SIG: Systems Modelling and Systems Engineering

Our global society depends on complex engineered systems — from railways and airports, to satellite networks and the World Wide Web. We are actively introducing a swarm of radical new dependencies, most notably the wide-scale deployment of large-language models, a powerful black-box so complex we can barely understand it. While the science and practice of specific aspects of systems engineering such as the “planning, design, evaluation, and construction of man-machine systems” (General System Theory p.91) have been extensively studied in isolation, we lack clarity about how the pieces fit together into a coherent whole.
This reality can be at least partially attributed to the fact that systems science is so immature. Whereas mechanical, electrical, chemical and bio engineers rely on the relatively well established sciences of physics, chemistry, and biology, systems engineers do not have access to a coherently defined science of systems to ground their work in. This is a problematic state of affairs for our present and future. As humanity plunges headfirst into the age complexity, we must develop our capacity to engineer and maintain complex systems in a truly systemic fashion. 
Our complex adaptive engineered systems, by nature of being designed and steered by humans, will always display emergent behavior, often leading to unwanted results or unintended consequences. Therefore we must aim not for the perfect prediction and control sought by the physical sciences, but rather for a greater understanding and an effective synthesis of holism and reductionism offered by the systems (meta)science that will help us anticipate, grapple with, and adapt to the behavior of complex engineered systems.
Within this context, this SIG explores the role of formal system languages and of systems modeling in supporting a systems engineering practice that is grounded in a science of systems.
Formal System Languages
Systems scientists and engineers need a unified language of systems. We need an ontology that effectively merges the largely positivist world of systems engineering and more holistic world of systems science. Towards that end, George Mobus has proposed a candidate System Language (SL) which will allow humans to easily talk with each other and machines about systems using verbal, graphical, and mathematical descriptions. We are studying, implementing, and critiquing SL as we use it to model and engineer specific systems of interest. We aim to inspire spirited constructive feedback, and are interested in complementary or alternative approaches to achieving the high-level goal of a unified language. Relational Holon science and Active Inference are a few examples of approaches we’re interested in. 
Systems Modeling
The process of building systems models supports better:
  • Individual and collective understanding
  • Communication
  • Prediction and anticipation in science
  • Design, building and control, in engineering
We are interested in how the practice of systems modeling can create a healthy feedback loop between the systems science and systems engineering communities in which systems scientific theory directly informs applied systems engineering work, which in turn helps theorists and scientists refine their ideas and methodologies. We strive to build “coherent models capable of describing wholes using many diverse views from a single representation” and are inspired to build modeling tools which help address the “eight-grand challenges in socio-environmental systems modeling.”