Last month we read Average Is Over [1] by Tyler Cowen. In this eye-opening book, renowned economist and bestselling author Tyler Cowen explains that high earners are taking ever more advantage of machine intelligence in data analysis and achieving ever-better results.
Meanwhile, low earners who haven’t committed to learning, to making the most of new technologies, have poor prospects. Nearly every business sector relies less and less on manual labor, and this fact is forever changing the world of work and wages. A steady, secure life somewhere in the middle—average—is over.
If you’d like to read the transcript, you may do so here [2].
Here are some of the highlights from this month’s review. First off, we start with a look at how technology trends (automation, outsourcing, and what I call, “clustering”) and how they will change your career path in the future.
How should you be planning your own personal development so that you can take advantage of these trends rather than have them take advantage of you?
This is a popular topic, it seems like every day you see a new opinion piece about robots taking all of our jobs… I think a lot of these pieces exaggerate the facts. Personally I think that although the advancements in deep learning and neural nets are impressive, I don’t think we’re on an imminent path and there’s going to be a level of artificial intelligence that can do all the jobs that humans can do.Â
But what you really want to be doing in your profession is pushing up the scale, because the further you push up the scale, the deeper your skill and competence is, the more you’re going to resist erosion from this middle vacuum of white collar easy to do jobs that will be taken over by machines or outsourced to other countries.
Next, I discuss Cowen’s different phases of machine and human relationships in the context of work:Â
He [Cowen] really maps out a transition path that he imagines we’re going to go through. This isn’t something we go through collectively, meaning that we’re entirely at one stage and then we’re entirely at another stage, but rather, individual industries and individual job positions are going to go through these stages and it may take a short amount of time, or it may have already happened for some… There are four stages in total.
The first is “man only” where there’s a human being who is working on a specific job. The next is the “human + machine” where the human is doing the bulk of the work but is using the software or the tools to facilitate the work.
The next is a “machine + human” combo where the machine is doing most of the work and the human being is there simply to monitor. To make sure it doesn’t go wrong, to fix common errors, etc. Finally, we have the machine only where now, there’s isn’t really much room for the human being to improve upon the machine’s results. The machine itself gives the best results possible.
So what does all this mean for your future?
For many industries and many types of jobs, these middle two phases where you see majority human being or majority machines but there’s still a team between these two elements, is the type of work is going to change.
In some ways, this is already the world we live in. This is a world where we’re all using software all the time to do our jobs. Many, many opportunities are coming because the person needs to understand how to use the software better. But I think that with a lot of innovations in machine learning and pattern recognition this is only going to continue and we’re going to have more and more sophisticated software programs that are going to require more and more sophisticated people to employ them.
Another piece of advice I would offer is learn to work with the algorithms instead of against them so you want to position your career so you are able to benefits from these trends by being something that you can add value to the technological landscape. This is something that is difficult to talk about in general — it’s going to matter and manifest a lot more in the specifics — but I think that deep understanding of how technology works and how to apply it is going to be incredibly valuable.
Will we all have to become programmers and engineers to ensure job security in the future?
One of the mistakes that Tyler Cowen notes that many people make is that they make the erroneous assumption that because innovations are coming from engineering, science, mathematics, technology, and so on, there’s many people who think “well maybe it’s the case that these are going to be all STEM jobs so the only thing we can do is teach everyone to become a programmer or an engineer” and what the author suggests here is that that’s not the case.
A lot of the professions that are going to come up are not going to be technical jobs. Instead it’s going to be using technology to do some job task that is not necessarily technical.
What this means that it’s important to understand the technology and be sophisticated in its use, but not necessarily that you have be the one making the technology.
Feel free to join in on our Facebook Group Discussion [3] I’d love to discuss this book with you there, thanks. December’s book is Godel, Escher, Bach: An Eternal Golden Braid [4] by Douglas Hofstadter.