Sigmund Freud is often quoted for his observation: “Love and work . . . work and love, that’s all there is.” But what happens to our sense of self, our sense of purpose, if the work part goes away?
I think we know that it’s not a pretty picture, at least in our current world. People who lose their jobs for an extended period tend to lose their sense of direction and self-esteem. Often they fall prey to alcoholism or other addictions. Families fall apart or become dependent on welfare, and an attendant sense of personal failure and shame ensues. When the work goes away, how much love remains?
The end of work is a theme explored by sociologists and political scientists and also extensively mined in science fiction. Our imaginations tend to be drawn to one pole or the other: a bleak, hopeless landscape of downward spiraling poverty on the one hand or a utopian vision of flowering creativity and intellectual exploration on the other.
We are told that we are on a social and technological trajectory that may in fact lead to the end of work on a broad scale.
I recently attended a two-day event in San Francisco called the World Fair Nano, a technological exposition. The show floor featured a wide variety of companies hawking everything from smart skateboards to the newest drones, to 3-D printers that could use recycled plastic, to toys that could teach children to code, to cognition-enhancing software for the elderly, and more. Of particular interest to me, however, were the talks from CEOs and visionaries that were scheduled every 20 minutes over the two days.
“Nearly half of Americans already receive some sort of government assistance to live on—quite possibly so they don’t revolt, whether at the voting booth or by civil disobedience. This support includes welfare, food stamps, Medicaid, social security, and myriad other programs. And the brunt of it is borne on the taxes we pay.”
I’ve been tracking prognostications regarding the future of work, and it’s been interesting to see how experts draw such diametrically opposed conclusions. At this point, my own opinion is that nobody really knows how this is all going to play out and that the outcome depends quite a bit on the sorts of decisions and leadership (or lack of it) happening now.
Three speakers at the Nano poured fresh fuel for me on this burning question. One was Dr. Frida Polli, CEO and co-founder of a company by the name of Pymetrics, Mr. Zoltan Istvan, a futurist and transhumanist who will be running for California State Governor on a platform of a guaranteed minimum income for all California citizens, and well-known blogger and futurist Robert Scobel.
I was able to email Mr. Istvan who responded by sending me his slide deck from the presentation along with some relevant links. He sees a collapse of work on the horizon in about 10 years; in fact, he predicts that between now and the end of Trump’s first term in 2020, millions of jobs will likely have been lost in the U.S. due to the impact of automation, software, and robots. He goes on to say that by 2030 job losses might rival that of the 2007 recession in which some 8,000,000 people were put out of work and our banking system was on the verge of collapse.
“By 2030, the job losses will likely be in the tens of millions. McDonald’s will flip burgers with machines, Amazon will deliver packages with drones and taxis will all be self-driving. Even white-collars jobs, like those on Wall Street, will be replaced by artificial intelligence—the world’s largest hedge fund has already set plans in motion for this. Like the Titanic, capitalism is sinking, but few passengers are wondering yet if there are enough lifeboats.” http://tinyurl.com/ycqza7th
As a futurist, however, Istvan is not as pessimistic as these predictions imply. Rather, he sees a survival solution. He advocates for a guaranteed annual income, supported not by taxes but by California cutting a deal with the federal government to lease its land and natural resources to pay for a basic income.
This visionary approach, he argues, could be extended to the entire nation.
“The Federal government’s net worth of natural resources is at least $130 trillion. California is the third largest state in the U.S., and its 45 million federal acres of land could be worth $10–20 trillion.”
And he’s not talking about selling off the national parks, either. Instead, a portion of the income they already produce might be directed toward this plan.
“Along with California’s state and national park tourism, as well as other wilderness and recreational areas that charge fees, these endeavors make good money. But you and I, as tax-paying residents, don’t really feel it or know about it—and we certainly don’t get a paycheck for it. I’d rather California be like Alaska, where everybody every year gets cut a state check.”
I’ve personally long thought that there is a fundamental problem in our economy such that, as machines take on more of the work, displaced workers will end up forced to be on public assistance with all the stigma associated with that. We need to recognize that this is a systemic problem and that the individuals impacted by it should not be stigmatized. In fact, he points out:
“Nearly half of Americans already receive some sort of government assistance to live on—quite possibly so they don’t revolt, whether at the voting booth or by civil disobedience. This support includes welfare, food stamps, Medicaid, social security, and myriad other programs. And the brunt of it is borne on the taxes we pay.”
So, I, along with others have long thought that some sort of universal income guarantee could be the best way out. However, I didn’t have an idea as to how such a thing could be funded. Zoltan Istvan suggests a solution to this dilemma.
“And how much money would Californians receive every year from its natural resources, assuming we use its midpoint valuation of $15 trillion dollars? It turns out, quite a bit, if at least 75 percent of the state’s federal land was leased out and it provided a 5 percent return, which is pretty standard.
If every household—and there are about 13 million in California—received this sort of 5 percent annual payout, it would be about $57,500 per household, or nearly $5,000 a month. In short, it would dramatically change the lives of tens of millions of people—especially the nearly 40 percent of Californians who live at, below, or near the poverty line of $24,000 for a family of four.”
“By 2030, the job losses will likely be in the tens of millions. McDonald’s will flip burgers with machines, Amazon will deliver packages with drones and taxis will all be self-driving. Even white-collars jobs, like those on Wall Street, will be replaced by artificial intelligence—the world’s largest hedge fund has already set plans in motion for this. Like the Titanic, capitalism is sinking, but few passengers are wondering yet if there are enough lifeboats.”
Dr. Frida Polli suggests there is not currently a job shortage, nor will there be one in the foreseeable future. The problem as she sees it is that the hiring system is broken—the whole process of writing and sending in resumes is deeply flawed and a waste of time, as many job seekers suspect. According to the Pymetrics website, the average job receives 250 applications, yet the candidate chosen by the company fails 30–50{87a18df7a28eb56c6a7dc02e4e1a3d322672f7d5de2b418517971f2bf2603901} of the time. Moreover, resume review leads to women and minorities being at a 50–67% disadvantage. Their research also shows that 83% of candidates rate their experience as poor and 45% of applicants never even hear back from the company. Pymetrics claims to be able to fix this broken system by recommending the right person for the job, while leveling the playing field for everyone. How do they accomplish this miracle? Computer intelligence, which others see as the cause of the looming problem, they see as the solution.
They have created neuroscience games that collect objective behavioral data using “neuroscience exercises that are the gold standard of neuroscience research.” In addition, they have created artificial intelligence to maximize prediction while increasing efficiency through customized but automated machine-learning algorithms. All of this they say leads to bias-free recruiting by methodically removing bias from algorithms, using an “iterative algorithm auditing process” that ensures a lack of bias. To date, the company already powers hiring for 50+ enterprise clients worldwide.
Another stance toward the feared coming technological apocalypse is one where, instead of being displaced, human workers and robots will co-exist side by side doing what each does best. This point was emphasized by Robert Scobel in his presentation. He said he’s been to places like the Amazon facilities, where workers slave away in vast warehouse-type structures that are too hot in summer and too cold in winter. He described it as truly miserable, dehumanizing work.
We’ve probably all heard about how robots are now able to search out the products people have ordered and bring them to the human workers to pick out and sort. The technology is at an inflection point where the robots will be able to “see” and recognize the various items and very delicately pick them up and sort them, even very small items. Robots are already beginning to take over these sorts of operations. This, according to Scobel, is a step in the direction of human liberation. What are robots good at? Speed, strength, repetition. And what are humans good at? Creativity, intuition, and context recognition, among others. He described humans teaching robots by “getting inside them” using virtual reality (VR). With VR goggles, the human worker can see what the robot sees and guide its “arms and hands” to pick items up and put them in the proper place. The human is driving the robot, so to speak, and the robot is recording it in memory so that it can later do the task on its own, after having mastered it. One important thing to notice in this scenario is that the human teacher does not have to be an engineer or a programmer. He or she merely has to understand the physical task to be performed. After having taught the robot, the human is presumably able to move on and teach other tasks to other robots.
The question remains, however, whether there will be enough demand to keep such human teachers busy or whether they will end up putting themselves out of work.
So, we’re back to the original conundrum.
How you see it depends upon whether you’re an optimist or a pessimist.
