The Collapse of the Human Labor Force

Artificial-Intelligence-no-jobs-for-humans-Eanfar.orgThe Job Apocalypse. It’s difficult to understand and appreciate why the U.S. and global economies are in so much trouble today without understanding the truth about the unemployment rate and why automation and Artificial Intelligence are rapidly gobbling up nearly all human jobs. Despite the high-spun propaganda emanating from Washington, Wall Street, and Silicon Valley, this is an accelerating trend that is already leading to a Malthusian nightmare. For those who have not read my book yet, this article should give you some interesting thoughts to consider until you read the book.

The Future of the Human Labor Force. I recommend these two brief videos as a starting point:

After watching those two videos, it should be clear that there is no technical or logical way for the U.S. and global economies to magically offset the number of human jobs that Artificial Intelligence and automation are devouring. This is why the real unemployment rate today is actually over 22% and it will continue rising to 50-75% within your lifetime (assuming you were born after 1955).

If You Can’t Find a Job for 52 Weeks, You Don’t Exist. In 1994, immediately after NAFTA was implemented, the U.S. Bureau of Labor Statistics (“BLS”) arbitrarily stopped counting “long-term discouraged workers” in the official unemployment rate. The BLS’ rationale is that if you haven’t found a job in 52 weeks, then you must not be trying to find work anymore and you should not be counted. And if you work part-time babysitting or mowing a lawn for even a fraction of one day during any 30-day period, the BLS counts you as “employed” and excludes you from the unemployment rate. That logic might work in the minds of politicians trying to make the unemployment rate appear lower after the job-killing NAFTA was passed, but there is no intellectually honest reason to exclude over 50 million unemployed, able-bodied Americans from the official unemployment rate today.1

Jack Welch & “Bullshit Labor Statistics”. Let’s take the BLS’ abject logic to its logical conclusion: If every human is replaced with robots tomorrow and can’t find a job for 52 weeks, the unemployment rate would fall to zero. The absurdity of the BLS’ unemployment rate methodology is why Jack Welch, the former CEO of General Electric, said the way politicians calculate the unemployment rate today is blatant government manipulation. In fact, it’s so blatantly deceitful that it discredits everything that comes out of the BLS, which is why many otherwise intelligent and thoughtful people around the world today can’t help thinking that “BLS” means “Bullshit Labor Statistics.”BLS-labor-statistics-Eanfar.org

The Ongoing, Systemic Lie. According to the BLS, the unemployment rate is only 4.3% (as of mid-2017) and has been allegedly falling for nearly a decade. This data from the BLS is a blatant, ongoing, systemic lie intended to conceal the real condition of the U.S. economy. Sadly, I still see many people citing BLS data to celebrate the fictitious economic recovery and massive equities and bond market bubbles. Anybody who understands how the BLS calculates the unemployment rate knows that the official U3 unemployment rate dramatically overstates the health of the labor force, which has obviously been done for political reasons by both dominant political parties since NAFTA was passed in 1994.

The Real Unemployment Rate: Approximately 23%. The unemployment rate during the Great Depression in 1933 peaked at 24.9%. When calculating the unemployment rate today using the same methodology used prior to 1994, the U.S. unemployment rate in mid-2017 is about 23%, which is very close to the Great Depression unemployment rate. For the victims of Broken Capitalism today—including nearly 25% of the unemployed and under-employed American labor force and over 90% of Americans who have no retirement savings and are drowning in debt just to survive—a Depression-level unemployment rate is not surprising.

Deceptive Labor Force Participation Rate Trends. Prior to the 1980s, 50-80% fewer women (depending on the year) were in the U.S. labor force because American households only needed one bread-winner to enjoy a high quality of life during the post-WWII economic boom. That logically means the data associated with women during those years should be adjusted to reflect their participation in the labor force relative to the much smaller population of women that were actually seeking jobs, but BLS’ labor statistics include all working-age women without regard for their actual numbers in the pre-1980s labor force. This results in official charts like the one below, which portray a grossly distorted picture of reality because it makes it seem like today’s labor force participation rate is higher than it was prior to the 1980s. This is another statistical lie.

official-labor-force-participation-rate-Eanfar.org

Contrasting Today’s Rate with the Pre-1980s Rate. Comparing the labor force participation rate prior to the 1980s with the rate today without adjusting for the actual female job-seeking population is like comparing apples to giraffes. The politicians who control the content of BLS reports have self-serving incentives to present the data without explaining the impact of this obvious flaw in their methodology. If women were counted in proportion to the size of the actual job-seeking female population prior to the 1980s, the historical labor force participation rate back then would be approximately 40-50% higher than the rate you see in the chart above. That would provide a much more accurate contrast against more recent trends, which would highlight why the collapsing labor force participation rate today is so alarming.

actual-historical-labor-force-participation-rate-Eanfar.org

Today: More Debt, More Job-Seekers, but Fewer Jobs. In contrast to the American labor force prior to the 1980s, today, men and woman (in nearly equal proportion) desperately want/need to work just to survive. Even with two people working in a household, a comfortable modern lifestyle in the U.S. today is only possible by going into debt for over 90% of the American population. In fact, Americans are now in more debt today than they were before the financial crisis. This is one of the consequences caused by what I define in the book as “Broken Capitalism”.

Responding to Defenders of Systemic Fraud. I see many so-called experts in the mainstream media today parroting these official BLS stats like un-thinking zombies, which magnifies the confusion for the general public. Worse, these so-called experts attack anybody who questions the official BLS reports with asinine straw-man arguments like, “So, you really think Trump/Obama/Bush/Clinton personally called the BLS and told them to cook the numbers just before an election?” No, that’s not how this fraud is perpetrated. It’s a systemic fraud based on the deliberately deceptive formula that the BLS has been using to calculate the “headline” unemployment rate since NAFTA was passed in 1994. And the fraud continues because U.S. politicians have distorted incentives to perpetuate the delusions embedded within the neoliberal economic policies that are destroying Capitalism and driving the global economy off a cliff.

Propaganda Distorts Human Perception. Without a strong foundation of accurate, nonpartisan data and truth, it’s impossible for any human to develop an accurate perception of reality. Having an accurate understanding of the true health of a country’s labor force is the foundation of all good economic policymaking. This is more critical today than ever before as automation and Artificial Intelligence are knocking on every human’s office door. Regardless of their intentions, when politicians collude with corporate interests and the media to perpetuate economic frauds and fantasies, they conceal their economic ignorance and policymaking negligence, which prevents citizens from holding them accountable for their destructive policies.

If you want to learn more about the socioeconomic and political consequences of Artificial Intelligence and what is destroying Capitalism worldwide today and how to fix it, please read Broken Capitalism: This Is How We Fix It.


Notes:

1. The BLS indicates that approximately 35% of the entire U.S. adult population “do not want a job now,” which is how they justify excluding over 90 million adults from their definition of the “Civilian Labor Force.” However, in their footnotes, they state, “Includes some persons who are not asked if they want a job,” which means they arbitrarily assume that approximately 90 million adults don’t want jobs. Of course, that’s an absurd assumption and ignores many economic policy factors that discourage millions of Americans from working. So, my definition of the “Civilian Labor Force” reasonably counts a significant portion of those 90 million erased humans, including significant subsets of the long-term discouraged/displaced population, college student population, over-age-65 population, non-severe disabled population, all of which are able to perform many jobs.

More specifically, discouraged/displaced humans don’t magically disappear in real life; so they should be counted. Many students would prefer to earn additional income to reduce their asphyxiating student loan debt if there were available low-skill jobs. Many healthy people over the age of 65 need to work because their retirement savings and benefits are insufficient to sustain a comfortable retirement, but they can’t find jobs. And a majority of the officially disabled population are not severely disabled; thus, they would be able to work if jobs were readily available to them.



About Ferris Eanfar

Ferris Eanfar has over 20 years of experience in technical, financial, media, and government intelligence environments. He has written dozens of articles and several books in the field of International Political Economy, including Broken Capitalism: This Is How We Fix It, which provides unique insight into what is wrong with the global economy and how to fix it. To learn more about Ferris, please visit the About Ferris page.

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