Our Jobless Future
The Need for Basic or Minimum Income Programs
The inevitable march of progress
Throughout history, we have been warned of technology replacing the role of human labor. The Luddites, whom destroyed weaving machinery in protest during the 19th century are probably the most well-known group, but one can imagine Homer complaining that the written word would make man less reliant on memory and oratory. Nothing that we have seen throughout the agricultural and industrial revolutions, however, has prepared us for changes in automation and artificial intelligence, as computers gain human levels of intelligence. These advances are set to erase most white-collar and blue-collar job, and unlike past transitions, this time we won’t be seeing new markets open to employ these displaced masses of workers. We must prepare for this permanent, mass unemployment today, by creating and evaluating basic and minimum income programs to provide for those affected.
The Singularity is coming
In 1997, IBM’s supercomputer Deep Blue shocked the world when it beat world chess grand-master Gary Kasparov in a series of chess games. For years, speculation over computer’s ability to win at chess had been mocked and derided by skeptics, but Kasparov’s decisive loss proved to the world that computers were the new dominant force in the game (Goldsmith). At the time, Deep Blue was one of the most powerful supercomputers on the planet, and had been designed specifically for chess.
Futurist Ray Kurzweil noted that computationally speaking, IBM’s supercomputer was roughly equivalent to the gray matter present in a salamander lizard. If one takes estimates of the number of brain cells present in a human mind, multiplies it by the average number of intraneuronal connections between each cell, and again by the firing rate of synaptic transmission, you will get a range of finite binary operations (Kurzweil). By this measure, Deep Blue was no match for the human brain overall, but its singular focus to the game of chess and brute force capabilities proved more than sufficient to handily defeat the greatest human player on earth. The problem, for those of us relying on biological matter, is Moore’s law. While Deep Blue might have been top of the line in 1997, today’s iPhone 6 is ten times as fast — and that’s not even the current version. Our brains aren’t getting any faster, and the computers are getting smarter.
The Jeopardy defeat of Ken Jennings at the hands of IBM’s Watson supercomputer made headlines in 2011, but mostly for the novelty factor rather than the existential threat that it represented to humankind’s place at the top of the totem pole. Whereas the game of chess was essentially a brute-force problem against the astronomical possibilities stemming from the rules of chess, the feat required to win at Jeopardy required a much more complicated set of skills. The underlying architecture, called DeepQA, had to figure out what the question was asking, then possible answers, each of which used hundreds of algorithms looking at over 200 million pages of information to find the best answer in seconds (Best).
Since mastering chess and Jeopardy, computers have gone on to beat humans at the traditional Chinese game Go, a feat once thought impossible, and are now the masters of Poker. Research and development has not been limited to beating humans at games. Like their robot brethren have done in the factories, artificial intelligence is coming for our jobs.
After Watson beat Jennings, IBM began working on putting Watson to work in medical fields using the same algorithmic skills. Using trained professionals, Watson was fed correct questions and answers to known medical histories, then was fed known answers and asked to guess the history. It was corrected where needed, and adjusted its algorithms through the magic of machine learning until the point where it could be given cases and suggest correct therapies. By 2013, Watson had achieved a level of medial knowledge comparable to a first-year med student and was well on its way to being the best cancer diagnostician in the world (Love). AI can now predict heart failure with 80% accuracy, and diagnose skin cancer as well as a board-certified dermatologist.
Meanwhile, Watson and other intelligent agents are becoming robolawyers. Having access to the entirety of course law will allow it to do research and provide case precedent faster and potentially better than any first-year law grad (Sills).
It is beyond a doubt the nascent revolution in autonomous vehicles that will have the first big impact on the lives of most everyday citizens. A study published by the Center for Global Policy Solutions in March of 2017 cited over 30 companies working on autonomous-vehicle technology. The most optimistic predictions are that we will see fully autonomous vehicles on the road in 3 to 5 years, and the report claims that “more than four million jobs will likely be lost with a rapid transition to autonomous vehicles” (CGPS). And that’s just the actual drivers. Not mentioned are the secondary costs associated with driverless vehicles. What happens to the truck stops and gas stations dotted along the interstate highway system when the number of long-haul drivers drops off a cliff? What about the municipalities that depend on red-light cameras, or speed traps and other moving violations to bring in money through traffic courts? What about the parking garages and meters and the money that they bring in? There are a lot of changes to be seen in the next few years as society struggles to deal with these challenges.
A jobless economy is coming
When most people think of automation, one of the first images that spring to mind are of the large robotic arms that were introduced to the automotive industry in the 1980s. Assembly line work has been one of the first targets for automation, as the repetitive, non-varying work is perfect for robotic programming. But the robots are already off the assembly line and are on the warehouse floor. A 2013 study by Carl Frey and Michael Osborne of Oxford looked at how susceptible jobs are to computerization. They looked at over 700 occupations from therapists to data entry and telemarketers, and concluded that “47 percent of total US employment is at risk” (Frey). They argue that both high wages and education level are the best factor of whether a job it safe from automation, but some authors argue that even this won’t last for too much further in the immediate future, as there will be few jobs that a human can do that a machine won’t be able to do better.
While there can be little doubt that most blue-collar jobs are at risk from computerization, convincing information technology workers, educators, doctors, lawyers and other white-collar professional classes that their jobs are at risk takes a bit more work. That is exactly the aim that Silicon Valley software developer Martin Ford attempts to achieve in his 2015 book Rise of the Robots: Technology and the Rise of a Jobless Future. In it, he argues that not only will blue and white-collar jobs disappear, but that we will not see the usual job creation in other subsequent sectors that has accompanied other transitions in the industrial and information economy. This time, Ford argues, the jobs aren’t coming back, and the only question is whether we’re going to see “broad-based prosperity or catastrophic levels of inequality and economic insecurity” (Ford)
Ford is not the only one who sees this future ahead of us. John Nichols, a correspondent for the Nation, and Robert W. McChesney, author and professor at the University of Illinois, wrote People Get Ready: The Fight Against a Jobless Economy and a Citizenless Democracy after the pair spent time with a number of tech company millionaires and billionaires and were shocked at how many of them are were planning for a future of automation. They report that the claims that Ford makes in his book, (which they cite by name,) isn’t far-fetched, but rather is accepted as fact by the CEOs of the world’s largest tech firms. Echoing Ford’s claim of a jobless future, People Get Ready says that “the end of work as we know it will hit at the worst moment imaginable: as capitalism foster permanent stagnation, when the labor market is in decrepit shape, with declining wages, expanding poverty, and scorching inequality” (McChesney)
The idea that the benefits of technological progress should be felt by everyone, not just the super-rich, is one that I hope I don’t have to argue. Without a course correction, we can expect wage stagnation for the middle class, while wealth and income growth continue to concentrate in the hands of the wealthy with access to capital, those able to afford the technology. And while geniuses like Tesla/SpaceX founder Elon Musk and noted astrophysicist Stephen Hawking are running around warning of the existential threat from a super intelligent AI, MIT economist Andrew McAfee is more concerned with how people will react. At a recent gathering of artificial intelligent researchers, he was quoted as saying: “I am less concerned with Terminator scenarios. If current trends continue, people are going to rise up well before the machines do” (Metz)
Income programs are a necessity
If education and retraining are pointless since computers will be better at everything that humans can do, what is the solution for a future where the jobs aren’t coming back? Martin Ford claims that “the most effective solution is likely to be some form of basic income guarantee”, or GBI. The Global Policy Initiative, in the report mentioned earlier, recommends a progressive basic income implemented through the Social Security program as part of their policy recommendations. Nichols and McChesney differ on this point and suggest that a basic income would lead to the privatization of government services. They advocate that government take over more functions from the private market, reducing the gap between rich and poor as services such as broadband, public transportation, healthcare and education are provided for free. (A bit of distinction is required here. A ‘basic income’ is a system where unconditional income is granted to every citizen, where ‘guaranteed minimum income’ is a social welfare based on means tests. The difference gets muddled due to reports which conflate the two.)
As Politico’s Noah Gordon points out, the idea of a guaranteed or basic minimum income isn’t a new one, nor is it one a completely liberal progressive one. Free-market libertarian economist Milton Freidman advocated one via a ‘negative income tax’ under a plan that President Richard Nixon tried to pass. Libertarian conservative political scientist Charles Murray advocated eliminating all welfare transfer programs via a $10,000 annual grant. Then there’s the Alaska Permanent Fund, which pays state citizens a dividend on the states oil revenues (Gordon)
The socially progressive proponents of such programs think that they provide people with a social safety net that they can use to pay their basic living expenses and have the freedom to pursue their interests, whether it’s starting a business, going to school, caring for a loved one or going to work for someone else.
Not all are convinced, however. Judy Wajcman, writing in The British Journal of Sociology, questions whether this artificial intelligence singularity proposed by futurists such as Ray Kurzweil will ever come to being, but even she agrees that the economic problems and inequality of time, money and work are problematic. She writes:
“Rather than worry about the dreaded moment of Singularity, we should be concerned about the dominance of a small number of corporations who have this computing power and about the social consequences thereof. Such political questions are too often lost in our obsession with the robotic revolution we are set to witness.” (Wajcman)
One of the biggest challenges to a basic or universal income program is the idea of the undeserving poor, or the argument that basic income will lead people to watch TV and sleep all day. Basic income advocates dispute this, and point to the masses of people left behind by globalization, outsourcing and automation, and claim that basic income will help slow the spread of right-wing populism. Organizations such as the Basic Income Earth Network, in association with a network of other like-minded operations, have even started a peer-review journal, Basic Income Studies, to explore the issue and other poverty relief initiatives, and researchers are starting to gather more and more data on these experiments.
This January, Finland began experimenting with a guaranteed income. 2000 participants in their welfare system were selected to receive €560 ($587) a month in a program scheduled to run for two years. The program is aimed at reducing the perverse incentives that prevent welfare recipients from working an earning income for fear of losing their benefits. The hope also is that the program will save money by reducing the bureaucratic waste that comes from administration of the welfare program. The Italian city of Lovorno started a guaranteed basic income program last June, and similar measures are being debated in Brazil, Canada, Iceland and Uganda. Scotland is also researching and considering universal basic income as well (Brooks). Private organizations are moving forward with their own experiments as well. Y Combinator, a startup incubator, has started a basic income project in Oakland, California to answer how “people’s happiness, well-being, and financial health are affected by basic income, as well as how people might spend their time” (Altman).
Not everyone is favor of such programs. Last year in Switzerland, a referendum was held on whether to give a guaranteed income of $2,500 a month to every adult citizen. The measure was rejected by more than 75% of the vote (Kottasova).
The largest attempt, by the nonprofit GiveDirectly, aims to provide monthly, long term basic income for 40 villages in rural Kenya for 12 years. They hope to have results on how the assistance affects welfare and short-term decision making within the first two years. They are 79% of the way to reaching their $30 million fundraising goal, and hope to have hard data on the effect of basic income on economic status, entrepreneurism, gender relations, and general well-being.
The carriage-driver or the horse?
The arrival of human-level intelligence has long been the subject of debate, and concerns about computerization were around long before Lyndon Johnson created a national commission on Technology, Automation, and Economic Progress back in 1964. From his remarks on signing the bill creating the commission:
“Technology is creating both new opportunities and new obligations for us-opportunity for greater productivity and progress — obligation to be sure that no workingman, no family must pay an unjust price for progress.
Automation is not our enemy. Our enemies are ignorance, indifference, and inertia. Automation can be the ally of our prosperity if we will just look ahead, if we will understand what is to come, and if we will set our course wisely after proper planning for the future.” (Johnson)
While Kurzweil, Musk and others may aim to bring about or prevent the singularity in the coming years or decades, we must make sure that the least of us are not trampled beneath the continuous grindstone of technological progress, and that the masses are not left abandoned to the past while the elites move on to a new gilded age. Change is happening, and we must take steps now to prepare for our probable future.
In discussions of industrial advancement and automation there are inevitably discussions of certain professions replacing others, one example of this being the invention and domination of the automobile as our primary mode of transportation. Skeptics of our jobless future would point out that while the carriage-driver may have easily found work as a motor-driver, there is one appropriate question to offer as a rebuttal:
‘What about the horse?’
