Complementary skills and knowledge

Let’s take a simple illustration. Two of the most common technologies in schools are calculators and spreadsheets. Imagine we were interested in working out the time it will take us to travel from from Sydney to Canberra by car, travelling at an average speed of say 80 kph. We could calculate the time of this 283 KM journey using a calculator or a spreadsheet as a little over three and a half hours. The number that comes up in a calculator or in a spreadsheet cell is 3.5375. All of this seems straightforward. But in order for us to make use of the computation of division the machine has carried out, the machine requires us to have a working knowledge of units and how they work in a division. At a simpler level, we may have inadvertently punched in eight instead of eighty and obtained the answer 35.375. Now most people would realise that the time is absurd, relying upon the knowledge of other travel times. Or, if we had good approximation skills, we could say that three times eight is twenty four so we should get an answer that is somewhat more than three and less than four. These checking or error correcting skills we are describing we call complementary skills, the skills and/or knowledge that the machine delegates back to us in order for us to obtain a meaningful outcome.

To take a different example, a spell and grammar checker is a common feature of many word processing packages. When you spell and grammar check a document, algorithm is only capable of recognising familiar mistakes in grammar and unlikely to pick up an incorrect their for there, whether for weather and so on.

When we work with the digital, we are always getting the machine1 to do something for us. In both of these examples we are delegating some kind of work to a machine but for every delegation of work to a machine, there is a delegation back to the human user. Being aware of what we are delegating to a machine is a key aspect of contemporary academic practice.

There is much more to be said here. We live in a world in which algorithms do a great deal of work associated with day-to-day living. A great deal of human decision making has been delegated to machines and the prospect for a good deal more of that occurring is high2.

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