That's not to say that this is a new phenomenon. The entire point of the industrial revolution was that machinery and automation could make large swaths of production fast and predictable, which they could never be when they were in the hands of individual craftsmen. Automation gives you fast, cheap, and interchangeable parts without which most of the modern world couldn't exist. Still, it's a bit unnerving to think that there are people out there who will, if they do their jobs right, make your knowledge and skill set pointless.
Here's my version of what this idea looks like on paper.I think I'm on reasonably safe ground with this, although I don't have specific numbers to back it up. The placement of the borders is something of a guess, and the boundaries are more of a slow fade from one to the next, rather than neat divisions. But I think it illustrates the idea.
Let's start from the left, with the "Replaced By Automation" section. My assertion is that the simpler a task is, the fewer the number of people who will be attempting it without the help of automation. For example, way out there on the small part of the tail are things like "moving heavy objects long distances without using wheels." The automation is so pervasive that it almost never makes sense to avoid using it, and millions of potential workers are forced to look elsewhere because of it. Somewhere closer to the border might be something like farming, which has been successfully automated, but with relatively expensive machinery. In some areas of the world you'll still find a fair number of people doing those jobs without automation because they're deep enough in a local valley of the global currency exchange that it wouldn't make financial sense to use it.
Although it may seem tempting, I'm not including in this section things that are done without automation for aesthetic rather than financial reasons. For example, handmade jewelry and artisianal food production are both things that could easily be automated, yet products produced without automation are specifically sought out because there is an assumption of some extra value in the item which could not be duplicated through automation. Whether this is true or not -- and it probably varies on a case by case basis -- that perception of additional value is something that cannot be produced by an automated process, so these cases don't count here.
Next up we have the "Not Automated" section. This is where a large portion of jobs in first world nations reside, since wealthier societies will not have a cost reason to drift into the red. At the low end of the curve are relatively simple things like the service industry -- not technically challenging in the day-to-day requirements, but with enough need for flexibility and a human touch that we can't automate them yet.
Higher up in the blue we have jobs which use automation heavily, but whose purpose is still to produce or exchange goods. These fall in the "not automated" category because, while they use automation to produce their output, the oversight of the process has to come from a human. This could be something like complex machining processes in a car manufacturing plant, or something as seemingly monotonous as running a checkout system in a store. In both cases the process is largely run by machines, but at the same time adjustments and human input are almost constant.
The next section, shown in green, is the set of human effort that is being put toward adding automation for something that is currently not automated. These are the people who are trying to steal your job. You'll notice that this section is relatively small compared to the rest of the curve; although a lot of people use automation to do their work, most of them are using it to produce some definite product. The set of people actually creating automation is much smaller, but the relative sizes are deceptive -- if the graph, rather than showing time spent, was redrawn to show output per time spent, this section would probably compose 90% of the total area or more.
That's because the product of this effort makes large sections of the blue portion obsolete. Build a car, and the market needs one less car; build a system that automates assembling a car, and you need millions of fewer man hours over the following decade to satisfy all that demand. And not only that, but effort in this section tends to rely heavily on automation itself, which magnifies the effect by allowing the new automation to be created more quickly and with less human effort.
Finally, running into the upper end of the curve we have effort spent on things that can't be automated. This is basically another way of saying that this is the portion of the green section that just ends up not working. Things that may seem like a good idea at the start (or not -- some people spend time working on really weird stuff) but just end up stalling out, or not catching on. This category is where I'd place things like natural language programming, and other things which would be nice if they worked, but basically require omniscient self-aware computers first. They may even pay off one day, but for now these are the things that are just too complicated to automate. Not that this stops some people from trying.
The abstraction isn't complete. There's an entirely separate area of human creativity which lives way, way out to the right side of the curve in this diagram, so much so that it may not even belong on the same graph at all. This whole thing may also be a little misleading, in that any one person or job will probably touch multiple sections of the graph in quick succession, but the balance of hours spent on an individual level will probably look nothing like this curve, depending on the specific job. But if you take this as an aggregate of hours spent across an entire country, or even better, across the entire species, I think you'll find this maps pretty well.
There are several implications of this idea that I want to explore, but this is already longer than I intended, so they'll have to wait for the next post.
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