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Complexity Engineering: How Subjective Issues Become Objective

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  • José Roberto C. Piqueira
  • Sérgio Henrique Vannucchi Leme de Mattos
  • Roberto Costa Ceccato

Abstract

This study details the substantial technological progress experienced in the last few decades, its impact on engineering, and how machine learning along with data science can contribute to solving human problems. The objective here is to establish the principles of “complexity engineering,” based on the works of Edgar Morin, and to demonstrate how these principles are suitable for engineering to deal with complex systems and the wicked problems linked to them. Thus, initially, a history of the events, discoveries, and disruptive inventions that marked engineering in recent centuries is made. Conceptual considerations and practical applications of complexity engineering in different areas of knowledge are also shown. The idea is to provide a historical perspective of engineering development that started before the advent of scientific methodological contributions and is based on accurate observation of natural behaviors. Since Galileo and Newton’s objective vision, scientific progress strongly influenced engineering progress, leading to the creation of unthinkable wonders, allowing spatial trips, and mainly providing a more comfortable daily life. However, two important new issues have emerged: ways to relate this progress with life on Earth and techniques to use the big data available to improve methodological engineering attitude. In this study, these questions are discussed, and we have shown that objectively obtained big data can be used to address subjective human problems, creating a new discipline called complexity engineering. The applications of complexity engineering to real problems are presented using examples of research developed by the authors involving urban planning, mental health, and landscape ecology in problems that require massive use of data.

Suggested Citation

  • José Roberto C. Piqueira & Sérgio Henrique Vannucchi Leme de Mattos & Roberto Costa Ceccato, 2025. "Complexity Engineering: How Subjective Issues Become Objective," Complexity, John Wiley & Sons, vol. 2025(1).
  • Handle: RePEc:wly:complx:v:2025:y:2025:i:1:n:9728576
    DOI: 10.1155/cplx/9728576
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    References listed on IDEAS

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    1. Felipe A. Rizzi & José Roberto C. Piqueira, 2021. "Complexity measures for probability distributions with infinite domains," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(3), pages 1-8, March.
    2. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    3. Kunihiko Kaneko & Ichiro Tsuda, 2001. "Complex Systems: Chaos and Beyond," Springer Books, Springer, number 978-3-642-56861-9, March.
    4. Letícia P D Mortoza & José R C Piqueira, 2017. "Measuring complexity in Brazilian economic crises," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-12, March.
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