If you keep up with the latest jobs-of-the-future news like I do it has been hard to miss the breathless commentary around AI and how many jobs it will soon eliminate. But before we all become preppers and await the Skynet apocalypse let’s take a step back and realize this is nothing new.
We commonly hear that Machine Learning is an emerging tech field as if it has sprung whole-cloth overnight. But the truth is that it has been slowly creeping up in plain sight for over a half century.
- Logistic regression — 1958
- Hidden Markov Model — 1960
- Support Vector Machine — 1963
- k-nearest neighbors — 1967
- Artificial Neural Networks — 1975
- Decision tree — 1986
- Q-learning — 1989
- Random forest — 1995
For many in the press the logic seems to be something along the lines of “if the general job-seeking public didn’t care about something important their whole lives, but care now, then it has to be emerging.”
Machine learning computer systems, which have a long and storied history are getting better all the time. And yes, they are poised to transform the economy just like steam engines or electricity did in the Victorian era. But while they can outperform humans in many tasks, they are unlikely to replace people in all jobs. We need to evolve along with our technology, just as we have always done.
So how do we do that? By making a long-term commitment to learning and skill diversification. AI is probably going to create as many opportunities as it will eliminate, at least in the foreseeable future. Our job is to keep apace with the changing workplace dynamic, and the best way to do that is an emphasis on development.
Companies are starting to realize this and are putting money and resources into play. One examples is Amazon’s Career Choice program, which encourages employees to learn skills for future employment. There are also more general online learning centers like Coursera, Codeacademy, Big Data University and Microsoft’s edX.
While each of these is still a work in progress, they do point the way forward. Education can no longer stop at 22 with the achievement of a diploma from a 4-year college. It needs to be a life long pursuit.
Luckily, there is an easy way to stay current on the latest trends and even get a bit ahead of the curve. And it doesn’t have to become like going to college all over again. Reading within your discipline can be easy and painless if you can just have a little discipline around the idea.
The average person can read about 15 pages in 20 minutes. That means if you just read 20 minutes a day, 5 days a week, you could read an typical 350 page book in just 28 days. In other words it would not be too difficult to make your way through a “work book” every month. All you have to do is find 20 minutes a day and you can be prepared for whatever the machines have coming our way.
But just in case the robot apocalypse really does happen, this should cover it.
This post first appeared in rough form on my newsletter, Career in the Balance. If you want to see me think out loud about the future of work and what it could mean for your career, you can subscribe here.