# Stand aside! I’m an expert

Actually, I am not an expert. However, I have frequently been introduced as one: “This is Colin Walls, our expert in embedded software / computers / C++ / photography / mind mapping / …”

I do not care about these introductions, as maybe the label is useful. But I am very suspicious of people who are self-proclaimed experts …

Over the years I have learned about many things – lots of different subjects. Some I have been taught; others I have studied by myself. Such learning may have been my formal education, professional training or just the pursuance of personal interests. Some things I have an aptitude for; I am good with words and numbers and I am told I take decent photos. Other things elude me; I cannot draw or play a musical instrument.

But there is one common factor about all of this learning: I observe that the more I learn about a subject, the more I am aware of how much more there is still to learn. When you start learning mathematics as a small child you are taught about addition, subtraction, multiplication and division – and you think that mastering these is all that is required. Of course, some people never achieve that, but most of us get there and start receiving hints about other aspects of mathematics: exponentiation, equations, geometry, calculus – the list goes on. I did enough mathematics to complete my [science] degree, but do not ask me about partial differentials or wave equations or …

An expert is someone who know a great deal about something. Maybe not everything there is to know, but darned close to that. Given that you are constantly and increasingly aware of your own knowledge shortcomings, how can you ever declare yourself to be an expert? By definition, anyone who says that they are an expert is not.

A colleague of mine commented that it would be good to have an equation to characterize expertise. I cannot figure one out – but would welcome suggestions. But my colleague has a PhD, so he must be an expert in something.

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Colin –

Regarding the last paragraph (an equation to characterize expertise) – the first thought that comes to mind is the graph of a capacitor charging (RC time constants & the like).

The X axis is the amount of knowledge acquired (time for RC), the Y axis is “expertise” (voltage for RC).

Initially you get a big surge, then as you learn more & more, you approach the “ultimate expert level” more & more slowly, very much like the smaller voltage changes on a capacitor as time constants go by.

In case I’m not explaining it well enough, this is what I have in mind:

http://en.wikipedia.org/wiki/File:Series_RC_capacitor_voltage.svg

Thanks for the input Dan. You are saying that one approaches being an expert asymptotically. However, I think that a different curve would make sense. As you learn more over time [curve moving up] you realize how much more there is to learn [curve moving up faster]. The gap between what you know and how much you realize that there is to know gets ever wider.