"All musicians are subconsciously mathematicians" ~ Thelonious Monk

Gregory Ronczewski is the Director of Product Design at TeamFit
view his skill profile

Last week a new book appeared on my desk. My wife bought it at Knick Knack Nook store on Bowen for just $1. I once found IDEO Method Cards in brand-new condition for $1.50 (on Amazon the same set costs over $100). Anyhow, it's a great place to find the good stuff and proof of how diverse is the population of our small island. The book is titled Jazz of Physics and is written by Stephon Alexander. Being a physicist and also a jazz musician, he looks at connections between the structure of music and the universe. It's a great read full of ideas on how supposedly distant disciplines could be adapted to illustrate or explain the workings of what surrounds us. On page 5 there is a splendid diagram that John Coltrane gave to Yusuf Lateef in 1961. I can't reproduce it here due to the copyrights restrictions, but here is a link to the Mathematics of Music.

Early in his career, the author found himself in Leon Cooper's lab at Brown University working as his Ph.D. student on a neuroscience project. They use the Hopfield model which illustrates how associative memory works, but as Alexander explains "the idea behind the model came not from neuroscience but from quantum mechanical physics of magnetism, specifically, the Ising model, named after German physicist Ernst Ising."

For some reason—must be the associative memory—it took me back to another book I enjoyed tremendously - Before you know it — the unconscious reasons we do what we do by John Bargh. The science uncovering how we memorize and retrieve memories is fascinating, and in the same spirit of connecting distant concepts, I started to think about skills and how the use of skills goes through the same pattern. When a new skill is acquired we tend to use it often, to explore its connections, see new applications. We are learning and using the Bargh metaphor, the network linking those skills together is reasonably active. In time, as we move on and new paths to the new sets of skills emerge, the past does not disappear - it is always there, but the connections fade into the background, replaced by what occupies our mind now. Skills on their own are just skills. An abstract concept aimed at capturing our abilities to understand and perform. When separated from each other their energy is dormant. Once connected, the network suddenly lights up, bringing so much to the forefront.

Here is Wikipedia's description of the learning rules for the Hopfield network: "There are different learning rules that can be used to store information in the memory of the Hopfield Network. It is desirable for a learning rule to have both of the following two properties:

Local: A learning rule is local if each weight is updated using the information available to neurons on either side of the connection that is associated with that particular weight.
Incremental: New patterns can be learned without using information from the old patterns that have also been used for training. That is, when a new pattern is used for training, the new values for the weights only depend on the old values and the new pattern."

In our skill graph (the map of how skills are connected to other skills, to jobs, roles, projects and people), we use a concept of complementary skills and associated skills. Associated skills are the skills you expect to find together in the same person (for example a line chef would have good knife skills and good grill skills). Complementary skills link areas that are more powerful when used together but are often held by different people (for example a person skilled in foraging for wild produce might provide ingredients to the line chef). It is possible to find patterns in these sets of relationships. Reading about the Hopfield network stimulated my memory just as the concept describes. "It is a neural model that has feedback connections. Its significance lies in the fact that it was able to bring together ideas from neurobiology and psychology and present a model of human memory, known as an associative memory."

There is another concept that Alexander writes about in his book. Brian Eno's Generative music. Here is an article I found on Wired.co.uk - Brian Eno on music that thinks for itself. Watch the video as it explains brilliantly the concept of building a musicscape with the elements that not only add sounds to the composition but respond to each other. Eno's concept came from an idea of creating an audio version of a moiré pattern. If it is possible to express what is basically a mathematical structure in audible form, can we use the same thinking and create a skillscape? Next, my associative memory kicked in again, and I realize that we already have Generative Design which takes the mathematical input and by mimicking nature's evolutionary approach creates a visual output - an image of a pattern. Or even better, Generative Art which adds another layer to the expression.

So, here is an idea. Is it possible to use a concept of a neural network to map the skill patterns and the strength of the relationship between them and them come up with an equation that captures those relations? The output could be represented in a visual skillscape or—why not—a soundscape unique to the skill composition! This way, every skill profile would list all the skills in a list format that will satisfy the more traditional HR departments, but as we would flip to the associative display, one can only imagine endless possibilities of what an exploration of a skillscape could do to our new experience addiction.

I will leave you with those ideas in the hope that your associative machinery will start generating many connections worth capturing using a skillscape output.