Complex Systems and Information with Prof. Karoline Wiesner
Jul 21, 2021
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Professor Karoline Wiesner, Professor of Complexity Science, discusses the field of complexity science, measuring complexity, information theory, entropy, zero entropy states, adaptability of complex systems, complexity science as a new way of doing science, measuring nonlinearity and complexity, complexity science and ethical reasoning.
Measuring order is crucial in understanding complexity and can be done through assessing the predictability and structure of a system.
Measuring disorder provides insights into the complexity of individual components within a system and helps understand their behavior and interactions.
Measuring nonlinearity captures the holistic behavior of a complex system and helps analyze the interconnections and emergent properties.
Deep dives
Measurements of Order
One of the key tools in understanding complexity is measuring order. Order refers to the predictability and structure of a system. By measuring the level of order present, we can assess the complexity of a system. This can be done using measures such as entropy, which quantifies the degree of disorder in a system. Another measure of order is the relationship of parts within a system, such as the nestedness or ratio of inputs to outputs. By measuring order, we gain insight into the organization and predictability of complex systems.
Measurements of Disorder
In addition to measuring order, it is also crucial to measure disorder in complex systems. Disorder refers to the absence of predictability or randomness within a system. Measures of disorder can provide insights into the complexity of individual components within a system. By assessing the level of disorder, we can better understand the behavior and interactions of the parts within a complex system.
Measurements of Nonlinearity
Nonlinearity is another important aspect of complexity that can be measured. Nonlinearity refers to the emergence of complex behaviors that cannot be attributed solely to the individual components of a system. Measuring nonlinearity helps to capture the holistic behavior of a complex system, providing insights into the interconnections and emergent properties of the system. Nonlinearity can be assessed through various statistical methods, including fitting nonlinear models and analyzing the relationships between variables.
Measuring Emergent Properties
Lastly, an effective way to measure complexity is by examining the emergent properties of a system. Emergent properties refer to the properties or behavior that arise from the interactions of the individual components of a system. These properties are not present in the individual components alone and can only be observed at the collective level. By measuring emergent properties, we can gain a deeper understanding of the complexity and dynamics of a system.
Complexity as a Measure of Systems
The podcast episode explores complexity as a measure of systems. Complexity is seen as a way to understand the nonlinearity and intricacy of a system. However, comparing the complexity of different systems is challenging due to the variety of possible models and the broad spectrum of complexity. Complexity science can help us make ethically informed decisions by identifying the characteristics and correlates of ethical value in systems. It can enable us to make triage decisions and prioritize actions that promote continuity, biodiversity, and a decrease in local entropy.
Misconceptions and Key Insights
One major misconception is the conflation of complex systems with chaotic systems. Complexity and chaos are distinct phenomena, yet they are frequently linked. Complexity science offers the insight that knowledge from one field can be translated and applied to another field, highlighting the universality of complexity. This enables us to tackle new problems by leveraging knowledge from unrelated domains, fostering cross-disciplinary solutions. Additionally, fostering dialogue and engaging with diverse perspectives can enhance our understanding of complex systems and aid in making informed decisions.
This episode is another dive into what is one of the most fascinating and promising fields of our age: complexity science. It's a relatively new field that is transforming how we see and understand the world across multiple disciplines. Most importantly, it's can provide us with a deeper understanding of our collective interactions with the complex biophysical system we call, Earth and how we might avert the catastophes that loom.
Joining me today is Professor Karoline Wiesner, Professor of Complexity Science at the University of Potsdam, Germany, and Associate editor for the journals Entropy and Advances in Complex Systems
Her research focuses on the use of information theory in the study of formation, maintenance and stability of complex systems.
She is also one of the authors of the recently released book What is a Complex System, which served as the basis of my interview with her.
In our conversation, we cover:
What is a complex system?
What is complexity and what are some ways we can measure it?
Why information theory and complexity science are such powerful tools for understanding the world?
We also spend some time discussing entropy, order, and disorder, as well as a bit on how these things might be related to ethical value, which, if has been a pet interest of mine in recent times.
Unfortunately we didn't get to cover all of the topics I wishes to explore as we were bedevilled by technical difficulties, so the conversation might not flow as normal. Regardless, I still had a great time speaking with Prof. Wiesner and I hope you enjoy it as well.