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Exploring the Human Cognitive Capacity in Understanding Systems: A Grey Systems Theory Perspective

  • Ehsan JavanmardiEmail author
  • Sifeng Liu
Article
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Abstract

The main purpose of this study is to probe into the human capacity of understanding systems and defects in human knowledge of the world. The study addresses the greyness levels and systems levels and explains why the world cannot be perceived as a purely white or black structure. It also clarifies why human knowledge of systems always remains grey. The investigation relies on logical and deductive reasoning and uses the theoretical foundations of systems thinking and Boulding’s systems hierarchy. The most important argument that this study advances is that human knowledge, in any form or under any circumstances, is grey and incomplete and will remain grey. Because the notion of “perfect knowledge” is ambiguous given human epistemic limits, any proportion of knowledge is incomplete and prone to change. Less complexity could lead to more accurate predications, but even in the simplest forms of systems, reaching perfect knowledge seems to be an unwarranted claim. Furthermore, because our perception of past events is incomplete, we cannot predict the future with certainty, as a result of which both the past and the future appear grey to us. The world, as an integrated system, is neither black nor white, but it remains grey, and the systems partially recognized by humans are part of the grey world. Gaining knowledge and increasing discoveries only contribute to the grey systems that are already known.

Keywords

Systems thinking Grey systems theory Human understanding capacity Boulding’s systems hierarchy Uncertain systems Philosophy of grey systems 

Notes

Acknowledgements

This work was supported by a project of the National Natural Science Foundation of China (71671091), a Marie Curie International Incoming Fellowship under the 7th Framework Programme of the European Union entitled “Grey Systems and Its Application to Data Mining and Decision Support” (Grant No. 629051). It is also supported by a joint project of both the NSFC and the RS of the UK entitled “On grey dynamic scheduling model of complex product based on sensing information of internet of things” (7171101211), a project of the Leverhulme Trust International Network entitled “Grey Systems and Its Applications” (IN-2014-020), and a project of China Postdoctoral Science Foundation (2018M642254), Also, the authors would like to acknowledge the support provided by the Postdoctoral Foundation of Nanjing University of Aeronautics and Astronautics.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Institute for Grey Systems StudiesNanjing University of Aeronautics and AstronauticsNanjingChina

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