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Adaptive systems / The importance of the past in our complex futures
The importance of the past in our complex futures
Topic: Adaptive systems
by Tom, 2021 Cohort
Overview#
Complex adaptive systems (CAS) are systems where the individual agents and the system as a whole are constantly evolving their behaviour in conversation with the world around them. Examples include ecological systems, the human brain and cells, and even traffic patterns.
How do adaptive systems evolve?#
CAS can evolve in a number of ways. One of the key features of CAS is that the individual agents do not necessarily interact in a linear way. Instead, they change their behaviour seemingly independently, only for the end product to seem cohesive. There are a range of ways individual agents evolve over time, but this primer entry wants to focus on one particular lens: path dependency.
What is path dependency?#
Path dependency is the simple idea that present outcomes can be traced to historical events. It has been identified as a key feature in adaptive systems.[1] The reason path dependency is important to CAS in particular is that it is a useful tool of analysis we can apply to understand the nuances of different systems.
What does that actually mean?#
A previous primer entry focused on an understanding of food systems, and the associated issue of obesity, through the lens of CAS.[2] By analysing this system with path dependency in mind, we can understand how historical factors have bought about the current state of affairs. Environmental history, for example, has exposed the vulnerability of pastoral systems and global food security.[3] This leads societies to greater levels of mass production in the face of vulnerability. Economic history supporting globalisation trends has increased the exporting of fast food and displaced fresh food markets.[4] Political history, meanwhile, has a key role in affecting the state of healthcare systems and their capacity to deal with the obesity epidemic. The crucial takeaway is that the different agents of the system (producers, corporations healthcare structures) have all been affected by their own ‘initial conditions’.
What lessons can we learn for complexity more generally?#
There are two key lessons we can learn about complexity if we understand the role path dependency plays in CAS.
First, it is important to know the history of complex questions before we try and tackle them. If we take the time to understand this history, we might better appreciate how different agents in a system will respond to changing inputs. Looking to food systems once again, we see that knowing the history of the system enables us to make effective decisions in relation to its agents. For example, we know that political, economic and environmental action is required.
Second, we should be sensitive to the different backgrounds of human agents in CAS. This is for the simple reason that path dependency shows us history has a strong effect on those agents. Therefore, if we take their history into account, we may be able to have more positive interactions with them when trying to tackle complex problems. In turn, this may create more productive outcomes overall.
Additional Resources#
[1] Lindberg C. and Schneider M. 2013. ‘Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance’, Leadership 9(2), 229.
[2] https://vc-courses.anu.edu.au/primer/adaptive_systems_krista/
[3] Mbow, C., Rosenzweig C., and Barioni L.G. et al. 2019. ‘Food Security’ in Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Available at https://www.ipcc.ch/srccl/chapter/chapter-5/
[4] Pan A., Malik V., and Hu F.B. 2012. ‘Exporting Diabetes to Asia: The Impact of Western-Style Fast Food’, Circulation 126(2), 163.
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Disclaimer#
This content has been contributed by a student as part of a learning activity.
If there are inaccuracies, or opportunities for significant improvement on this topic, feedback is welcome on how to improve the resource.
You can improve articles on this topic as a student in "Unravelling Complexity", or by including the amendments in an email to: Chris.Browne@anu.edu.au
Overview#
Complex adaptive systems (CAS) are systems where the individual agents and the system as a whole are constantly evolving their behaviour in conversation with the world around them. Examples include ecological systems, the human brain and cells, and even traffic patterns.
How do adaptive systems evolve?#
CAS can evolve in a number of ways. One of the key features of CAS is that the individual agents do not necessarily interact in a linear way. Instead, they change their behaviour seemingly independently, only for the end product to seem cohesive. There are a range of ways individual agents evolve over time, but this primer entry wants to focus on one particular lens: path dependency.
What is path dependency?#
Path dependency is the simple idea that present outcomes can be traced to historical events. It has been identified as a key feature in adaptive systems.[1] The reason path dependency is important to CAS in particular is that it is a useful tool of analysis we can apply to understand the nuances of different systems.
What does that actually mean?#
A previous primer entry focused on an understanding of food systems, and the associated issue of obesity, through the lens of CAS.[2] By analysing this system with path dependency in mind, we can understand how historical factors have bought about the current state of affairs. Environmental history, for example, has exposed the vulnerability of pastoral systems and global food security.[3] This leads societies to greater levels of mass production in the face of vulnerability. Economic history supporting globalisation trends has increased the exporting of fast food and displaced fresh food markets.[4] Political history, meanwhile, has a key role in affecting the state of healthcare systems and their capacity to deal with the obesity epidemic. The crucial takeaway is that the different agents of the system (producers, corporations healthcare structures) have all been affected by their own ‘initial conditions’.
What lessons can we learn for complexity more generally?#
There are two key lessons we can learn about complexity if we understand the role path dependency plays in CAS.
First, it is important to know the history of complex questions before we try and tackle them. If we take the time to understand this history, we might better appreciate how different agents in a system will respond to changing inputs. Looking to food systems once again, we see that knowing the history of the system enables us to make effective decisions in relation to its agents. For example, we know that political, economic and environmental action is required.
Second, we should be sensitive to the different backgrounds of human agents in CAS. This is for the simple reason that path dependency shows us history has a strong effect on those agents. Therefore, if we take their history into account, we may be able to have more positive interactions with them when trying to tackle complex problems. In turn, this may create more productive outcomes overall.
Additional Resources#
[1] Lindberg C. and Schneider M. 2013. ‘Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance’, Leadership 9(2), 229.
[2] https://vc-courses.anu.edu.au/primer/adaptive_systems_krista/
[3] Mbow, C., Rosenzweig C., and Barioni L.G. et al. 2019. ‘Food Security’ in Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Available at https://www.ipcc.ch/srccl/chapter/chapter-5/
[4] Pan A., Malik V., and Hu F.B. 2012. ‘Exporting Diabetes to Asia: The Impact of Western-Style Fast Food’, Circulation 126(2), 163.