BRANDON J. WEICHERT | THE WEICHERT REPORT
Essentially, Yang observed that automation (artificial intelligence, machine learning, robots), were an unstoppable wave of the future. He believed that they would become a ubiquitous part of the American economy, thereby adding to the wage woes that many Americans are experiencing.
What’s more, there would be no viable solution other than for the U.S. government to basically give each citizen in the United States a stipend of $1,000 per month, no strings attached/no questions asked. It was actually an extreme form of a great Milton Friedman idea (the Negative Income Tax) that was meant as a compassionate way to both help lesser-fortunate American families survive economically tough times while still avoiding the pitfalls of creating an onerous cradle-to-grave welfare society.
Milton Friedman’s Negative Income Tax is best defined as:
Negative income tax (NIT) is an alternative to welfare suggested by, among other proponents, economist Milton Friedman in his 1962 book Capitalism and Freedom. NIT proponents assert that every American without income above the threshold for tax liability should have a basic income guarantee and that NIT is a means to subsidize the needy at less cost than the welfare system.
Whatever one’s opinion of Yang’s ideas, his key concern–that A.I. and the coming automation of almost everything in the United States was going to irrevocably destabilize and disrupt the lives of most Americans–is a legitimate problem, that will only become more prevalent as the new decade wears on.
By 2030, we may all be looking back at Yang’s unorthodox (and failed) presidential campaign as having been ahead-of-its-time on this key issue (though I still disagree that UBI is preferable to the Negative Income Tax).
Although, it’s important to also note that Yang’s assumption is the worst-case-scenario.
After all, while the move from horse-and-buggy to automobile certainly disrupted the lives of many, inevitably, the country adjusted to the paradigm and many more jobs and opportunities were created over the long-run (yes, I know, as John Maynard Keynes once said, “In the long-run we’ll all be dead,” but what does he know? He’s dead, after all!)
Let’s look at some harrowing data points here:
According to McKinsey Global Institute:
Between 40 million and 160 million women worldwide may need to transition between occupations by 2030, often into higher-skilled roles. Clerical work, done by secretaries, schedulers and bookkeepers, is an area especially susceptible to automation, and 72% of those jobs in advanced economies are held by women.
Then there’s Oxford Economics which posited this:
Up to 20 million manufacturing jobs worldwide will be lost to robots by 2030.
Back to McKinsey:
At the high end of the displacement by automation spectrum are 512 US counties, home to 20.3 million people, where more than 25% of workers could be displaced. The vast majority (429 counties) are rural areas in the Americana and distressed Americana segments. In contrast, urban areas with more diversified economies and workers with higher educational attainment, such as Washington, DC, and Durham, NC, might feel somewhat less severe effects from automation; just over 20% of their workforces are likely to be displaced.
As Forbes reported last summer, a recent Forrester survey of business leaders argued that, optimistically, job losses from the A.I.-automation revolution will be 29 percent by 2030 with only 13 percent new jobs being created as a result of the embrace of the A.I. revolution.
The Boston Consulting Group, meanwhile says:
67% of Chinese executives and 50% of US executives expect a reduction in the number of employees over the next 5 years due to advanced robotics (global survey of more than 1,300 executives and operations managers).
Things are looking grim for the ordinary American worker, eh?
Of course, that’s one way of looking at things–and we should be concerned.
This is why I appreciated Andrew Yang’s commitment being different. Because, M-A-T-H. Or something.
But, perhaps he overstated his case out of desperation in an election where issues about the future matter less than the bruised egos of Baby Boomer billionaires and envious socialists?
Automation and America’s Baby Bust
After all, the data sets I listed above do not take into account the ongoing Baby Bust the United States (and the rest of the world) is experiencing. For decades, native-born American fertility rates have been plummeting. To have what demographers refer to as “societal replacement,” the country needs a total fertility rate of 2.1 children per 1,000 women.
Without that number, as the title suggests, societies cannot rejuvenate themselves; unrecoverable ideas and practices are lost to history; and such societies are gravely susceptible to being subsumed by a much stronger and more virile culture.
We see this happening in Europe today with the massive amount of migration from the Greater Middle East. We also see it happening, to a lesser extent (though still grave), with the illegal immigration coming in from the United States’ southwestern border. And, it’s happening in the Russian Far East, as scores of Chinese immigrants move into unoccupied territories along the Sino-Russian border and basically occupy them.
Until recently, the United States was exactly at societal level.
Looking at longer trends, if there are not fundamental changes made at the macro-policy level, this decline will only continue.
It is also important to note that there are cleavages even within these numbers. For example, immigrants to the United States and people living in the needlessly maligned “Red States” have, on average, more children than their native-born or overhyped “Blue State” counterparts do.
Digging deeper into the data, though, as Mark Steyn has outlined in his excellent 2008 epic, America Alone: The End of the World As We Know It, the fertility rates of second-generation immigrants to the United States begin mirroring their native-born counterparts. By the third-generation, there is no real distinction.
So, for those who say “immigration will save us,” that is not necessarily the case.
Part of the reason for the decline in fertility, I believe (as does Steyn), is the culture. Modern culture, with its focus on “Me,” its abrogation of the divine (save for Mammon), and its cult of youthful indiscretion–particularly in postmodern Western societies–is atomizing in nature.
Postmodern culture today, therefore, stifles community-building, which is the very essence of the nation. If the postmodern, Liberal culture of today is the problem, then no amount of immigrants will keep fertility rates at–or above–societal replacement level for very long. What will be needed is real social policy changes along traditional and conservative lines–which will likely only happen, as the Great Contraction makes the previous century’s Liberal assumption impossible to maintain over the long-run.
Much of the rest of the developed world has been well below that threshold for decades. The developing world (including China, despite having a billion people living there), and the Middle Eastern countries (despite being awash in young, unemployed, and therefore angry young men), will also endure a severe contraction in fertility rates no later than the 2050s, if trends persist.
Ultimately, automation might become America’s only way of remaining not only competitive in the global economy but dominant as well.
Millennials Hate Manufacturing
According to a CFO Magazine report, 10,000 Baby Boomers retire each day in the United States, leaving six million jobs open every month. This trend will not only persist, but will become exacerbated, starting over the next few years.
So, the Baby Boomers, who have retained their grip on power and wealth far longer than any other previous generation that has reached maturity, is in the process of retiring en masse and pulling from already-strained social security coffers.
As the Boomers leave the workplace in large numbers, despite their best efforts to “make 60 the new 40,” they leave behind them a massive gap. Over the next decade, there will be more jobs available across-the-board than there will be young employees people to fill them all.
Millennials already outnumber Baby Boomers in the United States today. These trends will only persist over the next decade of historic instability. The data points presented above indicate that the Millennials and younger Zoomer cohort are actually well-suited to survive and prosper in the coming decade of disruption. More jobs will be available to them and there will be less competition from those above.
In fact, it is very possible (again, possible) for many Millennials to make up for the lost opportunities of their early adulthood due to the dislocations that the Great Recession and subsequent non-recovery caused. At that point, the only problem facing them would be resolving the student loan crisis (though, as higher education is one big bubble about to burst, this may sort itself out on its own very soon).
Meanwhile, the data points above highlight the fact that the 512 counties (home to 20.3 million people) in the United States most associated with agriculture and manufacturing will be hardest hit by the supposed A.I. automation apocalypse.
Although, it is important to understand that 22-27 percent of Baby Boomers compose the manufacturing industry. Boomer job participation rate is set to decline by half, starting in 2022, from 80 percent to 40 percent (it will only go down lower from there over the decade). Also, the popular image of manufacturing (that Mike Bloomberg apparently shares) of it being a low-skill or grubby job for high school dropouts is totally wrong.
As Brian Fortney, the global business manager for Training Services at DesignNews.com said recently:
The challenge for manufacturers in the US isn’t foreign manufacturing, it’s the high school guidance counselor. They don’t understand that manufacturing is high tech. The plants are not dark and dangerous.
A recent Deloitte study found that:
The U.S. public ranks manufacturing as vital to the domestic economy, yet only 30% of the same group would encourage their children to pursue manufacturing jobs. In the same research, Millennials rank manufacturing as their least preferred career destination.
So, if manufacturing is essential to the nation’s well-being, yet there is an unwillingness on the part of most Millennials and Zoomers to partake in that industry, automation will be a net positive. Judging from the data, it appears as though the Boomers are most involved in the manufacturing sector and that neither the Millennials nor Zoomers will replace them in any meaningful way.
Even if the necessary amount of Millennials and Zoomers did seek to replace the retiring Boomers, there are still insufficient numbers of people to fill all of the gaps–meaning automation would still be needed.
And, since manufacturing today is increasingly a high-tech endeavor, it would seem that automation might work in the benefit of both the Millennial and Zoomer future manufacturing workers. Besides, the automation craze of today is merely theoretical.
Scaling up any potential artificial intelligence unit is something that even the most optimistic proponents of the technology do not think will be possible until the 2030s.
By that point, many of the Boomers will not be working in any industry. In other words, those most vulnerable to the disruptions won’t be around to experience the dislocations.
Further, as the coronavirus and President Trump’s trade and immigration policies continue being enacted, there is a real chance that these industries could be reconstituted in some form under the new generation. And, since there aren’t enough people in the Millennial or Zoomer generations to replace all of the outgoing Boomers, automation may actually help rather than hinder the country’s development.
Agriculture and Automation
The data also underscores how the agricultural sector will be deeply affected by the disruptions of automation. It will be disrupted. Although, bear in mind, according to a 2016 Land-o-Lakes corporation study, only 8 percent of my fellow Millennials are engaged in the agriculture industry (despite having oh-so-many opinions about sustainable development).
By the way, the same study found that only 3 percent of Zoomers were interested in becoming farmers or working in the overall agricultural industry. And, since most analysts believe it “takes a minimum of 15 percent of the nation’s workforce to produce, process, and sell our nation’s food and fiber,” then automation just might be a welcome development over the long-run (just as automobiles did).
I know this might sound like common sense, but given the data presented above, I find it necessary to state clearly: manufacturing is how we build the stuff we need and want. If there is an insufficient investment in it, whether it be in the overall industry or the human capital needed to maintain it, then things get very ugly, very fast in this country–particularly as the much-ballyhooed global supply chain is exposed to increasingly unmanageable risk (think coronavirus and other unpredictable events with long-ranging implications).
Let me give you a shocking example of what happens when American manufacturing no longer works as it should. Presently, the United States and China are engaged in a quasi-war for global dominance. Whether you think an adversarial relationship with China is needed or wise is irrelevant right now, because it is a fact that we are in such a relationship.
Part of countering China’s threat is in the construction of new Virginia-class attack submarines. The concern is that, while the U.S. Navy enjoys overall sea superiority, in specific ways, the Chinese navy can threaten American and allied forces closer to their shores.
China’s submarine threat is especially dangerous for expensive U.S. warships that operate near Chinese maritime borders and contested territories in the South and East China Seas. One way of meeting that challenge is for the U.S. to build out its own attack submarine fleet to better defend its assets in the Indo-Pacific (but it will always be the “Asia-Pacific” to me!)
Unfortunately, the U.S. Navy was forced to downsize their initial order for the Block V Virginia-class submarines because U.S. shipyards could not manufacture the number of submarines the Navy needed in time. The Navy expected to have a large order completed by 2019. Alas, General Dynamics could not meet the demand. So, the Navy reduced its order to nine submarines with an option for another. Again, American manufacturers are uncertain if they can complete even this small order–especially as other submarines remain on backorder.
Here’s some context from my friends at The National Interest:
The Navy had been counting on a big order of Block V Virginias to help mitigate a steep decline in submarine force levels. In December 2016, the Navy announced it needed 66 attack boats to meet regional commanders’ needs. But the attack-sub force could decline to a low of 42 in 2028 as old Los Angeles and Ohio-class SSGNs boats, their nuclear reactors worn out, leave the fleet in large numbers.
This is the risk we run if the United States does not a) possess the indigenous capacity to manufacture that which it needs and b) if it does not have the human capital to actually build the things it needs, whether it be newfangled gizmos for the civilian economy or attack submarines to help ensure American military dominance over its most cunning enemies.
If we continue to follow the trends I outlined above in the manufacturing sector; as Millennials and Zoomers continue hating on manufacturing, automation will be required in the long-run.
Slowdown in Tech Sector Development
Whether it be President Trump’s inaugural declaration that he was the elixir to the “American carnage” that had gone on since the 1970s (his policies are most certainly the solutions we need, especially when compared to those who oppose him), or Yang’s assumption that automation would be here far sooner than we anticipated and that it was going to end everything for almost everyone (save for the corporatist managers), things might not be so apocalyptic in the end.
This is especially true as we note that high-tech innovation is slowing down.
Even Moore’s Law, the basis of our modern computer revolution, which says that the computing power of silicon-based computer chips doubles every 18 months, is reaching its limits (which is why the tech sector is starting to look into things like quantum computing and bio-computing).
Chips are becoming more expensive to produce and it is not necessarily economical any longer for chip makers to push development up to the next node.
For example, in 2018, the chipmaker GlobalFounderies, said that it was stopping the development of its proposed 7 nanometer (nm) node. It was simply too expensive and the results would not have been worth the investment.
We see this everywhere. Everything is slowing down. Whether we’re talking technology, trade, immigration, the Great Contraction is occurring.
This is the result of long-running trends.
What’s more, it is a necessary move to correcting grave imbalances that have been allowed to form both in the United States and throughout the world. As these contractions occur, it is often important to curb the wide-eyed expectations of some (particularly in the technology sector).
Frankly, I am increasingly convinced that, while A.I. will come, it will not happen overnight.
What’s more, it will require more computing power than is presently available. Sure, laboratories can develop prototypes. Elon Musk has insisted that artificial intelligence is a serious and existential threat to humanity.
Here is what he said in a conversation with Alibaba (and Chinese Communist Party stooge) founder, Jack Ma recently:
I think generally, people underestimate the capability of AI. They sort of think like, it’s a smart human. But it’s, it’s really much—it’s going to be much more than that. It’ll be much smarter than the smartest human. It’ll be like, can a chimpanzee really understand humans? Not really, you know. We just seem like strange aliens. They mostly just care about other chimpanzees. And this will be how it is more or less in relativity. In fact, if the difference is only that small, that would be amazing. Probably it’s much, much greater. So like, the biggest mistake that I see artificial intelligence researchers making is assuming that they’re intelligent. Yeah they’re not, compared to AI. And so like, a lot of them cannot imagine something smarter than themselves, but AI will be vastly smarter—vastly.
Musk might prove to be correct in the long-run. Although, given that influencers like Musk are sounding the warnings about this new technology, perhaps we just might be able to avoid the pitfalls without beating our computers apart with metal rods.
But, the question of scalability is a factor. Further, the matter of computing power remains a key issue. These are things that will inevitably be overcome, given the industry’s commitment to developing artificial intelligence.
They will take time, however. The more investment into artificial intelligence research, the more industry leaders will recognize they need greater cloud computing. The more they need greater cloud computing, the more they will realize existing computing power is insufficient to meet their needs. Quantum computing, bio-computing, these will become the new wave of investments. If either of these two technologies are developed fully the computing power of artificial intelligence becomes truly unbelievable.
But, can it be done in such order? I don’t know. With quantum and bio-computing, we are talking about entire new forms of computing that require entirely new areas of research, investment, and scale. It’s like going from the wheel to horse-pulled buggies. The changes require complete paradigm shifts that are only just now beginning.
Here’s a good ‘splainer of biocomputing:
Here’s one on quantum as well:
Essentially, there is no guarantee that the changes underway will happen as quickly as some believe or will be anywhere near as caustic as what the Andrew Yangs of the world are predicting. Therefore, the most extreme solutions to these potential problems–particularly those preferred by both Andrew Yang and the notorious socialist, Bernie Sanders–might be unnecessary at this point.
Look at these data points provided by Peter Cohan of Forbes:
- There are very few examples of high payoff artificial intelligence applications to date (of course, that is because the technology is still in its infancy. But Cohan, who is a computer expert who previously worked in the A.I. sector during its last heyday in the 1980s, insists that the current A.I. craze is as much of a craze today as it was in his time).
- Very few companies can afford or find good uses for artificial intelligence applications.
Here’s what Kartik Hosangar told Cohan about that second bullet point:
AI engineers are expensive — their total compensation packages can go into the millions of dollars. It does not seem likely that large companies with limited AI capabilities will be willing or able to attract and retain such talent.
Moreover, even if they could, at this point it is unclear how companies could implement AI applications that would enable them to earn a high return on their investment.
Hosanagar thinks that the cost of building AI applications will drop as they did for iPhone apps. As he said, “When the iPhone first came out, it cost $500,000 to $1 million to build an app — now the cost is $25,000 to $30,000. The costs of AI applications will drop — in part with help from open source technology.”
He also suggests that companies start small. “Companies should not try to build AI applications that will boost revenue or reduce costs right away. Instead they should set a goal in the first 12 to 24 months of increasing their organizational learning and expect to build high payoff AI applications over five years,” said Hosanagar.
The Case for High-Tech Regulation
There are things that can be done at the policy level to mitigate these changes. Here is where Musk offers some practical and timely advice to U.S. lawmakers:
American lawmakers should take a much keener interest in the technology sector than they have. As people trained in law and liberal arts-related fields, many U.S. lawmakers do not understand the world of technology or the development of high-technology. From the 1970s until today, Silicon Valley and the tech investor community have benefited disproportionately from Washington’s abject ignorance on technological development.
And, it is true, many ordinary Americans whose industries, communities, and lives have been irreparably disrupted by the rise of Big Tech over the decades could have been protected from the worst excesses of disruptive tech development through better public policy. Washington’s leaders should understand the mistakes made yesterday and work to prevent from making those same mistakes as the automation revolution intensifies.
Judging from the government’s response to the suspected 2016 Russian “hack” of the U.S. presidential election (I am referring to the use of Russian bots and other electronic influence operations, not the entirely fabricated Democrat lie that either President Trump or any of his inner circle were Russian agents), Washington has not learned the lessons of the need for greater regulation of the tech sector.
After all, the U.S. government was reportedly shocked–shocked–to learn that not only could the internet be weaponized against the Democratic Party in the 2016 presidential election, but that a country like Russia could sow as much chaos in that strategic domain during our already-contentious election as Moscow did!
Meanwhile, conservatives are learning firsthand the totalitarian tendencies of America’s mostly-neoliberal tech gurus, who routinely de-platform and shadow-ban effective conservative pundits. In fact, Google and other social media platforms have been accused of attempting to rig national elections using algorithms that favor the Democratic Party’s candidates over the Republicans (this is the basis of Robert Epstein’s work on Google and it was one of the reasons why Facebook CEO Mark Zuckerberg has been under such intensive congressional scrutiny since 2016).
It is only now that these events have occurred that lawmakers are even moderately interested in regulating and understanding how the free-for-all development of technology since the late 1960s has fundamentally changed our society.
When it comes to the next phase of massive technology development, automation and artificial intelligence, American leaders should be concerned about too much disruption. The last thing anyone should want is for the country to return to the stifling levels of inequality and hopelessness that so many Americans in the “Gilded Age” experienced.
Yet, that does seem to be where we might be headed. It’s certainly where people like Andrew Yang and Bernie Sanders believe we are going (Bernie believes we’re already there).
I’ve written before in defense of the so-called “Robber Barons” of the Industrial Age. This is not because I agreed with their mostly-shabby treatment of workers and people of lesser means. It is because I recognize that they stood upon a moment in history where no one had ever stood before.
Never before had so much change, wealth creation, and political upheaval occurred in such a short timeframe (until today, that is). The people back then honestly had no idea how to move forward, so they relied on the ways they knew: methods and ideas inherited from what was by that point the bygone era of America’s agrarian lifestyle and economy.
Today, American political and industry leaders have no excuse. We know what happens when there is a lack of regulation and we know what happens when corporations of a specific industry are given far too much freedom to develop their products and pursue profit.
Yes, new technologies are created and entirely new ways of thinking and living are created–but many, many innocent people who could otherwise thrive are being broken by the ceaseless waves of innovation being forced upon the markets in such ways that it totally disrupts any chance for stabilization and stasis.
The trends I outlined above all indicate that some degree of automation is not only going to happen, but given the collapsing demography, it will be required for the future of this country. There are, in fact, many opportunities awaiting young people in the coming age of automation. But, it is important that Americans comprehend the need for a comprehensive regulatory framework meant to both encourage innovation and investment into artificial intelligence while not sacrificing our humanity in the process.
At the same time, it is important that Americans not overreact and embrace the tyranny of socialism to better prepare for the coming automation craze. Andrew Yang properly identified a potential downside risk to artificial intelligence. Yet, as I’ve written before, his UBI is not necessarily the best solution. A better one would be to try Milton Friedman’s suggestion of a Negative Income Tax. This would have the same impact as simply giving Americans $1,000 per month while also discouraging dependence on (and therefore the expansion of) the already-overburdened welfare state.
Meanwhile, Bernie Sanders’ calls to nationalize everything under the sun will not only save us from the possible automation apocalypse, but it will also kill every other aspect of our society. Andrew Yang is right about the problem but wrong about the solution, but Bernie doesn’t care what the problem because his solution is always the same: socialism. And, that’s not a solution at all, as decades of history has proven.
The key here is a much more middle-ground approach. Steps must be taken to encourage artificial intelligence research and development, on an as-needed basis. At each turn, though, the government should ensure that the needs of workers are being met first. If a new innovation threatens to destroy the livelihoods of people who would not be able to find gainful employment elsewhere, the innovation process should be slowed and prolonged, in order to allow for those citizens to be self-sufficient as long as possible.