Hero’s Journey into TRIZ

Recently I’ve been cleaning out my file drawers and closets, going though a lot of old material I haven’t seen or thought about in some time. Some work I had collected on TRIZ (a Russian innovation methodology) struck me with its connection to my “Remote Associations” post back in early February. Just as a refresher, here’s the diagram central to that post, and then here’s a diagram of the TRIZ method.

This isn’t a perfect mapping of quadrants; since these quadrants are measuring very different things (the first measures two continua, while with the second organized four discrete items into sequential flow). That said there are some pretty strong connections between what each of these diagrams says.

Moving from specific problem to generalized problem is abstraction; it is to see the metaphorical behind the actual. It is in a sense inductive. In terms of the first diagram, it is the ability to see similarities between things that seem different.

Moving from generalized solution to specific solution is concretization; it is to designate an actual from the metaphorical. It is in a sense deductive. In terms of the first diagram, it is the ability to see differences between things that seem similar.

Recognizing the similarities between apparent differences, moving from the actual to the metaphorical, is like bridging to other places. It is in a way like the archetypal hero’s journey Joseph Campbell (expert in comparative mythologies) describes.

The hero’s journey begins with a sickness in the village, a sickness the normal medicine cannot cure. This is the actual problem. Fortunately there is a magic elixir that can cure the village, but it is far far away. So a hero must be chosen to journey beyond the village and beyond everything that is known. This is the journey from actual to metaphorical. Along the way the hero gains many magic items and companions. These are the generalized solutions. And finally the hero must secure the elixir, and return to the village with it. This is the journey back from the metaphorical to the actual with the specific solution–the solution no one else could come up with.

Now here is the problem: according to my scheme here, TRIZ puts design (seeing the similarity between different things) *after* research (seeing the differences between similar things) the in the sequence of innovation. Clear this doesn’t make sense, so clearly I’ve made a mistake somewhere–but where?

So, what’s my point? Well, I’m not sure I have one really, certainly not beyond just pointing out an interesting connection between Campbell, TRIZ and an earlier posting of mine. But this connection does seem to suggest that there is a point buried in here somewhere – a point worth trying to figure out.

Algorithms vs. Humans

There’s an increasing trend I’ve been noticing out here on the net: a growing army of jabbering zombies regurgitating the same slavish uncritical adoration of Google. This level of uncritically always makes me a bit uneasy. Finally I’ve come across a refreshingly different take on Google. Perhaps the great Google might end up being more like the Great Oz. I especially like:

On the Network, The power of people will kick the backside out of algorithms. While computer sciencey solutions are almost always gameable, communities are equally almost always resilient, adaptive, and intelligent.

Philosophically its a very compelling position. Indeed algorithms can necessarily only deal in data (dead letters so to speak). Meanwhile human communities share information, knowledge, wisdom and surprisingly little data. Admittedly wiki’s are not exactly communities of people, their content is socially created and cultivated–no algorithms.

This could explain some of my own personal experience. After reading this I realized that I’m using Google less and less frequently, in favour of Wikipedia. If I need to know something, Wikipedia is now the first place I turn. I still use Google to help me find websites, but for information or knowledge Wikipedia is my engine of choice.

Here is a visualization of the self-correcting/self-healing properties of social information software like wikipedia. I found this by following a link from peterme.com’s october 12th posting