1.1 Systems

Designers play a crucial role in shaping our world.

They are responsible for creating products, services, interfaces, and experiences that we interact with on a daily basis. In order to create designs that effectively solve problems and meet the needs of their users, it is essential for designers to understand the decision making users, or agents, as self organizing systems as well as the context environment in which those agents operate in.

The quote "a system is greater than the sum of its parts" highlights the complex nature of interconnectedness of system parts. As stated by Donella Meadows, a system is not just the individual components that make it up, but rather the dynamic relationships and interactions between those components. This definition can be applied to non-living systems, like a car or watch, but also to living system – with an important distinction.

Most organic systems are autopoietic complex adaptive systems. They are characterized by their ability to self-organize, self-generate, and adapt to their environment – unlike the non-living systems. A human, for example, is a complex autopoietic system, but so is a human cell, as well as the economy of Canada. These systems are constantly evolving and changing in response to their surroundings. In the future, an artificial intelligence may also be considered an agent within the definition of a complex adaptive system, as it is capable of learning and possibly adapting to its environment, but that is a different story.

A system functions according to its set purpose and goals, which is the driving force behind its behavior and actions. Even when the purpose is not clearly stated or it’s misguidedly stated, its own behaviour implicitly reveals its purpose.

1.1.1 System = Agent

One key aspect of seeing the world as a system of systems is recognizing that the systems or agents are not just individual people, which are the centre of our examination, but also teams, companies, economies, and other larger systems. These agents have the ability to make decisions and take action, ability we call agency. They are also self-aware in relation to their environment, seeking to survive and thrive within their environments, as described in Patterns of Reasons. The key activity of decision making agent, as mentioned in the Main Pattern, is balancing value creation with limited resources available to the agent all according to their goals and purpose. It is the designer's job to understand these agents, their motivations, and the challenges they face, and to create designs that enhance their decision-making ability. This can be achieved by developing a persona, or model, of the agent that describes their context, motivations, and challenges for action.

1.1.2 Context Environment

Another important aspect of seeing the world as a system of systems is understanding the multiple environments or contexts in which agents function and interact with. These environments can be work, family, nature, community, nation, interest groups, or any other larger system that inform meaning, shape values, and give directions of the agent's actions.

As designers, it is important to identify these contexts and understand how they shape the motivations and constraints that drive the agent's decisions and actions. Whenever possible, designers should seek to gain understanding of the agent through deep participation in their environment, their context.

Even though lots can be learned from user interviews and research of their operating procedures, interests, and motivations, a load of implicit learning can only be acquired only by participation in their operating environment along with local agents for which a designer wants to design a solution. Participation enables designer to understand myriad of overlapping systems, cultural norms, interpersonal relationships, and motivations of agents from multiple perspectives. Better the understanding of the environment, better understanding of the agents’ problems and better the future solutions. Participating in the fullness of the agent’s lived experience, designer might even realize that no solution might be the best solution. Or that solution can only be brought up by other participating agents and that designer might only need to provide an environment to catalyze that process.

1.1.3 Nested Self-Similar Systems

Finally, it is important for designers to recognize that agents are part of larger systems, which themselves are agents in even larger systems, and so on. Say, my team is an agent within the larger context of my company, and my company is an agent within larger system of a certain industry. Yet there are key patterns of interaction and reason that are identical or at least self-similar to all levels of embedded systems, such as Patterns of Decision Making, Understanding, Surviving and so on.

In nature many systems or structures follow the same recursive patterns of organization. You can notice it with any tree, for example, the main trunk, branches, then smaller branches, and even leafs resemble very self-similar shape. Mathematician Benoit B Mandelbrot coined the term fractals to describe such structures, and even more importantly introduced the math of fractals that allows us to explore natural complexity within context of science, technology, art, etc.

Fractal structures are organized that way for redundancy and parsimony. Redundancy enables system to function even when a portion of the system is damaged, and parsimony refers to simplicity and the use of minimum possible resources to create new system parts. So all is in the function of Survival and resource efficient Decision Making.

Scientist at the forefront of intelligence research (natural and artificial) are also confirming that the nature of intelligence is deeply recursive and that higher systems’ intelligence relies on lower systems’ intelligences regardless if they are of the same or fundamentally different kind.

One perspective can even invite us to discard the notion of systems (plural) and adopt just one system (singular) since nothing exists in isolation, but interacts with other entities at multiple scales at all times.