1. The Scenario
As you pull up to LaGuardia airport, you hop out of the Uber that transported you, along with two other Manhattanites who set across the table from you in the car, which was quite spacious in the absence of a driver.
You head to the Delta check-in desk, where a computer prompts you to look directly into the camera above the screen. After the facial recognition technology kicks in, a check mark pops up on the screen along with your SkyMiles rewards number and prompts you to put your checked bag on the conveyor belt. At the security checkpoint, you make your way to the TSA Pre-Check line, and after the 10-second full body and baggage scan, a green light appears to signal you are free to proceed.
Finally on the plane, you order an orange juice and a decaf coffee from the television on the seatback in front of you, and about thirty seconds later, the two drinks emerge on the armrest next to you. Just under an hour later, a robotic voice comes on over the intercom to update you on the local temperature in Boston and the updated arrival time of the autonomous Boeing 717.
As you are getting into the aisle to depart the plane, you motion to the family in the row behind you that they can go in front of you. On a Monday morning in a previous life, you may not have been as generous with your time, but hey, you don’t have anywhere to be today. You don’t have a job.
But then again, neither does anyone else.
2. The Issue
The accelerating rise of artificial intelligence, robotics, and other exponential technologies threatens to disrupt the workforce as we know it, with millions of jobs at risk of either partial or complete automation. The potential disruption could result in anything from, taking a conservative view, a drastic shift in the the makeup of the type of tasks humans perform in an economy and the associated skill sets that will be required from them, to at worst, a significant proportion of the global population being displaced by automation to the point of long-term mass unemployment across all industries and regions.
Some skeptics may rightfully point out that ill-founded stories of robot-induced mass unemployment have been threatened to be on the horizon for decades, from former US President Lyndon Johnson, who in the 1960’s warned of an impending “cybernation revolution” that would result in widespread unemployment, all the way back to John Maynard Keynes in the 1930’s who predicted an imminent “disease” of “technological unemployment” that would have a dramatic impact on the economy.
However, the current wave of automation is radically distinct from these previous eras, with exponential technologies having accelerated more in the last 5 years than they have in the last 50, leading to more and more companies starting to automate not only routinely programmable tasks, but also tasks that require complex cognitive capabilities that have until recently been assumed to require “uniquely human” skills.
A detailed study by Oxford University in 2013 suggested that 47% of jobs in the economy were at risk of being automated in the next 20 years, which was one of the first smoke alarms in recent years that seemed to convince some of the general public to start paying more attention to the issue. Since then, other leading research centers have conducted a number of additional analyses with varying methodologies that have predicted similarly worrisome results. In 2016, the World Economic Forum released findings that even when accounting for the jobs that would be newly created from exponential technologies, the net impact of automation in the 15 countries studied would be 5 million jobs lost by 2020. And in 2017, the McKinsey Global Institute conducted extensive research on the potential for automation and concluded that 50% of all activities in the global economy could be automated using technologies that are already in existence today.
With more and more data-driven studies supporting the validity of this impending shift in the workforce, and more and more companies providing real word case studies by beginning to automate certain parts of their labor force, there is an emerging consensus of the large impact that automation will have on the workforce. There are significantly divergent views, however, on what exactly that impact will be, what the implications of that impact are, and what society should do about it.
While influential figures such as Bill Gates, Elon Musk, and Stephen Hawkings (prior to his passing) have infamously leaned towards the more negative side of the spectrum of the doomsday-like risk that Artificial Intelligence poses (both in the workforce and more broadly in society), others have predicted a mere shift in the workforce that results in less unemployment and more “redeployment” (that is, many jobs will be lost, but many jobs will also be created, so a large number of people will have to pivot to new occupations).
Suggestions on what society should do about this impending impact have diverged even further from a consensus, ranging everywhere from implementing a robot tax, to numerous deviations of some form of universal basic income (UBI), to ultimately fusing human brains with artificial intelligence (if you can’t beat ‘em, join ‘em?)
Whatever the result of accelerated artificial intelligence, robots, and automation, large scale impact to the workforce is imminent. And among the numerous areas in society that will likely experience domino effects of dramatic changes when such a large scale impact to the workforce occurs, the education sector may be one of the most significant. The inherent objective of education in society, in its most simplified form, is to prepare students for the workforce. Thus, if the workforce itself transforms dramatically, the education sector may have to undertake a proportionally dramatic transformation to continue to deliver on its aforementioned objective.
This imminent challenge for the education sector may prove to be incredibly difficult, especially when considering the “Skills Gap” (that is, the disconnect between the skills required in the workforce and the the skills the education sector is equipping students with) in the United States and around the world has already increased dramatically in recent years, with substantially larger changes to the workforce still on the horizon.
3. The Blog
I’m starting this blog to follow an issue that I believe will be hugely important to the future of our economy, our livelihood, and society as we know it. I’ll aim for my analysis to be evidence-based when possible, but rather than dive into technical nuances of artificial intelligence, I’ll focus more on theorizing about the broader societal implications with a healthy dose of everyday layman speculation and conjecture.
While the blog’s title and opening scenario above are intentionally provocative, painting the picture of a Hollywood-ready storyline about the complete takeover of robots in the economy, the reality is that even if we were headed towards significant unemployment, there would likely be a substantial runway time period of adoption, which is why questions like educating for the workforce of the future would still remain relevant.
Fundamentally, the guiding questions of my blog will be:
- What impact will automation have on the workforce?
- How will the education sector need to adjust in response to that new workforce?
- What other implications will workforce automation have for society as a whole?
I’ll kick-off the blog by summarizing some past material that I believe is most important to a foundational understanding of the issues. From that point on, I’ll use the blog as a way to aggregate the latest research, analysis, and opinion on workforce automation and related issues, with a small dose of unsolicited commentary over the top — connecting dots, playing devil’s advocate, and posing further questions.
Though the original impetus to create a blog came from a personal desire to follow the issues around workforce automation and organize my own thoughts around its implications, my hope is that this can also be helpful to those who share similar interests and who might offer their own feedback, comments, and suggestions, as we as humanity face what I think will be the largest societal shift of our lifetime.