Prepping for the 2nd Machine Age

Over a year ago I watched CGP Grey’s video “Humans Need Not Apply”, and its possible implications on my future have been on my mind ever since. It’s a scary little video that illustrates how machines will eventually replace us in the workplace. In the video, Grey explains:

You […] may look at the state of technology now and think it can’t possibly replace your job. But technology gets better, cheaper, and faster at a rate biology can’t match.

Just as the car was the beginning of the end for the horse so now does the car show us the shape of things to come. Self-driving cars aren’t the future: they’re here and they work.

Without thinking too far into the future, what I’m worrying about is the fact that low-skilled and white collar jobs are disappearing faster than they are being created. This is a trend that has started a few decades ago, and which will continue as artificial intelligence continues to make progress at the pace it currently is. In Andrew McAfee and Erik Brynjolfsson’s book, The Second Machine Age (2014), he shares a graph that illustrates that although Labor Productivity is soaring, the Median Family Income isn’t follow the trend as closely as it used to.

Where does this increased productivity come from? Machines, presumably. They are able to do more and more of the work that are typically done by humans. And while new jobs crop up as a result of new technologies, the median family income has nonetheless stagnated.

What we can expect in the near future

As the trend continues, we are bound to run into big problems. To take an extreme example, if nobody has money, then no one can afford the things machines produce. The economy grinds to a halt. To avoid this issue, one of the things governments are looking into is a Universal Basic Income: Everyone would be getting an income, enough for decent living conditions, regardless of whether you work or not. A utopia I personally look forward to.

However, while we wait for the government to save us all, I’ve been thinking about what I can do to protect my career in the meantime— Just in case things don’t go smoothly before we reach said utopia.

What I’m realizing is that even jobs that are difficult to automate will be affected by this trend. I’m predicting a kind of 2nd order effect as technology continues to progress…

1st Order Effect: Some jobs will become obsolete before others

With the advent of self-driving cars, I think we can see that the cabbing industry is about to get hit pretty hard. And then, what’s going to be automated next? It’s hard to tell for sure, but some researchers have ranked a comprehensive list of job titles, based on their likelihood of automation. Lucky for me, it looks like my job is among the least likely:

Find out about yours here: http://www.bbc.com/news/technology-34066941

However, I don’t think I’m out of the woods yet. As the first 35% of jobs become obsolete in the next 20 years, I don’t expect people to just stay idle as their jobs are being automated.

2nd Order Effect: People will start doing some of the work you’re doing

As long as there is no solution in place such as a Universal Basic Income, people will find a way to find economically viable work. And hopefully, they learn from what happened to them and they target jobs that are less likely to be automated in the near future. In other words, the less automatable your job is, the more attractive it will be as a new vocation.

Therefore just because my job isn’t at risk of being automated in the near future, it doesn’t mean that I’m not at risk of unemployment, or at the very least, a decrease in salary.

For example, I’m an engineer, but not all of the work I do require deep expertise and 4 years of university studies. If someone else acquires similar competences (e.g. you certainly can learn to code with online courses, practically for free) and is willing to be paid less in order to have an income at least, why should I keep my salary?

Instead, I can imagine that the job of an engineer will be redefined in order to essentially “outsource” some of the tasks to other more willing workers, as human labor gets cheaper. I can’t say any of this with certainty and I feel like I’m entering the realm of speculation at this point. So let’s move on to something more tangible.

What I am personally doing to protect my career

With those 1st and 2nd order effects in mind, I currently have a two-pronged approach. It’s not very sophisticated, but I think it’s a step in the right direction.

1. Learn to do valuable work that isn’t easy for others to replicate

The first is a principle that I think anyone in practically any field should strive to follow and should do so regardless of the effects of automation. If your work is easy for other humans to replicate, then the value that you are personally bringing to your company is limited. You can easily be replaced. Steer away from those types of jobs and find ways to make connections and to use your creativity. For more information on this, I strongly recommend Seth Godin’s book “Linchpin”.

The point that I’m making is that those efforts are all the more important as more and more humans will be competing for the diminishing number of jobs. I must constantly strive to work as a “linchpin” in order to stay valuable to the economy.

However, if I’m to improve my rare and valuable skills, it almost goes without saying that I should avoid skills that are at risk of being automated in the near future. So if you were to map all the valuable skills on a Venn diagram, you want to aim for that “Safe Zone”.

Hopefully we have Universal Basic Income before robots completely covers my circle of skills…

2. Learn to work well with intelligent machines

The second approach is more technical in nature. As the gap is widening between the rich and the poor, what I want to know is: Instead of finding myself on the less fortunate side of that gap, what can I do to benefit from this trend?

There are probably many answers to this, but personally to keep things simple I’d base myself on what Tyler Cowen believes will increasingly define the gap:

The key question will be: are you good at working with intelligent machines or not?

In other words, if you use machines to enhance your productivity, then it’s like a judo move where you use their strength against themselves. The better the machines, the more productive you become.

So what seems to be a sensible approach is to try and keep up with developments in artificial intelligence. Of all the emerging technologies out there that can redefine the way people work, I have to keep an eye on AI. There are a lot of things that can be done, requiring different time investments. Here are some ideas starting from the most proactive:

• For an engineer like me, it might involve enrolling in an online course on Machine Learning. Although I doubt that I’ll be among those who creates the AI itself, having an in-depth understanding of how it works should enable me to stay ahead of the game.
• For someone who isn’t familiar with coding, learning to code might be a good starting point which can open many doors. You could easily get started with a Python course on Codecademy, to at least understand the basics.
• If coding seems daunting, there are interesting side projects you can take on. I started with creating a simple chat bot and now I can better understand their strengths and weaknesses. API.ai and Wit.ai provide an interface where no programming is required.
• You don’t need to be the one creating the AI for your career to benefit from it. Going back to Cowen’s words, you need to be “good at working with intelligent machines”. So for example, I could look at the ways it can enhance my ability to express myself artistically, or how they can help me in sales or marketing, if any of those are relevant to my work. The idea is to be an early-adopter of work-related AI, so that decades from now I’ll be working in the new AI economy will be like a duck takes to water.
• At the minimum, whether you’d like to learn the “technical stuff” or not, simply regularly reading up on the subject will be useful. It can spark ideas for other side projects more relevant to one’s career. It can also help better understand in which ways AI poses a threat or can eventually be used as an asset in your career, and that comes in handy for the previously-mentioned approach (work that’s hard for AI to replicate).

From what I see around me, not many are proactively learning these kinds of skills. But I feel that at an individual level, one should avoid being “asleep at the wheel” (a phrase which will soon lose its meaning, come to think of it…) And as to whether Tyler Cowen is right about “the key question”, only time will tell. But personally I wouldn’t just wait and find out.