Educating for Cyber (Security)

2021 ◽  
pp. 394-408
Author(s):  
Roger Bradbury

This chapter considers the problem of educating for cybersecurity from the perspective of complex systems science. It argues that education is a process that has evolved in human social systems to curate, increase, and transmit the information needed for system survival. Education creates an increase in the negentropy (or useful information) of those systems as they seek to maximize the acquisition and throughput of energy—a physical principle known as maximum entropy production (MaxEP). Civilizations have responded to this principle over time by finding new solutions to the Earth’s MaxEP and becoming more complex in the process. A key part of this complexification is education. And in the present cyber age it is, as in previous ages, a lagging process cobbled together from the structures and processes of previous ages. The current education responses may soon be superseded as a new solution to the Earth’s MaxEP—the technological singularity—looms.

2018 ◽  
Vol 5 (2) ◽  
pp. 172189 ◽  
Author(s):  
Andrea Baronchelli

The origin of population-scale coordination has puzzled philosophers and scientists for centuries. Recently, game theory, evolutionary approaches and complex systems science have provided quantitative insights on the mechanisms of social consensus. However, the literature is vast and widely scattered across fields, making it hard for the single researcher to navigate it. This short review aims to provide a compact overview of the main dimensions over which the debate has unfolded and to discuss some representative examples. It focuses on those situations in which consensus emerges ‘spontaneously’ in the absence of centralized institutions and covers topics that include the macroscopic consequences of the different microscopic rules of behavioural contagion, the role of social networks and the mechanisms that prevent the formation of a consensus or alter it after it has emerged. Special attention is devoted to the recent wave of experiments on the emergence of consensus in social systems.


2019 ◽  
Vol 26 (2) ◽  
pp. 177-183
Author(s):  
Rebecca B Naumann ◽  
Jill Kuhlberg ◽  
Laura Sandt ◽  
Stephen Heiny ◽  
Yorghos Apostolopoulos ◽  
...  

Many of our most persistent public health problems are complex problems. They arise from a web of factors that interact and change over time and may exhibit resistance to intervention efforts. The domain of systems science provides several tools to help injury prevention researchers and practitioners examine deep, complex and persistent problems and identify opportunities to intervene. Using the increase in pedestrian death rates as an example, we provide (1) an accessible overview of how complex systems science approaches can augment established injury prevention frameworks and (2) a straightforward example of how specific systems science tools can deepen understanding, with a goal of ultimately informing action.


Homeopathy ◽  
2019 ◽  
Vol 109 (02) ◽  
pp. 042-050 ◽  
Author(s):  
Iris R. Bell

Abstract Background The concepts of complex systems science enhance the understanding of how people develop and recover from disease. Living systems (human beings, animals, and plants) are self-organizing complex adaptive systems (CAS): that is, interconnected networks. CAS maintain life by initiating and carrying out non-linear dynamical changes to optimize survival fitness and function in the context of an ever-changing environment. Aims In Part 1 of this two-part paper, we relate concepts from complex systems science to homeopathic healing. The systemic changes of homeopathic healing involve adaptive patterns of responses to salient signals (similia) for reversing disease patterns and generating emergent multi-symptom healing over time. Methods and Results This narrative review relates homeopathic clinical practice theory to complex systems and network research. Homeopathic medicines communicate individually salient environmental information to the organism, with effects that are multi-system and indirect. The body's defense mechanisms recognize the self-similar information that the correctly chosen simillimum medicine at low dose conveys as a weak external/internal environmental stressor or danger signal (hormetin) to mobilize neural and cellular defenses. The body networks then use endogenous cell to cell signaling and amplify the small magnitude signal information. The results are disproportionately large: that is, non-linear, adaptive, modifications across the inter-connected self-organized biological networks/sub-systems of the body. CAS amplification mechanisms for small or weak signals include stochastic resonance, time-dependent sensitization, and hormesis. Conclusions The body as a complex system has the capacity for self-organization, emergence and self-similarity over global (overall health and wellbeing) and local (organ) levels of organization. These features are key for future research on the systemic healing that evolves over time during individualized homeopathic treatment.


Author(s):  
Mike Unrau ◽  
Liane Gabora

We apply complex systems science to the study of social systems and show how a complex-systems-inspired theory of creativity, which is referred to as ‘honing theory’, provides insight into social innovation. We propose that creativity and social innovation are processes of self-organization that yield a lower-entropy state in worldviews, which are self-organizing webs of understanding. This allows us to offer a novel perspective on the evolution of technology, the role of creativity in cultural evolution and the manner in which creativity drives innovation in social systems, such as the economy. We also introduce creative destruction as having metaphoric relevance for a social system transition from entropy to negentropy, and offer a social innovation example addressing economic collapse and resilient reorganization. We conclude that concepts from complex systems theory, and particularly entropy, shed light on both creativity and social innovation and further our understanding of how innovation affects social systems, such as in cultural and economic change.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Alexander F. Siegenfeld ◽  
Yaneer Bar-Yam

The standard assumptions that underlie many conceptual and quantitative frameworks do not hold for many complex physical, biological, and social systems. Complex systems science clarifies when and why such assumptions fail and provides alternative frameworks for understanding the properties of complex systems. This review introduces some of the basic principles of complex systems science, including complexity profiles, the tradeoff between efficiency and adaptability, the necessity of matching the complexity of systems to that of their environments, multiscale analysis, and evolutionary processes. Our focus is on the general properties of systems as opposed to the modeling of specific dynamics; rather than provide a comprehensive review, we pedagogically describe a conceptual and analytic approach for understanding and interacting with the complex systems of our world. This paper assumes only a high school mathematical and scientific background so that it may be accessible to academics in all fields, decision-makers in industry, government, and philanthropy, and anyone who is interested in systems and society.


Author(s):  
Matt Kasman ◽  
Nancy Breen ◽  
Ross A. Hammond

Author(s):  
Patricia Goodson

This chapter discusses whether and how complex systems science (CSS) can revolutionize population health theory. First, the chapter defines theory and the practice of theory-building (or theorizing); second, it outlines some of the difficulties found in current population health theorizing; lastly, it characterizes the mechanisms through which CSS can influence, change, and revolutionize current theorizing efforts. The chapter also describes two examples of scholars who used CSS to challenge currently held assumptions and reframe complex health problems. Lastly, the author addresses the implications—of adopting a CSS approach to theorizing—for practice, policy development, and training of the future public health workforce.


Author(s):  
Yorghos Apostolopoulos

This chapter contextualizes the volume and describes its organization. It begins by delving into the limitations of the prevailing reductionist paradigm in population health science and the need for a transition from a typically risk factor–based science to a science that recognizes the whole and relationships among parts of pressing population health problems. Next, it walks readers through distinctions between public and population health on the one hand and key concepts of complexity on the other, while offering a shared understanding of population health science and complex systems science. The chapter also lays out the design of and potential audiences for this book.


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