What is applied cybernetics?
“Cause and effect act in webs, not chains.” — Steve Grand (2001)
As a student of applied cybernetics at the 3A Institute, I am identifying, critiquing, and designing relationships between pieces of cyber-physical systems. Applied Cybernetics is a course contributing to a New Branch of Engineering (NBE) being developed at the Australian National University's 3A Institute, lead by Genevieve Bell. It builds and expands upon the trans-disciplinary field of Cybernetics — Norbert Wiener’s term for the study of control and communication in animals and machines: a science of data, actions, feedback loops and the connection points between them. Cybernetics is widely seen as a precursor to the field of artificial intelligence, among others.
Applied Cybernetics calls on students to think deeply about the needs of future systems by developing critical question frameworks. It pairs conceptual skills in systems thinking, design anthropology, and critical theory with practical, hands-on experiences of the code, software, data and devices that drive the development of these systems. This approach creates a new kind of practitioner, skilled in many domains relevant to the management of complex, interconnected systems, particularly concerning dependencies, failure states, and emergent behaviors.
I’ve shared my experiences in three key domains through the images below. Each link introduces a concept and case study, reviews key lessons, and describes how my thinking about systems changed as a result. I end each section by proposing one idea that I will take forward as a form of relevant practice for the New Branch of Engineering.
Cyber looks at cybernetics through programming environments and software; Physical looks at sensors; and Systems looks at how we might navigate relationships between the two. At the end of each page, there is an option to return to this one.
For term two, I have added additional lessons taken from the application and synthesis of skills from term one. The second term portfolio is accessible below.
The images were generated by Eryk Salvaggio using a machine learning algorithm for images, known as a style transfer.