Chapter 3. Evo Devo Foresight: Unpredictable and Predictable Futures

Evo 2. Imaginations, Combinatorials, Emergences, & Divergences

Our imaginations offer us another powerful road to evolutionary foresight. Brainstorming is the technique most commonly associated with creative imagining, a process of initially “high quantity, no quality evaluation” idea production that can open us up to seeing outcomes that we didn’t realize were possible. Using design thinking, reading science fiction and creative literature, using CLA and other methods can greatly expand our ability to imagine outcomes. Methods like futures wheels, which explore possible consequences and outcomes via causal chains, branching out from the central trend, event, or issue being explored, are another very powerful way to harness our imaginations to map a possibility space.

Another well-used evolutionary foresight approach is the exploration of combinatorials of possibilities. This can be done at a fine level of granularity, with methods like cross-impact analysis, a way of exploring outcomes by putting causal factors, issues, or other entities in an n-by-n matrix, or a low dimensional set of matrices, and exploring all the ideas or outcomes suggested by combining each of those entities. Many locations on the matrix can be silly, causing us to consider combination of words and ideas that don’t make sense. But they can also be insightful, showing us a few combinations and possible implications, that we hadn’t considered.

We can also explore outcome possibilities at a coarse level of granularity with methods like scenario analysis, which require us to determine particularly important and/or uncertain outcomes, causes or driving forces, on a very small number of dimensions, and build stories about the futures that would exist if those particular combinations occurred.

Emergences, or the looking for emergent new complex adaptive systems that are more than the sum of their combined parts, occuring via the collective interaction of simpler rules and systems, is another powerful way to explore the possibility space. A few emergences will be developmental, but of course the vast majority will be evolutionary, useful in particular times and places, but not broadly optimal, versus other kinds of emergences. Both John Holland’s Emergence (1999) and Steven Johnson’s Emergence (2002) offer good popular introductions to this universal process. Miller and Page’s Complex Adaptive Systems (2007) is a popular technical work. Thinking carefully about the conditions necessary for emergence of new complex adaptive systems in physics, chemistry, and biology, can help us greatly to look for those conditions in society and technology.

Yet another tool of possibility foresight is the exploration of divergences from our current condition. Futures wheels can do this at a basic level, but there are many more formal methods like TRIZ, morphological analysis, and degrees of freedom analysis that explore the dimensionality of complex systems. One particularly powerful approach in the exploration of divergences is to look for those newly emerging systems, platforms, or tools that will greatly improve the thinking or behavioral options available to people. Emergences like electricity, cars, computers, phones, and software often create powerful divergences, greatly expanding the possibility space.

As beings of finite computational complexity, we are often quite poor at thinking through what will happen next at divergence points. Any new tool has thousands of potential applications, and once it arrives, we often see only a few of them. So it is particularly helpful, when some new freedom like Twitter emerges, to look for the “killer app” for that tool, the most developmentally dominant users and contexts. We have to mentally consider many possible use cases before it becomes obvious that, among other things, Twitter will be excellent for celebrities, and for quick updates among masses of protestors using smartphones, as in the Arab Spring (2010-present).

Share your Feedback

Better Wording? References? Data? Images? Quotes? Mistakes?

Thanks for helping us make the Guide the best intro to foresight on the web.