Attention bias or Dunning-Kruger?

There is a lot of talk these days about the Dunning Kruger effect and cognitive biases in general like the fundamental attribution error or attention bias. While the Dunning-Kruger effect essentially describes the learners misinterpretation (notably: overestimation) of their level of competence after they have acquired the basics of a topic, it is often used for bashing people who seem to be over-confident without really knowing much about subject they are talking about. But does it always have to be just Dunning-Kruger? I don't think so.

A while ago, someone made a nice – or rather not so nice, but unfortunately very on point – joke about the incompetence of a company that wanted to hire a developer with "8+ Years of Swift experience" in 2018, pointing out that the programming language Swift came into life only three or four years before that.

Being annoyed with a lot of enterprise recruiting myself I answered with a picture of the Suzuki Swift car that was in production from 1983 onwards...

After some laughter we realized that we had fallen prey to some kind of bias, because actually Swift as a programming language is way older than Apple’s incarnation of it. There is a scripting language called Swift, targeted towards parallel processing in the high performance computing area) ... from 2007.

We obviously fell prey to cognitive bias, but I'm still struggling to find out which one.

But that was a good cue to pull out my favorite visualization cognitive biases that used to be part of the wikipedia article on cognitive biases, but now they have a really stunning list of cognitive biases.

The fascinating take away from this whole story for me was, that for days after I had toyed around with the infografic and the list, I caught myself repeatedly being more aware of potential cognitive bias pitfalls. It might not help against the Dunning-Kruger effect (or does it? I don't know, I'm not an expert in that area ;-) ), but it surely helped me with looking twice.

Or –as Alan Lokos might have said once– "Don't believe everything you think!" :-)

Cheers
  Michael Mahlberg