A high — tec version of “What have the Romans done for us?” I love it.
Many of the article on ‘data science’ I’ve read here have left me bemused by the blind faith the authors show in data science when big data has been responsible for so many embarrassing failures over the past few years, simply because the more data that’s fed into a computer and the more nebulous the query, the greater the likleyhood of the answer being way off target.
Those who call themselves ‘data scientists’ (programmers when I loaded my first programme from punched paper tape many years ago,) need to understand computers are great at handling specifics. Technology can do many things for us, but we should thing about the skills we need to posses in order to do those things and whether it is wise to risk losing those skills by not using them.
I’ve been called a dinosaur for ridiculing statements like, “In twenty years all cars will be autonomous and battery powered, nobody will drive themselves because technology will do it so much better.” Now I’m not against autonomous, electric powered cars in principle, I think they have a future in congested city driving conditions. But if I’m still driving in twenty years, when I’m 90, I will still be driving my 1974 Triumph TR6 — and if by then they have prised my cold, dead fingers off the steering wheel, I don’t think my daughter will give it up without a fight. There are just some things technology cannot improve on, like zooming along the byways of northern England in an open top car.
But the issue here for me is the term ‘data science.’ Given that ‘science’ has become one of the most overused and therefore meaningless words in the language, can’t we simply refer to data analysis or data processing? After all, gathering data, collating it and drawing conclusions from the various statistics it throws up isn’t really science unless we count the inflation of job titles a science.