[kristianc]

I'm interested by the classification here.

Many backend jobs involve routine work from people who could be doing non-routine work if the CRUD routine job was automated. Within an industry or a profession it seems like there could be a mix of routine and non-routine work.

Similarly, how many people's jobs have changed from being routine jobs to non-routine jobs through either retraining or automation allowing them to take on higher order work? Again, doesn't say.

Also, interesting to note that the actual unemployment rate for routine congnitive, routine manual etc 2009 shock aside doesn't actually look anomalous compared to much of the last two decades of the graph is to be believed.

[netcan]

I think you've hit on the right point. I'm also always curious about how far these definitions can and should be pushed.

Talking in terms of "automation of routine tasks" sounds reasonably descriptive of how the spread of technology works. But, technology is a concept that is notoriously elusive in economics. That's because it's hard to clearly define in concrete terms useable in the context of economic theories, whether they're mathematical conceptual.

For example, we've always been imagining "robots" as tin humans that do stuff people where doing. You have science fiction movies, books and such being written right now with this imagery, just like the 1950s sci fi art, Jetsons. Just like the mechanical turk and automatons of the 1700s.

I think robots are a useful mental placeholder. "Technology will be doing task X." But in reality, technology is usually more like "tools." Imagine a mechanic in the future. Maybe the cars come in with better self diagnosis before he sees them. The parts he needs are already known so he has them ready ahead of time. An AR (or whatever) info delivery thingy tells him exactly how to install or remove parts. etc.

What you have is a more useful mechanic. As long as a mechanic is still involved, I think "tool" is a better description. If people are no longer involved, "robot" seems a bit better. Ahead of time, when you are trying to imagine where technology is going it is very hard to discern tools from robots. Is a lawnmwer a robot? Is a a self guiding scalpel a tool?

[chimeracoder]

> But, technology is a concept that is notoriously elusive in economics. That's because it's hard to clearly define in concrete terms useable in the context of economic theories, whether they're mathematical conceptual

That's not true. The word "technology" is quite precisely defined in economics, and the definition is generally agreed upon by economists. This definition does indeed lend itself to useful economic theories.

The challenge is that the economic term "technology" does not map 1-1 with the colloquial use of the word "technology", which leads to an abundance of confusion for people unaware of this distinction when they interpret economic analyses.

[spacehome]

> What you have is a more useful mechanic.

The endgame here is that I don't need a mechanic.

[netcan]

Yup, potentially. In that case what you have is a more useful car, or cloud transport service.

But endgame, where it's "robots" as we all imagine it is always a moving target. Mechanics weren't needed 200 years ago either. So far, we've needed new professions. Maybe that will end.

My point was just that automation is a fairly fuzzy way of explaining what is going in.

[jsprogrammer]

>An AR (or whatever) info delivery thingy tells him exactly how to install or remove parts. etc

Once you have exact replication steps, automation is easy.

[leereeves]

I was wondering about the classification too.

Is the distinction between routine and nonroutine manual occupations simply technical vs service?

> Nonroutine manual occupations, which include service occupations related to assisting or caring for others

> Routine manual, which include construction, transportation, production and repair occupations

For example, why is driving a truck considered more routine than being a nursing assistant or phlebotomist?

[petra]

>> Many backend jobs involve routine work from people who could be doing non-routine work if the CRUD routine job was automated

Interesting, could you please expand ?

[netcan]

I'm not the OP, but I think he means this:

A bookkeeper/accountant might be manually entering invoices into a system, emailing managers to approve payments and such. It takes 3 hours per day. This work is "routine" in the relevant sense (it can be automated) but our young, congenial and soon-to-be-replaced-by-robots accounts payable woman (her name's Lynne) also does and is capable of doing "non-routine" tasks. She can call up suppliers to negotiate payment terms, have lunch with the manager in the next office to clandestinely suss out some questionable expense charges, etc.

Calling Lynne a "routine worker" is kind of problematic. She does routine work because it needs doing. When that work disappears, she's not out of work by default. Generally when technology creates efficiencies, the unemployment rate does not just increase by the number of people that did that work yesterday. People who are capable of doing other useful things do those things, if it's useful to do more of those things. There's still a question of whether the economy can use up these newly available Lynne hours. Often it can.

What happens when some technology automates a lot of "routine" programming work? Programmers make more program(s).

[mapt]

"Generally when technology creates efficiencies, the unemployment rate does not just increase by the number of people that did that work yesterday"

Perhaps not, but it does increase. Because somebody else was calling suppliers and having lunch with the manager yesterday.

[ryandrake]

Not necessarily. As a stereotypical "knowledge worker" my current work activities can be classified very broadly into two buckets: 1. Low-value routine grunt work that I am required to do and 2. High-value non-routine work that is ultimate optional but the more of it I do the better results I get at my job. I try to spend at least 10-20% of my work time figuring out ways to automate more and more of bucket 1 so that I have more and more time to do bucket 2. There's an unending amount of bucket 2 work available for me to do should I have time for it (trust me).

And here's the magical thing! Once all of bucket 1 is automated, a lot of my bucket 2 tasks start becoming routine--patterns emerge and I can imagine ways to even chip away at them with automation, allowing me to do even more high-value work, in theory making me more valuable to my employer.

[paulryanrogers]

My guess is this varies widely depending upon the business. Some are more compatible with automation than others.

[netcan]

Dynamic effects are really hard to talk about deterministically. Generally speaking, technology is always creating efficiencies and unemployment usually ranges in a range, over the long term.

Some technology advances seem to reduce unemployment. When factories were doubling efficiency several times in an average career-span, employment in manufacturing kept going up and so did pay. This was a long period. It started with farmworkers (replaced by automation) urbanising to work in the rapidly advancing, high tech manufacturing sector. The factories kept automating more and more. Efficiency went up. During long periods labour got a good cut of these gains, salaries rose.

At other times and other technological events (including trade which is economically very similar to technology) unemployment went down in the sectors closely linked to the tech.

[hnal943]

That's an unfounded assumption. There's lots of work that goes undone because it's cost prohibitive. Technology in this case increased overall value because it allowed Lynne to do something that no one was doing before.

[mapt]

If it was cost-prohibitive yesterday, why isn't it still cost-prohibitive today?

Maybe it would be doable at a lower salary. Let's pay Lynne half as much as yesterday for this new job.

[hnal943]

Because technology gave us levarage, and lowered the cost. Lynne's pay is ultimately set by the market. Lower her pay and see if she leaves to make more somewhere else.