From Economics to Trekonomics, 300 Years Early

I have always been an avid student of history and economics. And through many twists of circumstances I have found myself teaching these subjects to several million students every year. In these lessons, we learn how civilizations wax and wane due to economic, cultural and political forces; how technological revolutions like the advent of agriculture, writing, mass printing, and industrial know-how have transformed humanity. And we are in just one of those times right now, where technology is making us rethink the nature of human purpose, potential and opportunity.
That is why I find Star Trek to be fascinating from a labor economics perspective. In that television series, automation has freed everyone on Earth in the 23rd and 24th century from the need to be a laborer. Instead, everyone is some combination of explorer, researcher, or artist. Humanity has been liberated by technology to find real meaning and purpose in life. That sounds great!
So shouldn’t we be excited that the technological underpinnings of the Star Trek universe seem to be happening much faster than Gene Roddenberry expected when he created the series in 1966? Alexa or Siri can already handle most of the tasks that the early U.S.S. Enterprise ship computer seemed capable of. True 24th century Star Trek- level artificial intelligence may be 30, not 300, years away. Low-cost smartphones are already far more powerful than Spock’s tricorder. Behind the scenes, automation and artificial intelligence are beginning to transform marketing, manufacturing and distribution in nearly every industry.
But there seems to be a disconnect between our accelerating technologically-driven productivity that, in theory, should be getting us closer to the world that Star Trek promised, and where we actually seem to be headed, based on trends of the last several decades. While Earth in Star Trek seems like an egalitarian utopia, wealth inequality in our country has been trending up since the early 80s and is currently at a level not seen in roughly a 100 years. In 1978, the top 0.1% had 7% of the wealth in the United States. Today, the top 0.1% have over 20%. And this trend — fueled by globalization, tax policy and early new, tech-enabled business models — has happened before the really profound automation has had a chance to kick in.
How did we get here?
Globalization, for starters, has allowed everything from clothing to appliances to become cheaper for the American consumer on an inflation-adjusted basis. But it has also lowered demand for low and mid-skilled labor in our country by shifting production to lower cost countries. Another likely factor is the almost four decades of investment-friendly fiscal and monetary policies.
Technology has also begun to play a role, with new tech-enabled business models like e-commerce or ride sharing. These innovators haven’t replaced jobs with robots en masse just yet, but they have generated an incredible amount of new value through transformative business models that have improved most of our lives. A big chunk of that value goes to consumers, but the fraction that accrues to a relatively concentrated set of entrepreneurs, investors and tech employees still disproportionately contributes to the wealth of the top percentiles.
And automation is just getting started which is likely to make life a lot more convenient and efficient for a lot of us. But if we’re not careful and proactive, the technology Star Trek foretold would not match the society it envisioned resulting from these advancements. In fact it is likely to accelerate wealth inequality and be extremely disruptive to labor markets. After all, in the next 20 years, it is likely that automation will take over everything from driving, to grocery checkout lines, to reading x-rays.

So what can we do?
One option is to do nothing and hope that new jobs that we can’t quite imagine yet get created. But hope is not a plan. If those jobs don’t get created, what happens to the 4 million American ride-sharing and truck drivers? Or the 4 million Americans who work in retail? And even if many new jobs do get created, will the displaced have the necessary skills for those jobs? The fear that technology will replace human jobs is not a new one; it existed even before the Industrial Revolution. But artificial intelligence and robotics will go much, much deeper in the ability to do work that has traditionally been viewed as the domain of the human hand and mind than anything we’ve seen before.
And millions of displaced workers who will not be able to support themselves or their family will want solutions. Some will blame the rich and corporations. Others will blame immigrants or minorities or the intellectual elite. Most will lose faith in our political and economic system. Those not disrupted will enjoy their cheap transportation and merchandise, but will likely spend more on gates, barbed wire and security as the protests and marches and anger gets more and more uncomfortable. History has not been kind to nations with large angry populations that have little to lose.

A second option is some type of accelerated wealth redistribution — increased taxes on the wealthy to support those out of work. But if the job displacement is on the scale of tens of millions of people, the taxes needed to meaningfully support so many people would have to be significant and not just be on the wealthy. And if the taxation becomes extreme, capital and jobs are likely to move to lower taxation countries, which would only accelerate the job losses in the United States.
But even if the redistribution — say through a universal basic income — were perfectly implemented with no unforeseen negative economic consequences, on its own, it would still miss a bigger point — it deprives a large number of people of purpose and squanders most of the incredible energy and creativity that we collectively have. For many in that scenario, this would be more like the reality of Pixar’s Wall-E — in which human beings drift purposelessly through life in all-you-can-eat, all-you-can-watch stupors minded by their robot servants — versus the utopian Earth of Star Trek.

This brings us to the third option — educate our way out of the problem. The Industrial Revolution labor needed a lot of low and medium skilled labor at the bottom of the labor pyramid. It also needed a large number of bureaucrats to process information in the middle tier. At the top of the pyramid, there was a small number of entrepreneurs, investors, researchers and other types of knowledge workers. And this pyramid roughly describes the breakdown of the labor force even today. If automation and AI disrupt the bottom two layers, why can’t we invert the pyramid through education and allow most people to participate at the top? This leads us to wonder whether there is a way to give most people the skills that we today associate with the most-skilled 5%.
The solution, I believe, is to revisit old ideas, impractical and prohibitively expensive a generation ago, but, now pragmatic and scalable because of the very technology that is driving all this rapid change.
In 1984, the education researcher Benjamin Bloom published his famous “Two Sigma” study. He showed that if students were provided with a personal tutor that flexed to the individual pace and needs of the student and worked with the student until they mastered concepts, students would improve by two standard deviations. In plain English, that means that an “average” student could be accelerated to perform like the top 5%; the same top 5% many associate today as being capable of being a member of the creative class in Star Trek. And over 250 studies on mastery learning since then have reached similarly positive conclusions. In theory, if we could apply this technique to all 57 million k-12 students in America, within a generation we could have the 10x Star Trek workforce we need.
So why haven’t we done it? The simple answer is cost. A personal tutor for every child in every subject would require 10–30 times the resources that we currently spend in education and would eat up most of our GDP.
But the inflection point we are entering allows for the creation of software-based tools that permit educators to get a lot closer to Benjamin Bloom’s ideals than would have seemed possible a generation ago. These tools — which I and many others are devoting our energies to — can be universally accessible and flex to the individual needs of every student. They can inform teachers when and where appropriate interventions are most valuable. And the data is compelling. Using the SAT as an example, in a study of 250,000 test takers, even just 20 hours of practice in a mastery framework over an 18 month time period — a little more than an hour a month — was associated with doubling the expected gains from the PSAT to the SAT. Millions of American kids are already starting to engage this way, but to navigate the inflection point, we need a concerted partnership between non-profits, philanthropy, industry and government to reach all 57 million students in America.
And if you are still skeptical that a majority of people are capable of contributing to the frontiers of art, science or industry, think about where global literacy was 1000 years ago. Back then, less than 20% of the world population could read and the few literate folks — like members of the clergy — would have probably thought that, even with a great education system, maybe 30 or 40% are even capable of reading. Nineteenth century mass public education — which was a bold idea of the time — changed that and showed that pretty close to 100% of the population could read. What I am suggesting is an analogous step-change that leverages online learning tools for teachers and students and allows nearly everyone to be a 21st century knowledge worker. Closely tied to this would be new global credentials so that anyone can show they have these higher order capabilities.
What about demand for these knowledge workers? Even at this early stage of this automation revolution, the Amazons, Googles and Microsofts of the world can’t get enough employees with these top-of-the-pyramid skills. And the demand will only accelerate as more discoveries and productivity drives more and more opportunity for investment and innovation.
There is also place for the government to even further stimulate demand for these types of skills by investing even more in research and development. Think about the economic dividends that we are continuing to reap from the Cold War investment in ARPANET, which has now evolved into the Internet. And most of the advances in medicine and computing over the last 100 years all started with government investment in basic research. And the jobs that this type of investment creates — researcher, explorer, engineer, and designer — are the exact Star Trek jobs that can’t be automated for a long time. Rather than wealth redistribution, this would be wealth re-investment that would only accelerate entrepreneurship and innovation.

So we know that the age of automation and artificial intelligence is upon us. It will be full of opportunity and also be disruptive on many, many levels. It will force us to ask tough questions about society and an individual’s purpose in it. As we navigate this new paradigm, we have only a handful of options. The first option is that we can do nothing and hope. This risks leaving millions without the possibility of enjoying the fruits of this new age which would likely lead to social instability. The second option is more and more aggressive wealth redistribution which constructs negative incentives and economic distortions and could leave many Americans without purpose. Or we can take the third option and — adapting Captain Kirk’s famous words — go boldly where no society has gone before. By reinvesting some the fruits of innovation into even more innovation and inverting the labor pyramid, we will innovate, create, and cure 10 times faster than ever before. This would put us on track to be in a Star Trek reality not in the 23rd or 24th century, but in this one. Our nation has the option to truly live long and prosper. As far as I am concerned, this is the only option.

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