In a fascinating installment of the IEEE Techwise podcast [MP3], Rice University Computational Engineering prof Moshe Vardi discusses the possibility that robots will obviate human labor faster than new jobs are created, leaving us with no jobs. This needn't be a bad thing -- it might mean finally realizing the age of leisure we've been promised since the first glimmers of the industrial revolution -- but if market economies can't figure out how to equitably distribute the fruits of automation, it might end up with an even bigger, even more hopeless underclass.
I think the issue of machine intelligence and jobs deserves some serious discussion. I don’t know that we will reach a definite conclusion, and it’s not clear how easy it will be to agree on desired actions, but I think the topic is important enough that it deserves discussion. And right now I would say it’s mostly being discussed by economists, by labor economists. It has to also be discussed by the people that produce the technology, because one of the questions we could ask is, you know, there is a concept that, for example, that people have started talking about, which is that we are using, we are creating technology that has no friction, okay? Creating many things that are just too easy to do.
Many of these ideas came up in this Boing Boing post from January, which also touches on Race Against the Machine: How the Digital Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy, a book that Vardi mentions in his interview.
The Job Market of 2045
The Nightmare Machine is an MIT project to use machine learning image-processing to make imagery for Hallowe’en.
The Stormtrooper Decanter is on back-order, but you can pre-order one from the next batch for £22 — it’s based on Andrew Ainsworth’s original movie helmet moulds from 1976, and will provide endless opportunities to point to lowball glasses and say things like “aren’t you a little short for a Stormtrooper drink?” (via Bonnie Burton)
Yahoo has released a machine-learning model called open_nsfw that is designed to distinguish not-safe-for-work images from worksafe ones. By tweaking the model and combining it with places-CNN, MIT’s scene-recognition model, Gabriel Goh created a bunch of machine-generated scenes that score high for both models — things that aren’t porn, but look porny.
If you like to DIY and you like helicopters, you’re going to really love the Flexbot Hexacopter Kit. This copter blows traditional models out of the water: it includes everything you need to actually build your own hexacopter, and then pilot it like a pro, too.The construction is complicated enough to give you a challenge, […]
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