Eighth Law of the Interface: Interfaces are subject to the laws of complexity

Once upon a time… Historical narratives are usually presented as a linear succession of events. Henry VII (1485–1509) was followed by Henry VIII (1509–1547), Edward VI (1547- 1553) and Lady Jane Grey, who only governed for nine days in 1553. In the same way, the version 1.0 of Photoshop (1990) was followed by 2.0 (1991), 2.5 (1992) and 3.0 (1994), which was perhaps the most revolutionary of all because it incorporated layers. Applying linear models to evolutionary processes ends up generating mythical discourses impregnated with an ideological faith in the future. The linear series like 1.0, 2.0, 3.0, etc. only show a part of a much more complex and conflictive process. Marketing experts know this very well. We are all waiting for the new version of a smartphone and we feel frustrated because we know that the one we just bought is already old.

How can the evolution of interfaces be represented without falling into the simplicities of the sequential model? Is it possible to complement a linear interpretation with other perspectives that allow us to visualize the evolutionary processes in another way? In this Law I will reflect on the evolution of the interface ecosystem (Third Law) from the perspective of the complexity theory.

Complexity

Talking about complexity is not simple at all. A system is complex when it is composed of interrelated elements that exhibit general properties not evident in the sum of the individual parts (Waldrop, 1992). The complexity can be disorganized, for example when millions of elements have random relationships with each other, or organized, when the number of relationships between elements is reduced. A system composed of gas molecules in a container is an example of disorganized complexity; organized complexity manifests itself in biological or economic systems. According to Ricard Solé “complexity surrounds us and is part of us” (2009:20). Stuart Kauffman (1995) believes that the general principles of coevolution and self-organization govern the biological (biosphere), economic (economosphere) and technological (technosphere) domains. Perhaps, as Kauffman suspects, the same law applies to all the biospheres of the cosmos.

Kauffman and other scientists from the Santa Fe Institute consider that technological evolution is based on laws similar to those that govern the biological domain. After 2.5 million years of evolution it could be said that the culture of Homo sapiens is a network of designers, users, design strategies, use tactics, skills, practices, processes, institutions, texts, hardware, software, artifacts, proposals and interaction contracts, and, above all, a network of interfaces (First and Third Law) whose complexity has nothing to envy of biological ecosystems. According to Kauffman “tissue and terracotta may evolve by deeply similar laws” (1995:194).

This migration of analytical models from biological to technological research is fundamental for understanding the interface ecosystem because, among other advantages, it definitively takes us away from any form of determinism. The complexity theory facilitates understanding phenomena such as the Cambrian explosion of technological species or the proliferation of variations in certain moments of the evolution of an interface (Fourth Law).

Technology, complexity and increasing returns

The best interfaces generate virtuous circles. Brian Arthur, a researcher from the Santa Fe Institute and author of The Nature of Technology (2009), argues that technologies improve with their use and adoption, which leads to greater use and adoption, thus generating positive feedback (increasing returns). He also affirms that new technologies are nothing else than combinations of previously existing technologies. However, this “combination principle” was not enough for Arthur, so he decided to complete his model with a second principle: technologies are recursive systems, that is, assemblies of other technologies similar to building blocks. If the content of an interface is always another interface (Third Law), Arthur complements this idea stating that “each component of technology is itself in miniature a technology”.

“Each component of technology is itself in miniature a technology”.

For Arthur the assemblages that form a technology communicate with each other and generate an evolutionary process that he defines as “combinatorial evolution”. This process, which resembles a conversation between components, never ends. The technologies, adds Arthur, are fluid: they are always in motion. As the number of actors and interfaces increases, the possibility of new emerging combinations also increases. However, not all combinations are possible or make sense (Third Law). Some combinations work; others, don’t.

According to complexity principles, we cannot know what combinations will emerge from a socio-technical network. The digital simulations that Arthur and his colleagues developed to analyze the evolution of logic circuits showed that combinations can create very complicated products. They also identified Cambrian explosions of new models after long periods without innovations and “avalanches of destruction”. Like in any other complex system, technological evolution depends on small events.

Impossible predictions

The configurations adopted by the socio- technological network and the properties that emerge cannot be explained by the individual properties of each actor. Original black and white television included color television within its possible evolutions but nobody in the 1950s could have imagined that it would be possible to watch TV on demand on a phone. Nor would anyone have thought that emails would become one of the main contents of the first Internet, or that SMS would be the killer content of the first generation of mobile phones. These developments existed in nuce, almost imperceptible, but until they connected to other actors in a new interface, they remained hidden from the observer. In a complex system the whole is much more than the sum of its parts, and what we can come to know about an interface or its actors is never enough to understand the entire ecosystem.

According to Kaufmann, it is impossible to predict the evolution of the biosphere. Something similar can be said about the socio-technological network: new variables (mutations, variations, symbiosis and interactions) emerge both in the biosphere and in the technosphere without a solution for continuity.

In the socio- technological network unpredictability increases due to overuses, misunderstandings, redesigns, negotiations, confrontations, deviant interpretations and many other amazing activities of human actors (Second Law).

In this context, the evolution of interfaces is an open and unpredictable process (Fourth Law). Kauffman argues that, in “chaotic systems we can not predict long-term behaviour” but he adds: “not predicting does not mean failing to understand or explain” (1995:17).

Note: This text is a synthesis of my book Las Leyes de la Interfaz published by Gedisa in 2018.

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References

Arthur, B. (2009). The Nature of Technology. What It Is and How It Evolves. New York, NY: Penguin.

Kauffman, S. (1995). At Home in the Universe: The Search for Laws of Self- Organization and Complexity. New York, NY: Oxford University Press.

Solé, R. (2009). Redes complejas. Del genoma a Internet. Barcelona: Tusquets.

Waldrop, M. (1992). Complexity: The Emerging Science at the Edge of Order and Chaos. New York, NY: Simon & Schuster.