We ran a quiz last week about AI. There were seven questions about AI, algorithms and their application and you can take it here. You get a score out of 20 at the end. Of the 160 respondents so far, the average score is 10.1.
The most popular answer was the correct answer for all the questions but one. That one was about algorithms:
The correct answer is ‘deep learning’ but less than a quarter got this right. By far the most popular answer was ‘algorithms’. Of course, learning professionals will be quick to point out, multiple choice questions are far from perfect. Still, I think the results suggest that some education on algorithms and its surrounding concepts would be helpful for the public and the learning community.
Rather than regurgitate one of the many articles (here’s a nice, simple one) / diagrams / definitions you can find yourself online, I’d rather give a different perspective; to present the concept of algorithms relative to some others, both narrower and broader:
I’ve tried to precisely prescribe definitions and concept spaces to terms that are mostly not all that well defined (see Wikipedia’s page on Technology for a fascinating, self-indulgent discussion of what it means eg “the pursuit of life by means other than life”).
Still, I hope the diagram above is instructive.
You’ll see that algorithms encompass a lot here, almost everything. That’s because they are simply rules, stitched together to get you from some inputs to some outputs. They can be computerised (eg Facebook’s algorithms) or not (cooking instructions), which is why software sits inside algorithms. Josh Bersin recently (precisely here) said he wished we didn’t call it AI, that we “just called it more intelligent software”, neatly explaining why AI is a subset of software.
Hope more than 22% would get this question right now.
