If you’re a white-collar worker (a person who makes a living translating the value of your intellectual property into wealth) as opposed to a manual laborer (a person who translates the value of their mechanical energy into wealth), get ready for a wild ride.
Remember the receptionist on the 15th floor who used to take excellent phone messages on those adorable pink pre-printed message pads? Her job predeceased yours by a few short Internet years.
The receptionist was replaced with voicemail, door buzzers and a few other disparate automated systems that were more efficient and materially reduced expenses.
Why bring up such an obvious piece of recent history? Well … as it turns out, your job may be the next – but you probably don’t see it coming. After all, you have domain expertise that machines could never match (at least, not in the near future), so your job is safe. Right?
The Answer Is Not Binary
Some jobs are more secure than others. It depends where your core competency sits on Ray Kurzweil’s “calculations per second per $1,000 of computer cost over time” curve. The end of your white-collar job is scheduled just past that point. And because of the exponential nature of this curve, it could be way sooner than you think.
But … how soon is soon?
At this moment, the rate of technological change is the slowest you will ever experience for the rest of your life. There is plenty of historical data to back up this statement; my favorite writing on the subject is Ray Kurzweil’s 2001 essay entitled “The Law of Accelerating Returns,” which begins,
An analysis of the history of technology shows that technological change is exponential, contrary to the common-sense ‘intuitive linear’ view. So we won’t experience 100 years of progress in the 21st century—it will be more like 20,000 years of progress (at today’s rate). The ‘returns,’ such as chip speed and cost-effectiveness, also increase exponentially. There’s even exponential growth in the rate of exponential growth. Within a few decades, machine intelligence will surpass human intelligence, leading to the Singularity—technological change so rapid and profound it represents a rupture in the fabric of human history.
Can You Think Exponentially?
If, in this particular pond, lily pads double every day, and if it will take 30 days for the pond to be completely covered with lily pads, what day is depicted in this photograph?
The pond is roughly half covered, so it’s day 29. Most of us would not have noticed the impending bio-disaster for the first 29 days. We’d just wake up on day 30 to a fully covered pond. Such is the nature of exponential change when observed by human beings. We’re just not wired to understand that tomorrow will be nothing like today – it looks the same. We wake up, the sun comes up, we eat breakfast and go to work, but all around us technological progress is accelerating at a fierce pace.
Man-Machine Partnerships First
If you move numbers from one cell in Excel to another for a living, or if you move markers on a Gantt chart to track production progress and manage projects, you’ve probably created some macros to help minimize the tediousness of your job. In practice, you’ve already created a man-machine partnership. If you’re great at it, you may be more productive than other people who compete with you. Efficient man-machine partnerships are “the” key component to modern productivity. If you’re better using your tools, you will almost always be better than your competition.
Interpretation and Analysis
While it’s tedious to move numbers from box to box, the reason you do it is so that you (or someone else) can analyze and interpret their meaning. This may be done with some automation, but people usually add human narrative that adds understandable causality to the data – for example: “We sold more of the blue widgets this season because the top quintile of two-headed Martians think they complement their green eyes.” Of course, you only need causality and human narrative if humans are needed to make the data actionable. If computers are going to make the data actionable, a human narrative is meaningless.
What You Can Do to Save Yourself
First, technological progress is neither good nor bad; it just is. There’s no point in worrying about it, and there is certainly no point trying to add some narrative about the “good ol’ days.” It won’t help anyone. The good news is that we know what’s coming. All we have to do is adapt.
Adapting to this change is going to require us to understand how man-machine partnerships are going to evolve. This is tricky, but not impossible. We know that machine learning is going to be used to automate many, if not most, low-level cognitive tasks. Our goal is to use our high-level cognitive ability to anticipate what parts of our work will be fully automated and what parts of our work will be so hard for machines to do that man-machine partnership is the most practical approach.
With that strategy, we can work on adapting our skills to become better than our peers at leveraging man-machine partnerships. We’ve always been tool-users; now we will become tool-partners.
Where Does This Ultimately Lead?
Uber drivers will ultimately be replaced by self-driving cars. You will press a button, the car will show up, and it will take you where you want to go. What will drivers do then? Hold on – that’s not going to happen for a hundred years! Maybe, but I’ve got some lily pads that beg to differ with you.