Based on a 2013 report by Carl Benedikt Frey and Michael A. Osborne of Oxford University. Will Robots Take My Job shows you the probability that your job will taken by an AI or a Robot.
Thanks for the hunt @bentossell !
Just a few weeks ago, I joined the freelance.tv (thx @dannpetty) community slack where @dreamture reached out to see if I might be interested on working on a side project.
I've been involved in the bot scene for a while (👋 https://www.producthunt.com/post...), so Dimitar's idea to build a website to show how susceptible your job is to automation peeked my interest.
He had found the data in an report published in 2013, and we pulled in some additional data from the Bureau of Labor Statistics, and we had the basis of our website.
Dimitar did a great job of designing a clean but interesting interface, and I got to coding. We pulled the data into Algolia to make it easy to find the jobs.
I found the numbers interesting, and seeing how far things have come since 2013, I'm curious to see how automation will continue to move into the work place.
Hope you like it!
@mubashariqbal@bentossell@dannpetty@dreamture nice use of ONET data guys! We used onet data at my last startup to build a KSA map of all the jobs in the US. I like your use of the data set! Are you catching the data locally and using your own services or are you using ONETs API? Did you consider including the related job titles in the API call? The occupational titles seem too broad, if you add related job titles that brings your jobs up to around 85k different possible "street names" for jobs.
One thing could be better: When I click on "random", I get a page reload and need to go back to the homepage to get a new random job. A global random-button would be nice.
@souravray@dreamture I tried searching for "prostitute" it is missing in the DB. I can think of these creepy being from the AI Movie, what is the probability of that coming to pass?
Software developers, software engineers, and programmers are essentially the same profession yet the results are drastically different. What's your methodology for determining the numbers?
@kay0stheory The data was collected from a report titled "The Future of Employment: How susceptible are jobs to computerisation?”, published by Carl Benedikt Frey and Michael A. Osborne: http://www.oxfordmartin.ox.ac.uk...
We also aggregated additional data from the US Bureau of Labor Statistics, related to the number of jobs and salary.
@daspianist I mean why can't we use robots to model clothes? The robots could move to reflect body measurements or this could simply be about those apps that scan you and then recommend clothing for your body.
@carafnparrish I see your point. In the technical context of the word "model", I think a robot-model definitely makes sense. However, in the marketing campaign, Vogue spread context of "model" (which I believe is what "fashion model" was referencing), my personal opinion is that humans are still hard to replace - even down the road.
@daspianist I mean with enough aesthetic work will we even be able to tell the difference in a human model and what will basically be a "Real Doll" but in a fashion model version instead of a love doll version in a Vogue spread?
could you add a top 10 list somewhere for those of us who are too lazy to check multiple professions - say, a top 10 most prone to automation; or top 10 highest/lowest paying vs. propensity for automation; given you are using algolia, this kind of faceted view will be trivial for you to setup on the backend.
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