]. [Cited: January 5, 2015.] http://pdf.aminer.org/000/260/416/towards_a_unified_paradigm_for_verification_and_validation_of_systems.pdf

  36. Office of the Under Secretary of Defense (Acquisitions, Technology and Logistics). (2008, August). Systems engineering guide for systems of systems [Online] 1.0. [Cited: January 5, 2015.] http://www.acq.osd.mil/se/docs/SE-Guide-for-SoS.pdf

  37. Larson, W. J., & Wertz, J. R. (Eds.). (1999). Space mission analysis and design (space technology library) (3rd ed., Vol. 8). Boston: Microcosm Press.

    Google Scholar 

  38. Karwowski, W., Soares, M. M., & Stanton, N. A. (2011). Human factors and ergonomics in consumer product design: Methods and techniques: Needs analysis: Or, how do you capture, represent, and validate user requirements in a formal manner/notation before design. Boca Raton, FL: CRC Press.

    Google Scholar 

  39. Babou, S. (2008). What is stakeholder analysis? The project management hut Web site [Online]. http://www.pmhut.com/what-is-stakeholder-analysis

  40. Wogalter, M. S., Dempsey, P. G., & Hancock, P. A. (2000). What’s in a name? Using terms from definitions to examine the fundamental foundation of human factors and ergonomics science. Theoretical Issues in Ergonomics Science, 1, 1.

    Article  Google Scholar 

  41. Hughes, T. P. (1983). Networks of power: Electrification in Western society, 1880–1930. Baltimore, MD: Johns Hopkins University Press.

    Google Scholar 

  42. Hughes, T. P. (2004). Human-built world: How to think about technology and culture. Chicago: University of Chicago Press.

    Google Scholar 

  43. Arthur, W. B., & Polak, W. (2006). The evolution of technology within a simple computer model. Complexity, 11(5), 23–31.

    Article  Google Scholar 

  44. Wolfram, S. (2002). A new kind of science. Wolfram Media.

    Google Scholar 

  45. Bloch, M., Blumberg, S., & Laartz, J. (2012, October). Delivering large-scale IT projects on time, on budget, and on value. McKinsey & Company Web Site [Online]. [Cited: January 2, 2015.] http://www.mckinsey.com/insights/business_technology/delivering_large-scale_it_projects_on_time_on_budget_and_on_value

  46. Eremenko, P. (2010, October 7). Adaptive vehicle make [proposer’s day briefing to DARPA for the Adaptive Vehicle Make Program]. DARPA Web Site [Online]. www.darpa.mil/WorkArea/DownloadAsset.aspx?id=2659

  47. Baas, N. A., & Emmeche, C. (1997). On emergence and explanation. Intellectica, 2(25), 67–83.

    Google Scholar 

  48. Helbing, D. (2014). Complexity time bomb—When systems get out of control. Chapter 2, Digital Society, 2. Forthcoming. SSRN: http://ssrn.com/abstract=2502559

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Acknowledgements

We’d like to extend our appreciation to Draper for providing opportunities to ignore boundaries and question all things assumed and sacred; to Frank Serna for extending the invitation to propose our ideas for this volume and for being our advocate and advisor; to Dan Soares for his unwavering support and indispensable contributions; and to Spencer Lewis for volunteering to extend our research of the existing literature.

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Correspondence to J. E. Manuse Ph.D. .

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Manuse, J.E., Sniezek, B. (2017). On the Perception of Complexity and Its Implications. In: Kahlen, J., Flumerfelt, S., Alves, A. (eds) Transdisciplinary Perspectives on Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-38756-7_9

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