The Memetic Bottleneck
So in the last post I talked about how the notion of simplification as a way of explaining good ideas shifts into the belief that good ideas can always be simplified, and finally into simplicity as a sign of good ideas.
Here’s my thoughts on why this is a problem.
This diagram shows two funnels. The top, red, one is a fairly basic schematic of the process of research, but it might also stand for the process of simplification in general. You start off with a mass of data. You subject it to a process of analysis, which explains the data. You boil that analysis down to an insight (see previous Blackbeard Blog entries!) which maximises its explanatory power, copyability, sexiness, etc. etc.
The insight is then delivered. The blue pyramid represents a downside scenario for what happens next. The insight is preserved intact, but becomes received wisdom - an unquestioned piece of information, something for recipients to expand, extrapolate from, base assumptions on and generally build on. For instance, if you have an idea of Maslow’s Hierarchy of Needs in your head you might decide to base your next segmentation study on those, and then you find yourself mapping different levels of relationship with a brand onto the levels of the Hierarchy, and so what you’re doing is building your own set of analysis out of the original insight, often by combining it with other insights you’ve picked up along the say (Hey! Maybe self-actualisers are more likely to be Mavens with a higher Dunbar Number!!). But - and remember this is a bad-case scenario - you run the risk of ending up with nonsense.
What’s happened here? The process represented by the red pyramid neccessarily involves simplification - stripping away parts of an idea until you’re left with a kernel of “insight”. The notion is that the insight will lead you back up the chart, encouraging you to dig deeper into the analysis. But what often happens is that the insight stands in for the analysis and the pyramid flips, transporting you into the blue pyramid like a sci-fi wormhole. Here the insight is all that is left of the original analysis. Coming to it second-hand, you assume it is correct and complete, and build on it. This isn’t necessarily harmful, of course: you can imagine a “happy” version of the blue pyramid:
Here the insight is working like insights are meant to work - it’s robust, it’s complete, it leaves nothing important out and it’s hard to misinterpret. So it’s a great foundation for building new ideas on. O happy day when we find and communicate one like that!
Of course, you can’t control ideas once they’re out there - if they’re going to live, they’re going to change. I wonder if the process of simplification accelerates this - by introducing a kind of memetic bottleneck, where the population of ideas has been reduced to a small number and the chances of those ideas mutating (being misinterpreted, extrapolated without reference to data, etc.) rapidly increases.
We live in a period where simplification processes are everywhere - I had the wikipedia page on “genetic bottlenecks” open writing this; I work in an industry forever flagellating itself for not being simple enough; once I hit “Create Post” I will go to Twitter and post a 100-character summary of this whole thing. The rapid scrambling, remixing and mutation of information that results means we live in exciting times. Is there even room (professionally or otherwise) to stand as an advocate of nuance or complexity? I’m not sure. But it would be a good idea for researchers to remember that they’re the guardians of the red half of the chart as well as enablers, for good or ill, of the blue.
