Deep Learning Is Going to Teach Us All the Lesson of Our Lives: Jobs Are for Machines
Curated from: medium.com
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Routine Work
- All work can be divided into four types: routine and nonroutine, cognitive and manual.
- Routine work is the same stuff day in and day out, while nonroutine work varies. Within these two varieties, is the work that requires mostly our brains (cognitive) and the work that requires mostly our bodies (manual).
- Where once all four types saw growth, the stuff that is routine stagnated back in 1990. This happened because routine labor is the easiest for technology to shoulder. Rules can be written for work that doesn’t change, and that work can be better handled by machines.
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Neural Networks
They’re a giant network of interconnected cells. Some of these connections are short, and some are long. Some cells are only connected to one other, and some are connected to many. Electrical signals then pass through these connections, at various rates, and subsequent neural firings happen in turn. The result amazingly is us, and what we’ve been learning about how we work, we’ve now begun applying to the way machines work.
One of these applications is the creation of deep neural networks - kind of like pared-down virtual brains.
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Big Data
Big data isn’t just some buzzword. It’s information, and when it comes to information, we’re creating more and more of it every day. In fact, we’re creating so much that a 2013 report by SINTEF estimated that 90% of all information in the world had been created in the prior two years.
This incredible rate of data creation is even doubling every 1.5 years thanks to the Internet.
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Deep Learning
The power of deep learning is that it’s a way of using massive amounts of data to get machines to operate more like we do without giving them explicit instructions.
Instead of describing “Chairness” to a computer, for example, we instead just plug it into the Internet and feed it millions of pictures of chairs. Next, we test it with even more images. Where it’s wrong, we correct it, which further improves its “Chairness” detection. Repetition of this process results in a computer that knows what a chair is when it sees it, for the most part as well as we can.
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Nonroutine Automation
We need to recognize what it means for exponential technological change to be entering the labor market space for nonroutine jobs for the first time ever. Machines that can learn mean nothing humans do as a job is uniquely safe anymore. From hamburgers to healthcare, machines can be created to successfully perform such tasks with no need or less need for humans, and at lower costs than humans.
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Decoupling Income From Work
The idea is to put machines to work for us, but empower ourselves to seek out the forms of remaining work we as humans find most valuable.
This paycheck would be granted to all citizens unconditionally, and its name is universal basic income.
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