Searching for some intelligence
We’re pretty well in to the internet age. But how much do our perceptions, selection and judgement reflect that?
Is the smartest person you know the one with the deepest personal repository of knowledge? Or the one with the widest knowledge, armed with the tools and skills to find out anything?
Are there many pub trivia nights that arm patrons with the web to hunt down obscure clues or answers?
I’ve been thinking of this as I get stuck into my latest coding textbook, the Python Data Science Handbook. Early on author Jake VanderPlas writes:
When a technologically minded person is asked to help a friend, family member, or colleague with a computer problem, most of the time it’s less a matter of knowing the answer as much as knowing how to quickly find an unknown answer. In data science it’s the same: searchable web resources such as online documentation, mailing-list threads, and Stack Overflow answers contain a wealth of information, even (especially?) if it is a topic you’ve found yourself searching before. Being an effective practitioner of data science is less about memorizing the tool or command you should use for every possible situation, and more about learning to effectively find the information you don’t know, whether through a web search engine or another means.
Surely this goes for most things. Knowledge itself isn’t redundant, obviously. It’s experience, information and skills that inform how and where you search, and what for.
But, at the same time, it feels like we’re still living with an outdated perception of intelligence. Intelligence as a kind of isolated store of information that can’t be updated or augmented mid-problem.
I’m waiting to see a job ad that’s looking for a candidate that isn’t just qualified, but has skills to locate, store and retrieve appropriate information. Better yet, emphasises that.
As usual my emphasis