Sunday, August 20, 2017

A Different Class

In Stop Working & Start Thinking (which I also mentioned the other day)  Jack Cohen and Graham Medley want scientists to consider what science is and how they do it, as well as just getting on with it. To help explain this, they partition scientific answer-seeking like so:
  • observation
  • measurement
  • investigation
  • experiment

And that's interesting in and of itself.  But the authors have been round the block and so recognise that this categorisation is not absolute, and that sometimes it might not be clear where a particular activity sits, and that some activities probably sit in multiple categories at different times and even at the same time.

In science — and thinking, so this applies to you too, testers — generalisations are useful because they help us to frame hypotheses at relevant granularities. We’re all made up of atoms but a description of social deprivation in inner cities at an atomic level would unhelpfully obscure, for example, that higher-level concepts such as social class can be useful factors in such an analysis. Further, this can be true despite social class itself being a fluid notion.

But generalisations are problematic for scientists — and thinkers, which includes us testers. It’s easy to be lulled into a false sense of security when, for example, all known observations show one general thing (swans are white) but then a new observation doesn’t fit (it looks just like a swan, but it’s black). There’s a human tendency to want to avoid complicating a simple model, and so reject the data (that’s not a swan!) which doesn't improve the theory.

Scientists, Cohen and Medley say — and I'd add testers also — should retain a critical distance when classifying: what does it mean to be a black swan? Would, say, a white stripe under one wing affect this? Could there be shades of black? Could there be greys? What explanatory power does a given classification permit? What does it prevent?

Further, they add, involving tools in categorisation, or more generally in any measurement, requires another consideration:
... when measurement is automated, the final figure, the one you get from the machine, incorporates the prejudice of the designer, not yours!

Edit: I wrote another post from this book too: Quite the Reverse.  

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