Silicon Collar tackles many policy issues around automation and impact on jobs, but the best part is the first half where I profile over 50 settings where man and machine are working as peers. Here are some I have been excerpting on New Florence:
Harper Lee published her Pulitzer Prize winning book, To Kill a Mockingbird in 1960. A couple of years later, Gregory Peck won an Academy for Best Actor in his role as Atticus in the movie adaptation. Quite a remarkable book.
What many do not realize is Lee was given a grant by friends to take off work for a year and concentrate on writing the book. Her story has fired the imagination of many who would like all of us to find similar friends and get a similar grant. Imagine what wonderful things we could produce. They call it a Universal Basic Income and our angel would be the government. We would all get an amount irrespective of our work status. Not a one time gift, an annual one.
No matter that Lee was a unicorn as authors go, and few of us will have such success or that we should all strive to find a similar angel in our personal networks, not expect it from the government, but the idea is getting wide play. President Barack Obama in a recent interview with Wired talked about it. Ok, so as a lame duck President he will not get too far with it, but the Swiss already held a referendum about it earlier this year (it lost but is expected to come up for consideration again in a couple of years), and several governments around the world are debating it.
I have several questions about the concept before we rush off and commit much time and money
Why are we panicking over sensational analysis of job losses?
Two Oxford researchers think nearly half the US workforce is susceptible to being eliminated by automation. Gartner says a third. Those are clearly catastrophic numbers. But…how about we dissect that analysis first? I do so in my book, Silicon Collar and in this blog post. There are many flaws with those and other alarmist reports, and before we spend trillions in new social programs we owe it to ourselves to commission more independent analysis, this time with practitioners included, not just by academics and analysts.
Last century of automation shows gradual job losses which societies adjusted to
For my book I analyzed a century of technologies in the form of UPC scanners, ATM, email and others and how they only gradually impacted jobs. Here are some of the examples
An early version of the ATM machine was introduced in 1960. Six decades later and even with mobile banking taking off, we still have over 90,000 bank branches across the U.S., employing over half a million tellers and other employees
The UPC code and scanner were patented in 1952. It took the grocery industry two decades to start to widely adopt it. The end result was not loss of checkout jobs. It improved inventory control and led to an explosion of SKUs. Even today, with self-check out kiosks in many stores, those jobs have not disappeared.
We have been predicting the death of “snail mail” for decades as email, texting, Skype, Facetime, and social media have become our preferred methods of communicating with each other. Unbelievably, the US Postal Service business has gone up — it sorts half the world’s paper-based mail and packages and keeps over half a million workers employed.
With digital voice mailboxes and most of us doing our own word processing and travel arrangements, who needs secretaries or administrative assistants? Well, according to the Bureau of Labor Statistics, that category still employs nearly four million workers in the US.
In the book, I show what I call societal circuit breakers to automation and leads to an evolution, not revolution in jobs.
Modern automation is similarly impacting jobs — just gradually
People say modern technologies will kill many more jobs. I say show me. Artificial Intelligence? IBM’s Watson has been hyped for 5 years and so far has not replaced a single job even after massive investment. Yann LeCun, director of AI research at Facebook, recently commented, “ we are a long way from machines that are as intelligent as humans — or even rats. So far, we’ve seen only 5% of what AI can do.” Robotics? Japan is the world leader and for 5 years they have tried to use robots for their nuclear clean up. Everyone of those robots has failed. Forget nuclear clean up — how about tidying your hair? David Bruemmer, president and CTO of 5D Robotics, recently described how intimidating a hairdresser’s job looks to a robot. Autonomous cars? Our laws and infrastructure will not be ready for years if not decades.
I have many more examples in my book, but don’t take my word for it. Let’s commission an independent review of automation and job impact in the past few decades and how our societies have adjusted without a UBI needed.
Plenty of new jobs being created
As I told Dennis Howlett there is no single version of the truth when it comes to job estimates. I have described an “Alt-Job” economy of workers in franchises, on platforms ( iStore, Amazon fulfillment, eBay work at home, Uber etc.) and a whole new categories of services — alternative health like acupuncturists, herbalists, pet care etc. — none of which our parents enjoyed. These jobs are not well tracked. The Bureau of Labor Statistics has also reported for 3+ years 4+ million unfilled jobs in each of its monthly reports in the better tracked part of the labor economy. The IRS reports if you exclude the top 1% the rest of us plebs still report $ 10 trillion in income a year. Our workforce is creative enough to keep creating new opportunities — not wait for a dole.
Why are we hell bent on hurting the dignity which comes from work?
Most of us grew up reading Richard Scarry’s illustrated books where anthropomorphic animals went about their daily lives in Busytown. One of his most popular books, What Do People Do All Day? showed these characters like Grocer Cat at work.
For eons, many of us have derived our self-esteem from our work lives. In fact, many of us continue with names which reflect the trades of our ancestors. It could be the Chinese Chong (derived from bow maker), the English Weaver, the Egyptian El-Mofti (from Arabic for legal expert), German Baumgartner (related to orchard), or the Indian Bhattacharya (from Sanskrit for teacher) — and there are thousands of other names derived from occupations in various societies.
Instead of UBI, I would prefer an enhanced Earned Income Credit. Let’s supplement, as needed, the incomes of those who get a good’s night sleep after accomplishing something they feel good about during the day.
What could we do with UBI funding?
UBI fans point to all kinds of funding sources — repurposed unemployment benefits, raise corporate taxes etc. I am not sure it would cover even a fraction of what UBI would cost if we truly mean “universal” — every one in a region gets the benefits.
Here’s how I would like to instead spend the money. We have three major issues in the workforce — drugs (misuse is endemic in certain industries), anger management (made worse by the recent Presidential election), and stress (especially in our veterans,broader ones caused by fear of job loss from machines etc.). Let’s spend on therapies to make these workers much more productive again. Let’s invest in solving our Grand Challenges — in next-gen infrastructure, healthcare, energy, space travel. That will generate a bunch of new jobs.
We are letting our pessimism drive us to a social program which will cripple many economies. Even worse, it will dent work ethic. For most of us work equals dignity and immense satisfaction from accomplishing something each day. Why are we trying to destroy that?
Final thought: why not sponsor our own Harper Lees, not involve the government?
Many of us work in corporate settings as managers, developers, doctors etc. That is the backbone of our job economy. I have spent most of my life in corporations and consulting with corporate clients.
So I was staggered to learn more in my research for Silicon Collar about what I call the “Alt-job” economy that has blossomed in the last couple of decades
Look around and you see franchises of every stripe — Ace Hardware, Dunkin Donuts, Amex cruise planners — literally hundreds of franchises. We have come a long way since Ray Kroc built the McDonald’s empire starting in the 1950s with his phrase, “In business for yourself, but not by yourself.”
Stop by a local Whole Foods and flip through an issue of Natural Awakenings, a publication which carries ads from practitioners in the growing “alternative healthcare” market. This includes acupuncturists, yoga instructors and herbalists among others. The publication claims nearly four million readers in 90 markets in North America. This represents an entire services sector that did not exist a couple of decades ago.
Stop at ethnic grocery/restaurants — selling Latino, Asian, and other ethnic stuff. Look at signs in the store and you will see travel agents who specialize in travel to those parts of the world, others who arrange for cross-border funds transfer, gifts and other commerce.
Talk to small businesses which use Amazon Fulfillment. As much as 90% of certain product categories such as patio furniture sold on Amazon come from third parties
Developers writing apps for iOS and Android stores, authors who write for the Kindle Publishing platform, musicians on iTunes and many more platforms
People selling products from home on eBay or artisanal stuff on Etsy
Contractors listing services on Angie’s List or Thumbtack for residential work. Companies like Avetta certify contractors for complex, industrial settings.
People driving few hours a day on Uber then doing a few hours of courier delivery sourced from Amazon Flex
I am just scratching the surface — by my estimate there are at least 30+ million part and full time jobs in this new economy
Before you scoff and say it’s not a great living let me share some anecdotes from my network. A former ERP exec runs our local UPS store franchise, a former bank manager runs a franchised Kona Ice truck, a former systems integrator runs 2 restaurants and a gourmet grocery store, our pool service is run by a couple, both college graduates.
So before you feel sorry for them, consider this — they might just feel sorry for us. Best I can tell, none of them would go back to a corporate job or relish working at a desk again.
I went to sleep last night jaw wide open having heard Donald Trump do his best imitation of a third world dictator and threaten his political opponent and in turn, hearing Hillary Clinton invoke beloved Abe Lincoln as she wriggled through a question.
I woke up this morning, amused to hear howls on both sides of the aisle. My brain had, however, moved on. It had overnight drawn a bigger circle — put things in perspective.
Yes Trump is disgusting, but he is larger than life. Tom Wolfe’s Man in Full. He is Don Corleone, Hugh Hefner, Howard Hughes. People with deep flaws, yet people we admire, if grudgingly. Yes Clinton appears weak and slippery, but some of the steadiest leadership in the world has come from ladies like Margaret Thatcher, Golda Meir, Indira Gandhi and more recently Angela Merkel and Aung San Suu Kyi.
I would gladly salute either as my Commander in Chief. I have faith in our checks and balances. People say the media is unfair to Donald with a wave of October surprises. It’s part of the American political lexicon. Wikipedia has an entry for the term and examples going back to 1972. People say this is the a new low for US politics. I say go back to the time when we had Presidential duels and when rumors could not be fact checked.
Bigger Circle. I first heard that expression from Bill Joy, one of the cofounders of Sun Microsystems: “If you cannot solve a problem, make the problem bigger. If you draw a bigger circle, you start to see several systems you can work on.”
We often get caught up in the moment — in our social media circles, on talk shows, in cable news chatter. We should take time off and read history books and watch documentaries. They make our circles bigger and put things in perspective so we don’t react hysterically.
I interviewed practitioners in a wide range of work settings where they are using machine learning, robotics, drones and a wide range of other automation technologies. While these practitioners were positive about the new technologies and their impact on work, a number of academicians, analysts, and economists are worried sick about the new machine age and envision a jobless future. Their pessimism, amplified by politicians, is leading to widespread gloom on the street. Internationally, it is even leading to referenda about whether citizens should be guaranteed minimum incomes, irrespective of work status, in anticipation of such jobless societies.
Why are so many smart people so pessimistic? Being a technology enthusiast for decades, I wondered what I might be missing. And that’s when I invoked Joy.
Drawing a bigger circle for the book meant looking at how automation has gradually rolled out over the last century and not just in the last few years. I researched the history of UPC codes and scanners with their impact on grocery jobs going all the way back to 1948. I researched how cars have gradually been taking over control of driving from humans since cruise control was first introduced to the masses in the 1958 models of Chrysler’s Imperial, New Yorker, and Windsor. I similarly studied progress in artificial intelligence, robotics, and self-service technologies and their related impacts on jobs.
Then I made the circle even bigger. I studied how Japan, a voracious adopter of automation in the form of service robots, vending machines, and even conveyor belt sushi, still keeps artisans working with skills that date back centuries.
This research gives me a confidence that we will continue to see “evolution, not revolution” when it comes to automation’s impact on jobs. Our societies have what I describe as “circuit breakers to over-automation.” Machines will become more of our colleagues, and we should not be so worried about their increased presence in the future. If anything, they will take our outstanding workers and make them even better.
As a result my book is a lot less panicky about machines causing widespread job losses.
I feel the same about our elections.
May not work for everyone, but try and make your circles bigger. You will likely find the present and the future a lot less scary when you study the past and understand in most things in life we tend to have evolutions, not revolutions.
This too shall pass and we will soon laugh about the craziness we worry about today. Actually, it took SNL only a day to start laughing about the Trump tapes and Clinton reaction:)
As I was writing Silicon Collar over the last year, I got to see the impact machines are having on jobs and workers in over 50 settings. I looked at work in accounting firms, in banks, on the battlefront, in digital agencies, in garbage collection, in the oil patch, in restaurants, in R&D labs, on shop floors, in the warehouse, in wineries and many more. Just based on those case studies, I could say HCM is going through a major transition. But I did so with Brexit and the US Presidential campaign in background and the talk about “middle class squeeze”, angry workers “who have been left behind”, and that 6 out of 10 Americans say the “economy is on the wrong track”. That made me look at US IRS, Bureau of Labor Statistics, Census and other data to get a better handle on the actual state of the labor economy. The end result – I am firmly convinced HCM executives are in for a dramatic jolt. They face massive opportunities and challenges.
Here are some insights as many executives convene in Chicago for the HR Tech show
a) Machines are becoming a bigger source of “talent”
In the book, I discuss workers being assisted by machine learning, robotics, drones, wearables, process bots, exoskeletons and many other forms of automation. All that technology is a form of talent, but HCM executives have not taken the lead in its deployment. Organizational ownership of “machines” is fragmented—the plant manager likely knows about shop ﬂoor robots, and someone in IT may know how many web services or service bots are deployed, but few companies have an executive responsible for coordinating all their automation efforts. It is an opportunity for HCM execs to step up.
b) Full-time employees are becoming an even smaller portion of the human talent mix
We have used contract labor for a long time. In the new “gig economy” the percent of full-time employee talent is even smaller.
Apple may be an extreme example, but has several thousand employees who develop products which are then sold in its retail stores. Its contract manufacturer, Foxconn, employs thousands of employees and robots in its manufacturing plants in China. Those plants also have interns and other staff hired through third-party recruitment ﬁrms. Apple’s third-party logistics providers like FedEx have a similar mix of man and machine. There are also millions of associated jobs that are not on Apple’s payroll around the apps, music, movies, books, and other items in the Apple ecosystem.
Most other companies are moving to similar models. The talent in the platform, franchise, outsourced ecosystem is rarely controlled by the HCM exec. If they want to continue to be recognized as the Chief Talent Officer, they will need to get involved in sourcing and managing these new forms of talent.
c) Recruiting and retention policies are outdated
The student loan crisis has many root causes, but one most certainly is what Wikipedia calls “credentialism.” There are some jobs which used to require a high school diploma, such as construction supervisors, loans ofﬁcers, insurance clerks and executive assistants, that are increasingly requiring a bachelor’s degree. Who writes those job specs? And who makes candidates jump through hoops? The Glassdoor site (where employees post candid reviews about employers) said on its blog: “Talk to anyone trying to ﬁnd a job, and you’ll hear the same old groans. ‘Job hunting is a black hole.’ ‘This whole process is demoralizing.’ ‘I feel like I’m spinning in circles.’ It’s no secret that recruiting is broken. The current process leaves both parties—recruiters and candidates alike—exhausted. It’s time that companies make improvements or risk damaging their brand.” And many should reconsider going back to apprentice models and de-emphasizing formal degrees and focusing on more just-in-time, new ways of video and other interactive “learning”
d) Workers are becoming much more mobile
HCM executives need to face up to another reality in the workforce. Never before have workers had so much choice in jobs. The Bureau of Labor Statistics classifies workers into one of 840 detailed occupations. CareerPlanners.com does an even more granular listing and lists 12,000 separate jobs.
There are so many “new gen” opportunities — franchises (about 10 million jobs), platforms (Apple, Amazon fulfillment, eBay work at home, Uber etc — about 20 million part time for now but rapidly changing ), new services — alternative healthcare, ethnic groceries, pet/child care etc.(another 5 million). I am not even including Silicon Valley type entrepreneurship opportunities in energy, space, food, IT etc.
Never before have workers had a chance to get second, third, later acts in our careers. In the book, I catalog many who keep evolving and thriving. The average person born in the latter years of the baby boom (1957–1964) held 11.7 jobs from age 18 to age 48, according to the BLS.
That means HCM executives will have way more competition for talent. This when most employer brands have been tarnished by waves of layoffs, offshoring and other moves.
Lots of opportunities. Even more challenges for HCM execs. As the Chinese saying summarizes in masterful understatement “May you live in interesting times.”
I heard Peter Diamandis of X-Prize fame and author of Abundance present at a tech event this week. It was staple Peter talking about how human development has moved to an age of “exponential and global” after 150,000 years of “local and linear”. He has an optimistic view on how technology helps turn things that are scarce into abundance.
As he presented on trends in robotics, machine learning, 3D printing and other areas, I correlated them to what I learned in interviews for my new book Silicon Collar. They were pragmatic and positive like Peter.
Then he joked President Clinton once asked him “Why do you have such a positive outlook? Don’t you watch the news?”
He dove into neuroscience and talked about the amygdalae, the two almond shaped portions of the brain which are said to have evolved with our ancestor’s survival instincts. Modern days amygdala are said to be always on high alert and we filter out positive news and focus on negative news, which the news media is only too happy to provide.
I was tempted to stand up and shout “the news media have been joined in the negativity by analysts and academics”
In the book, I have a chapter titled Sum of All Fears. I point out the pessimism of Gartner, Oxford U and many other “brands” about machines killing hundreds of millions of jobs.
Peter Sondergaard, Head of Research, told the audience at the ﬁrm’s 2014 Symposium/IT Expo: “By 2025, three out of 10 jobs will be converted to software, robots or smart machines.” and “By 2018, digital business will require 50% fewer business process workers.”
More recently, Gartner has projected by 2018, more than three million workers globally will be supervised by “robobosses”.
Two Oxford researchers had a similarly pessimistic assessment: “According to our estimates, about 47% of total U.S. employment is at risk.”
WEF, McKinsey, MIT and many other thought leaders have similarly large and scary projections about job losses.
I was a Gartner analyst from 1995-2000. Gartner usually assigns a probability to its planning assumptions, as an indicator of its conﬁdence in such a prediction, but the Sondergaard statements did not indicate any such hedge.
While Gartner had a timeline for its projection, the Oxford professors did not even attempt one. They also did not appear to do a reality check for the job categories they analyzed. The researchers had calculated a high 0.79 “susceptibility to computerisation factor” (with 1.0 being the highest) to heavy truck and tractor-trailer drivers. This, when the U.S. trucking industry says driver shortages could reach as high as 175,000 positions by 2024 (even if the industry adopts autonomous trucks, regulations will likely require a driver as a backup). The professors had assigned an even higher factor of 0.84 to cartographers and photogrammetrists (who deduce measure- ments from images), which the Bureau of Labor Statistic projects as one of the fastest growing occupations over the next decade. They had assigned a yet higher 0.94 factor to accountants and auditors, whereas hiring at U.S. public accounting ﬁrms jumped to reach record levels in 2013–2014.
What about new jobs from the automation and new digital businesses? The Oxford profs did not feel that was worth quantifying.
Here’s what is concerning. Oxford is the oldest university in the English speaking world. It has archives going back centuries.
Did they look at the archives and factor research like I did which shows that automation only gradually erodes jobs, often over decades. Why are there still 90,000 bank branches each with several teller and other jobs (just in the US) even after decades of ATMs and Mobile banking? Why do we still have over 600,000 U.S. postal jobs in the face of all kinds of digital communications and when the USPS has automated in the form of kiosks and logistics tech? Why do we still have so many grocery checkout jobs in face of the UPC code/scanner patented 65 years ago and self checkout available for years now? Why were half the cars sold globally last year manual – 5 decades after Playboy magazine proclaimed “Bye bye, stick shift”?
Gartner has been issuing “technology hype cycles” for decades. Did they factor that AI has gone through multiple hype cycles since the 1950s. That is when Alan Turing defined his famous test to measure a machine’s ability to exhibit intelligent behavior equivalent to that of a human. In 1959, we got excited when Allen Newell and his colleagues coded the General Problem Solver. In 1968, Stanley Kubrick sent our minds into overdrive with HAL in his movie, 2001: A Space Odyssey. We applauded when IBM’s Deep Blue supercomputer beat Grandmaster Garry Kasparov at chess in 1997. We were impressed in 2011 when IBM’s Watson beat human champions at Jeopardy! and again in 2016 when Google’s AlphaGo showed it had mastered Go, the ancient board game. Currently, we are so excited about Amazon’s Echo digital assistant/home automation hub and its ability to recognize the human voice, that we are saying a machine has finally passed the Turing Test. Almost. Yann LeCun, director of AI research at Facebook, has commented, “Despite these astonishing advances, we are a long way from machines that are as intelligent as humans — or even rats. So far, we’ve seen only 5% of what AI can do.”
It’s the same hype with robots. The ﬁrst humanoid robot appeared in Japan in 1928. It could do simple motions like move a pen with its right hand. Today, Japan is the leading maker and consumer of robots, accounting for half of the world’s production. Naturally, it has the world’s largest concentration of robot engineers. Yet, these world-leading experts have tried for ﬁve years following the Tohoku earthquake to use robots to clean the radiation at the Fukushima nuclear plant. So far, all the robots sent into the reactors have failed to return.
With their brands, every word they say gets amplified. The Oxford study has been parroted in over 400 other academic journals, without any of the questions I raise. Gartner issues hundreds of similar predictions each year and rarely goes back and audits them for accuracy.
Business executives know how to take such analysis with a pinch of salt. They even have a term for it – FUD. But the average citizen feels paranoid. It’s showing up in alarm in government policy.
Switzerland was the first of many countries which plan to hold a referendum on “Universal Basic Income” – a payment to each citizen irrespective of work status. It is being justified on the assumption we are moving to jobless societies. If Gartner can project a third of jobs gone by 2025, and Oxford even higher, you can see why people are panicked.
It’s time to ask the pessimists for the data which justifies their dire predictions,
Predicting the future has always been risky. The pushback I get is the past is a poor indicator of the future. I say then we should quit teaching regression analysis in Stats 101. Trend lines across a time series of data – in my case going back a century – should count for something. My analysis over aa century showed only gradual impact on jobs. I saw jobs being transformed, more than destroyed.
The reality is there are compute evolution curves, and then there are adoption curves. The former are becoming exponential (but they have been since Gordon Moore wrote about his famous law in 1965) , the latter not so much. As I analyze in the book, there are societal “circuitbreakers to over automation” which causes stop technology from being absorbed at dystopian rates.
Our thought leaders should be more responsible in their pronouncements. And we should not be afraid to challenge them for justification of their pessimism, before we set up a new wave of social programs which could cost us trillions and potentially destroy our work ethic.
In writing my book, Silicon Collar, I saw plenty of examples of how machines make human workers safer, smarter and speedier. I also became more aware of poor implementations where the man-machine balance is broken and leads to worker and customer dissatisfaction. On New Florence I have started a series with some of those experiences.
As Steve Miranda previewed last week, one of the more interesting announcements this week at Oracle OpenWorld is around its Adaptive Intelligent Applications. Steve had said
“Basically, what we're doing is leveraging our data cloud, which I know you're familiar with (having profiled BlueKai), together with machine-learning algorithms and incorporating that into our transactional applications to derive better BI/better decision-making, and frankly, a new category of applications. The first one which we'll launch and demo is our next best offer, next best action - essentially a recommendation engine off of our cloud commerce.”
In addition to lots of data and lots of compute power in their cloud, Oracle also believes its domain and industry apps knowledge and its “decision” science (Oracle Labs, vertical groups as in Smart Factory and IOT areas) – the 4 “pillars” position it well as machine learning grows in the enterprise space.
Some of the apps being planned in this category are
Smart Offers and Actions
Best Fit Candidates
Best Value Freight
Optimized Payment Terms
While Oracle has plenty of data to leverage for the first app, especially around consumer marketing data via BlueKai, it’s not completely clear where it will source data for other announced apps. The timing of release of the apps was also a bit unclear from the initial briefings, and I am sure there will be industry and geography cuts at many of these apps.
BTW, in my recent book, Silicon Collar about automation and impact on jobs, I point out AI has gone through 10 hype cycles since 1950 when Alan Turing defined his famous test to measure a machine's ability to exhibit intelligent behavior equivalent to that of a human.
So it is good to see a major vendor start to talk about specific use cases and put a bit more business context around the current buzz around machine learning.
Silicon Collar is off to very nice media reviews, Amazon reader reviews and many nice emails from readers. But in many ways it has also touched a nerve. Some are irritated with my optimism. I find they fall into three camps
a) “Things will be really bad” – the guru
These tend to be technology savvy academics, analysts and economists who are convinced acceleration in computing corves will lead to massive job losses. In this ZDNet column I summarized a century of examples across sectors where we still have tens of millions of postal, secretarial, grocery and other jobs decades after automation was supposed to have destroyed them. In the book I have a chapter called Circuit Breakers to Over Automation which describes how societies only gradually absorb automation. I don’t see that changing anytime soon. Automation does cause erosion of jobs, but that takes time, and it also creates a new generation of jobs
b) “Things are already bad” – the guilty
These tend to be people who talk about workers “left behind”. No denying there are many of those. You would be blind to not see the homeless or those that just stumble from job to job. This group of pessimists, however, focuses mostly on poor and lower middle class and wants more social programs for them. They keep talking “middle class squeeze” – blaming corporations and the “one percenters”. For whatever reason, they only have a foggy notion of the solid core of middle class – plenty of accountants, attorneys, architects, engineers, healthcare professionals and many others. They also don’t want to believe data like
if you leave out the top 5%, the rest reported $ 6 trillion in AGI or $ 8 trillion in income to the IRS
for 3+ years, the BLS has reported at least 4 million unfilled jobs every single month
c) “Things are already bad” – the angry
This group tends to discount all data, especially government sourced as propaganda for President Obama and by extension, Hillary Clinton. Their narrative is things will only get better if we have a change in government. I don’t have a problem with that (I am politically independent), but I do point out progress has been non-partisan under both parties
Since 1990, average value of new US home has nearly doubled
Since 1990, we have never had a single year when median annual family income has been under $ 50K
our workers have $ 25 trillion in retirement assets
I am not on a crusade to turn everyone optimistic, but I sure hope they give the book a chance to provide an alternate point of view.
Lost in all the noise about the “middle class squeeze”, angry workers “who have been left behind”, and that 6 out of 10 Americans say the “economy is on the wrong track” is another story which has not been widely reported. The US has created a new-gen labor economy which the rest of world will gradually adopt.
No single person designed this “thing” or trademarked it. Some have called it the gig or indie economy but that barely touches on the broad dimensions I will describe. No politician has taken credit for it — so far.In fact, few even know about it.
I found it through pattern recognition I did for my new book, Silicon Collar. I was looking for trend lines on how societies gradually absorb automation (see my ZDNet post for a summary), and I stumbled across this remarkable new organism.
First some context.
In the 50s, a company could stay on the S&P 500 list for 60 years, today they barely last 20 years. With that shortened corporate life span, the concept of corporate lifetime employment and pensions are a pipe dream. Actually only 4–5 generations in all of human history enjoyed that lifestyle (and honestly many did not enjoy the bureaucracy which came with it) so it was an aberration. Our agrarian ancestors did not avail , neither will our digital descendants.
And it’s not just US companies — German, Japanese, Chinese face the same pressures. But the US has adapted a bit better.
Our companies have moved to what I call in the book “Clover-leaf organizations”. Management philosopher Charles Handy was prescient when he wrote in his 1989 book The Age of Unreason about the three leaves of the “Shamrock Organization.” I continue in the book
“You could argue that if Handy had written the book today he would consider a four-leaf clover as his defining metaphor, with the fourth leaf covering machines, robots, and other automation as another source of the “talent”
Actually, clovers can have many more leaves. The Guinness World Records says one was found with 56 leaves. If you look at all the ways organizations utilize talent these days, Handy’s three leaves have many derivatives, most enabled by advances in technology.
Apple has several thousand employees who develop products which are then sold in its retail stores. Its contract manufacturer, Foxconn, employs thousands of employees and robots in its manufacturing plants in China. Those plants also have interns and other staff hired through third-party recruitment firms. Apple’s third-party logistics providers like Fedex have a similar mix of man and machine.. There are also millions of associated jobs that are not on Apple’s payroll around the apps, music, movies, books, and other items in the Apple ecosystem. Just around apps, Apple claims to support a broad community: “Nearly three-quarters of those jobs — over 1.4 million — are attributable to the community of app creators, software engineers and entrepreneurs building apps for iOS, as well as non-IT jobs supported directly and indirectly through the app economy.”It also says, “The iOS app economy has created 1.2 million jobs in Europe and 1.4 million jobs in China.”
I provide other examples in the book. But look what that has done for our workers. We have a choice of 840 occupations the Bureau of Labor Statistics (BLS) is tracking. The list will be updated in 2018 and I expect it will be longer and have more STEM influence. Our workers are getting 2nd, 3rd, later acts in life, No other country has so many new gen opportunities — franchises (about 10 million jobs), platforms (Apple, Amazon fulfillment, eBay work at home, Uber etc — about 20 million part time for now but rapidly changing ), new services — alternative healthcare, ethnic groceries, pet/child care etc.(another 5 million). I am not even including Silicon Valley type entrepreneurship opportunities in energy, space, food, IT etc.
In this new gen economy, machines will play a much bigger role. Amazon has delivered 50 price cuts around its AWS in the last decade. Could not do it without a heavy mix of machines. UPS averages 1 accident per million miles of driving. Could not do it without all kinds of telematics in their trucks. Foxconn has delivered billions of high-quality Apple and other devices. Could not have done it without precision machinery and bots. Machines will take our best new gen workers and make them exemplary.
But our corporate policies have not kept up. Very few organizations have a complete map of all the talent they are leveraging. That’s remarkable, considering that for many companies 80% to 90% of their talent (like Apple above) is now “off balance sheet” — not directly on their payroll. Companies have insanely long interview processes when employees are changing jobs every few years.
Our public policies have not kept up. We need portable benefits and safety nets for their new work life. Government data on the changing labor market is outdated. The BLS classification mentioned above is not due till 2018. Once a decade in this fast moving world? Our politicians keep hammering Apple, GE and others to bring jobs back. Which of those “off balance sheet” jobs? I am seeing extreme thinking like Universal Basic Income in preparation for jobless futures. There will be plenty of jobs — just very different ones.
No wonder, many of our workers have not kept up and are bewildered and angry.
Shame on us, collectively. We have seen it coming several times in our lifetimes. Cities like Pittsburgh, Detroit and others have gone through near death experiences and have come out very differently. We need to do the same in our individual lives. Reinvent, continually, not keep pining for the past
A friend of mine wryly observes there are only 9 lifetime jobs left. They are in Washington DC. And most lucky to get it, have to wait till they are in their 60s. As we are seeing with a candidate trying for the job today, the recruiting process is extremely painful.
In turn, however, we have ended up with a remarkable new labor economy, that our parents would have drooled to be part of.