Essay: The future – technological unemployment

Introduction
Over human history, technological innovation has consistently lessened the burden of work for all people. From the invention of the wheel that exponentially decreased the effort required to transport objects to modern-day supercomputers that compute 200 quadrillion calculations per second, human inventiveness results in less total work done by humans.1 Analyzing and predicting this trend for the 21st century poses an important question: is there an end to this progression of less work, and if so, what does it look like? While one can only speculate, it appears that the growing use and abilities of automation and artificial intelligence will decrease the population’s overall participation in work, altering society’s perception of “work” to represent other activities.
While at first, the possibility of the end of work may sound implausible, consider the most important developments in human history. Some developments that may come to mind are the invention of the wheel, domestication of work animals for farming, written symbols, penicillin, or electricity. If there was some way to quantify these developments, maybe one could debate their relative importance. Historian Ian Morris has attempted to quantify human development through “social development.” Social development is a “group’s ability to master its physical and intellectual environment to get things done” through the measurements of energy capture, organization, capacity for war, and the ability to store and share information (currently known as “information technology”).2 Through this quantification and its comparison to the total human population, one of the best singular measures of human success, Morris reveals an interesting correlation. The two plot of both measures are almost identical:
Figure 1. Human Social Development Versus Worldwide Population
Source: The Second Machine Age, pp. 7.
As is clearly visible, they seem to almost be the same line! Even more interesting is the explosion of growth around the dawn of the Industrial Revolution, which many historians believe started with the innovative efficiency of James Watt’s steam engine (hence the dotted line dating Watt’s invention).3 And if one had to summarize the impact of the Industrial Revolution, it would be categorized as the largest boost to the human physical power; more than any other period it helped overcome humanity’s physical limitations. Yet, when analyzing why homo sapiens have become earth’s most dominant life form, many historians attribute this rise to human intelligence as expected. As the social development explosion from the Industrial Revolution’s ability to advance humanity’s physical abilities is so prominent, what would a similar advancement of humanity’s defining characteristic, intelligence, do for human development? The burning question is: are humans entering a period of transformation similar to the Industrial Revolution, but for mental capacity?
Second Machine Age Indicators
This possible rapid development of humanity is labeled by Erik Brynjolfsson and Andrew McAfee, two researchers at MIT, as the “Second Machine Age,” as they believe it holds the same magnitude as the first machine age. The first machine age was coined to define the period of development following the innovations from the Industrial Revolution becoming available to the masses, not just the elite.4 Likewise, they dubbed this potential explosion in social development the second machine age because most of the defining technologies of the 20th century, like general purpose computers, are finally reaching the masses.5 Hereafter, Brynjolfsson and McAfee’s term, the second machine age, will refer to this potential period of rapid human development for simplicity. The forecast of the second machine age is best understood by analyzing multiple economic trends of the past half-century with the two core characteristics of recent technological development.
1.1 Economic Trends
The four most cogent economic trends of the past century that evidence the second machine age are decreasing labor force participation, stagnant wages, corporations’ share of profits proportionally increasing compared to labor’s, and the declining return of a college education. The first, decreasing labor force participation, is perhaps the most persuasive, but also the most complex (See Figure 2.).
Figure 2. Labor Force Participation Rate, 16 years and older, 1948-2016
Source: U.S. Bureau of Labor Statistics.
To understand this graph, it is important to consider the demographics that factor into this statistic, which measures the percentage of employed workers in the eligible population (16 years and older). From 1970-1990, labor force participation greatly increased due to women rapidly entering the workforce. The labor force participation rate peaked at ~67% in 2000 as women participation peaked at ~60%.6 So what trends have factored into its decline since 2000? One could attribute this decline to younger workers pursuing more education or the retirement of the baby boom generation. Yet, when looking at the labor force participation rate for those aged 25-54, which excludes those groups, the statistic has declined from 84.5% in 2000 to ~81% in 2013.7 Thus, the trend is not explained by these demographic factors and there still seems to be a major economic influence missing. It stands to reason that more and better automation and artificial intelligence are driving individuals out of the labor force.
The second trend began when wages began to stagnant in 1973 and the average American worker earned $767 per week in 2013 dollars. As of 2013, using the same measure for average wages, workers’ average wages had fallen about 13% to $664.8 While the stagnation of wages is no new trend to an economy, this recent trend in the U.S. is hot topic of economic debate because it has harshly deviated from labor productivity, which measures the value of an economy’s output produced per hour by workers. As traditional economics teaches that wages should equal the output of workers, economists are puzzled by this trend.9 The graph on the next page (See Figure 3.) shows the growth of real hourly compensation and productivity and demonstrates that American wages have completely diverted from productivity since 1973.
Figure 3. Growth of real hourly compensation for production/nonsupervisory workers and productivity, 1948-2013
Source: EPI Analysis of Data from the Bureau of Labor Statistics and the Bureau of Economic Analysis.
This diversion from classical economics poses the quandary: why? While the economist community has still not agreed on any one explanation, its cause may be rooted in an increase of technology’s output in the economy. Consequently, technology would be supplementing the increased output produced by workers per hour. Technology’s increasing output may be the core factor behind the divergence as workers productivity could be remaining the same. Naturally, technology’s increases in productivity would return to the employers who own the technology while workers’ wages remain stagnant with their productivity. Again, better technology seems to be a factor behind this important economic trend.
The third trend that evidences the second machine age is corporations’ shares of profits increasing while labor’s share is decreasing. From 1947, labor’s share of the American national income had fallen from 65% to 58% in 2014.10 This downward trend has accompanied an increase of corporate profits as a percentage of national income, where over a similar period of time from 1947 to 2012 the percentage rose from 10.8% to 13.6%.11 Additionally, this is not just an American trend; economists Loukas Karabarbounis and Brent Neiman found that other economic powerhouses, like China, Germany, Japan, Canada, France, and Italy, experienced even larger declines in labor’s share of national income. Similar to the potential explanation for the trend of stagnant wages, they concluded that the decline in labor’s share was due to “efficiency gains… attributed to advances in information technology and the computer age.”12 Again, if most of the growth in productivity is due to technology, then corporations would collect the bounty from increased productivity. This would contribute to their growing share of profits.
The last trend, the decreasing return on investment in a college education, is most closely indicated by the declining incomes and underemployment of college graduates. Throughout 2000-2010, and beginning before the Great Recession, incomes for young workers with a bachelor’s degree decreased by almost 15%.13 Furthermore, new college graduates have difficulty finding meaningful work as approximately half are “unable to find jobs that utilize their education.”14 Even though the common conception that a college education provides more income holds, these trends suggests that the economic value of a college education is decreasing.  When analyzed with the consideration of the second machine age, this poses an interesting association. Assuming society is beginning a period where technology is providing a huge boost to collective mental abilities, isn’t it likely that the economic benefits of the primary way to increase intelligence are decreasing?
1.2 Other Possible Explanations
While it is impossible to understand all causes behind these four trends, economists are discovering that technology contributes, sometimes more than any other factor. But to acknowledge naysayers, it is important to mention other factors that also may contribute to the trends: globalization, financialization, and politics. Globalization is a factor in the first three trends as it has contributed to the percentage of U.S. manufacturing workers decreasing from >30% in the 1950s to <10% in the 2010s.15 Yet, the total inflation-adjusted value of American manufactured goods has risen in the same period. The best explanation for more goods created by fewer workers is better technology. The next factor, the growth of the financial sector, is a portion of the economy that has drastically grown from 2.8% of America’s GDP in 1950 to 8.7% in 2011.16 As many economists have found strong associations between financialization and a decline in labor’s share of national income, it seems reasonable to conclude that financial sector growth contributed to that trend.17 But, further analysis of the financial sector reveals that much of its growth is due to accelerating technology. From data science decision making to increased consumer participation in investments to better investor and entrepreneur connectivity, technological innovation has enabled much of the industry’s growth.18 Lastly, political decisions, stemming mainly from the enormous influence of business interests, could factor into the second and third trend. But, corporations’ rise in political power also occurred as, even perhaps because, the influence of organized labor drastically decreased. The declining power of organized labor can be attributed to the declining ability of workers to seize the fruits of growing productivity.19 As discussed above, workers’ stagnant wages is directly linked to technology’s increasing productivity. Therefore, is politics really contributing to these trends? As well written by futurist Martin Ford:
“If a nation fails to implement policies designed to mitigate the impact of structural changes brought on by advancing technology, should we label that as a problem caused by technology, or politics?”20
A closer analysis of globalization, financialization, and politics indicates that their effects were amplified by advancing technology. Though that may seem like an oversimplification, it is clear that consistently upgraded technology is a constant in all three explanations.
1.3 Technology’s Characteristics
Complementing these economic trends in their evidencing of the second machine age are the characteristics of recent enhancing technology, specifically its exponential and digital nature. The first and most powerful of these two traits is the exponential nature of technology. Without exaggeration, the most famous prediction in the field of computer science is Moore’s Law. In 1965, Gregory Moore predicted that the number of transistors on a computer chip will double every year. The number of transistors on computer chip directly correlates to computer power, so his bold prediction was that computing power would grow exponentially.21 Remarkably, over 50 years from his prediction, the doubling of transistors on a computer chip has occurred approximately every 18 months.
Figure 4. Moore’s Law: Transistors Per Microprocessor
Source: Karl Rupp, 40 Years of Microprocessor Trend Data.
This graph of Moore’s Law (See Figure 4.) shows transistors per microprocessor, basically computing power, on the y-axis and demonstrates the pace at which exponential curves grow (notice that the y-axis’ scale is logarithmic). Subsequently, Moore’s Law explains the bewildering increases in computing technology. In 1997, the ASCI Red’s computing power, which was introduced as the fastest supercomputer in the world in 1996, reached 1.8 teraflops. It cost $55 million, occupied 1600 ft2, and used as much power as eight hundred homes. In 2006, the Sony PlayStation 3 was introduced; it too had a computing power of 1.8 teraflops.22 Further highlighting Moore’s Law’s significance is the transition of analog sensors to digital sensors. Many analog sensors, like microphones or cameras, transitioned to digital, which subsequently subjected them to Moore’s Law. Because previously analog sensors now follow the exponential improvement predicted by Moore’s Law, there are now smartphones with cameras that take 48-megapixel photos.23 As increasing amounts of technology becomes digital, exponential growth will further expand to formerly analog devices. Enhancing technology is spearheaded by its exponential growth, and because of the nature of exponential growth, technology’s abilities can change a heartbeat.
The digital nature of technology is the second major force that drives its rapid development. This force gives digital technology two extremely powerful economic properties: it is non-rival and has almost zero marginal cost of reproduction.24 In contrast to almost all physical goods, digital goods are non-rival, which means they are not used up when used. For example, if two friends want to separately listen to “Sicko Mode,” a song by rapper Travis Scott, they can both “consume” the song. This differs from the average, rival physical good because they cannot both “consume” the same sandwich from Subway or the same gas from Exxon. The second trait of digital goods, which gives them vast economic abilities, is that the cost of marginal reproduction is nearly zero. This means that though it may cost a lot of time, effort, and money to make the first copy of “Sicko Mode,” it costs Travis Scott basically nothing to sell additional copies. Principally, the increasing amount of digital goods can be instantly and perfectly replicated for free. Applying this concept to future machines and software applications that could replace human work holds shocking implications. If a software engineer creates an application that writes better quarterly company reports than humans, it won’t be long before all companies buy that application and replace all quarterly report writers with it. Digitalization complements exponential growth to further accelerate the effects of technology on the world by allowing society to effortlessly and perfectly replicate its ideas, insights, and innovations.
2. Implications
The indicators of the second machine age point to a revolutionary future transformation of work but provide no concrete evidence of technology currently replacing work. While one can speculate on the future of work, the evidence of the second machine age is already present. Seemingly futuristic technologies are already replacing both high and low skill jobs in economies around the world. The second machine age is already happening and is transforming society.
2.1 Low-skill Jobs
With the advent of more multifaceted and smarter robots, low-skill workers are finding their jobs increasingly threatened. Low-skill work is a segment of the workforce characterized by requiring a lower skill set, often times correlating with lower educational requirements and wages. One of the clearest examples of low-skill job displacement is in the manufacturing industry. As most Americans know manufacturing unemployment in the U.S. has continually fallen over the past twenty years. But what most may not know is that this decline is not due to increasing non-domestic manufacturing in countries like China. In fact, though economists have estimated that about a quarter of the employment decline is from China’s competition, China is encountering a similar situation.25 From 1996 to 2014, manufacturing employment in China has fallen approximately 25% while their manufacturing output has increased.26 Both America and China are producing more manufactured goods with fewer workers due to expanding automation.
This drop in manufacturing is mainly due to the proliferation of robots. Currently, robots are experiencing a structural transition; instead of companies employing specialized robots to manufacture goods, they are using general purpose robots like Baxter. Baxter is one of the first general purpose robots. Rethink Robotics, Baxter’s manufacturer, claims that Baxter is “the first safe, flexible, affordable alternative to fixed automation.”27 Baxter is easily taught to perform an infinite amount of tasks to replace humans. Though Baxter may not be as quick as a human worker, he is much cheaper and never gets sick, complains, or pauses working. Simply put, Baxter is better. When general purpose computers first were introduced to the masses, they quickly transformed society and now are used to check out customers at a grocery store and buy clothes online. Similar to general purpose computers, general purpose robots are already transforming industries by displacing low-skill workers.28 The robot future is now.
While manufacturing is one low-skill profession currently being decimated by automation, another industry poised to be disrupted is the transportation industry. The advent of self-driving cars will rapidly revolutionize the transportation sector. As of 2013, Google’s autonomous car fleet had driven over 300,000 accident-free miles and a company report from the same year showed that their cars consistently had better “general defensive driving practices” than the average human driver.29 Vehicle automation has progressed so fast that in 2018, another large player in the autonomous driving race, Tesla, has reached over 1 billion miles driven by their Autopilot feature.30 Tesla already claims full-self driving capability, though its release “is dependent upon extensive software validation and regulatory approval, which may vary widely by jurisdiction.”31 Furthermore, as with Baxter only having to be better than a human manufacturer, autonomous vehicles only have to perform better than human drivers. Since over 90% of accidents occur due to human error and self-driving cars don’t blink, sneeze, get sleepy, and drink and drive, human drivers shouldn’t be too hard to beat.32 Self-driving cars are not a sci-fi fantasy, they are here now and will become common over the next few years. As the transportation industry has the largest number of employed workers, it will be one of the first major industries affected by the second machine age.
2.2 High Skill Jobs
Comparable to robots’ impact on low-skill work, the rise of artificial intelligence has and will continue to displace high-skill professions like stockbrokers and doctors. In fact, because white-collar jobs are more expensive and numerous, the incentive to replace them is even higher. Just as the manufacturing industry workforce has been decimated due to robotics’ advancement, there is a similar progression with artificial intelligence’s effect on stock trading. This is clearly evident by a quick glance at the floor of the stock market today. Twenty years ago, there were constant trades happening across the entire stock market floor, but now, it is a glorified TV set. So what happened? It is estimated that automated trading algorithms make up over two-thirds of trades, while the average time to execute a trade fell from about 10 seconds in 2005 to just 0.0008 seconds in 2012.33 Trading stocks went from a human profession to artificially intelligent bots trading with other artificially intelligent bots.
Analogous to the coming disruption of the transportation industry by self-driving cars, doctors too will soon be augmented and perhaps replaced by artificially intelligent systems. IBM’s Watson, the supercomputer project that routed the best Jeopardy players on the nationally televised show, is currently being transitioned to become the best doctor in the world. Currently, IBM is attempting to turn Watson into an “interactive advisor capable of recommending the best evidence-based treatment options, matching patients with clinical drug trials, and highlighting the possible dangers or side effects that might threaten specific patients.”34 Watson, unlike any human, can understand and access any combination of the thousands and thousands of pharmaceutical drugs while at the same time processing all previous and current medical research (one study estimates that a doctor would have to spend ~160 hours a week just to keep up with current research).35 Furthermore, healthcare needs innovation as there are ~100,000 deaths every year in the U.S. attributed to preventable medical errors.36 It would be quite far-fetched to suppose that Watson is going to replace most doctors in the near future, but it seems clear that increased artificial intelligence in the medical field will decrease the work of doctors, perhaps potentially lowering the educational requirement to become a doctor.
From studying the industries and professions that are currently and projected to be affected by increasing automation and artificial intelligence, it seems clear that job automation is directly correlated to its predictability. The more predictable, the easier to automate. This means that while low-skill, blue collar jobs may be the easiest to automate, high-skill, white collar jobs are not far behind. Automation and artificial intelligence are only improving and seizing more jobs as they do.
2.3 Job Creation
In light of the prior conclusions, it is important to ask: though technology is replacing old jobs, won’t it also create new jobs and industries not accounted for? To some extent, reasoning along this thought process is correct. Technology will continue to create new jobs as it always has, most of those jobs involving the combination of humans and artificial intelligence. Perhaps the best example of this comes from the ancient game of chess. In 1997, the world champion Garry Kasparov was beaten by IBM’s Deep Blue computer in a six-game series and it appeared that technology had surpassed humans. Now, there is no chess player who could beat even the average computer at Chess. But, with the invention of freestyle chess tournaments, where teams can be made up of multiple computers and humans, an interesting phenomenon has been observed. In 2005, one of the first freestyle tournaments was not won by a supercomputer, grandmaster, or some combination of the two, but by two amateur chess players with three computers. As Kasparov said, it seemed that a “weak human + machine + better process was superior to a strong computer.”37 Perhaps job creation in the future will be similar, benefiting those best at working with computers. Could technology create enough new jobs to offset its job elimination?
Realistically, the research indicates a different conclusion. Supposing that new job creation will be able to offset old job creation seems naive when looking at the current and past jobs tracked by the U.S. census. Sorting the list by amount of people, the list is relatively unchanged. Specifically, comparing the past census with one a century old, it is not until #33, computer programmers, that a brand new job has been created. The current jobs tracked by the census existed in one form or another a century ago.38 The reality is that there will not be that many jobs created in the second machine age; humans are already really good at meeting their needs.
Recently, most economists have strayed from concluding that technology is a net job destroyer, because this concept, the “Luddite Fallacy,” is often considered to contradict traditional economics. In light of foregoing evidence, maybe now is the time to question the common conceptions of economics. For example, consider the position of horses after the invention of the automobile. Up until that point, technology had continually made their lives better. Earlier, they were forced to farm, deliver mail, and go to war, but around the invention of the automobile, they had their best jobs to date, pulling carriages. If there was an economist horse, they probably would conjecture that technology consistently makes their lives better and the new automobile would follow that trend. But as summarized by the YouTube channel CPG Grey, “there isn’t a rule of economics that says ‘better technology makes more better jobs for horses.’”39 Hopefully, most people can understand that this rule sounds silly. The invention of the automobile replaced almost all horse-drawn carriages; now horses are rarely employed and the population of their species peaked in 1915.40 Not only are horses unemployed, they are simply unemployable. Yet, when examining that supposed rule, somehow it is a common belief that replacing “horses” with “humans,” “better technology makes more better jobs for horses humans,” makes it a sacred economic principal. Like horses and anything with a specific skill set that provides economic value, humans too could become unemployable when that skill set is no longer needed.
3. Future of Work
With the advent of the second machine age, society is going to enter an extreme transitional period. Carl Frey and Michael Osborn, two Oxford professors, estimated in a 2013 study that 47% of U.S. jobs are at risk of being automated in the next two decades.41 Diving further into this concept, look again at the list of jobs tracked by the U.S. census. Looking at the list of the top 10 most employed jobs tracked in the last census (consisting of the occupations of transportation, retail salesperson, first line supervisors, cashiers, secretaries, managers, sales representatives, registered nurses, elementary school teachers, and janitors/cleaners), reveals that these main 10 professions make up 45% of America’s workforce.42 Even if only a small part of these jobs become automated, it could cause mass unrest. To put the situation into perspective, the highest rate of U.S. unemployment was 24.9% in 1933 during the Great Depression.43 Even if Frey and Osborn’s prediction is an overestimate, the U.S. is still facing a potential disaster and permanent societal transition.
3.1 Future Work
It is difficult to hypothesize on the nature of work with future mass unemployment, but in “A World Without Work,” Derek Thompson raises some likely possibilities. In this article, Thompson examined the city of Youngstown, Ohio which entered a regional depression in 1977 due to the closing of a prominent steel mill. As a result of the economic depression, Youngstown also entered a “psychological and cultural breakdown” from the lack of employment.44 Thompson traveled there to investigate the future of work as “Youngstown has become a national metaphor for the decline of labor, a place where the middle class of the 20th century has become a museum exhibit.”45 Through interviews of the residents and speculation about the future, Thompson theorizes that a future of joblessness will be accompanied by daily life divulging into leisure, creativity, and contingency. Leisure would be the largest consumption of time where people explore their freedom from work by consuming goods, but it lacks work’s fulfilling sense of purpose. That is why he believes it will be accompanied by creativity and contingency. Society will explore their creativity through art, music, and education. People still can feel a sense of purpose from creating something that is uniquely theirs or by learning something new. Perhaps higher education will revert from a requirement for a white-collar job back into a center of culture. Lastly, contingency is reserved for time spent fighting to reclaim lost professions. Though one cannot completely predict future substitutes for work, it does seem that work will be replaced by some combination of leisure, creativity, and contingency.
3.2 Good or Bad?
As society approaches this transitional point in human history, there are many reasons to doubt humanity’s ability to conquering mass unemployment. Technology is accelerating faster than comprehension, maybe faster than society can adjust. As Voltaire said, “work saves a man from three great evils: boredom, vice, and need.” Will humanity’s vices empowered by an absence of work prove too great to overcome? Ford believes that humanity may be facing a “perfect storm” where humans are going to be afflicted by technological unemployment along with other major problems of the 21st century, like climate change. This perfect storm may be impossible to navigate. In acquiring technology’s great power, humans have also given themselves a great responsibility.
Nevertheless, I am optimistic about the second machine age. I believe we can navigate the road ahead to continue to better our entire species. Yes, it seems like more and more are not getting their fair slice of the pie, but the pie is also constantly increasing. I believe the ultimate challenge arises in making sure everyone gets a fair slice of that pie. Though the sooner society accepts the advent of this transition, the earlier we can adjust and prepare for the outcome. We can use the advancement and acceleration of automation and artificial intelligence to create a more prosperous society. Our history shows that on average humans continually enjoy more wealth, “more freedom, more social justice, less violence, and less harsh conditions for… more and more people” than ever before.46 I agree with Brynjolfsson and McAfee in their belief that a specific quote overrules Voltaire’s pessimistic logic.
“The arc of the moral universe is long, but it bends towards justice.” – Martin Luther King, Jr47
4. How to Transition
Though progress towards a future of technological unemployment seems uncontrollable, it does not prescribe any one destiny. Society can drastically alter the outcomes of the machine age. America’s laws and policies have an enormous impact on technology’s future. In “Artificial Intelligence, Automation, and the Economy,” a report released by the White House in 2016, three broad strategies are suggested for managing the impact of technology on the U.S. economy.48 While these strategies are later rephrased and altered, their core values ease the transition from the second machine age.
4.1 Continuing Technological Advancement
If the U.S. decides that the second machine age is beneficial, it must continue to invest in automation and artificial intelligence to stay on innovation’s cutting edge. Through this investment, America can further accelerate its productivity and output as a nation, while continuing to “maintain the strategic advantages that result from American leadership in AI.”49 Firstly, this should stem from increasing scientific funding, specifically federal funding for AI research. Though federal support for scientific funding continually rose in the decades prior to 2005, since that year, support for basic academic research has continually fallen.50 Many of America’s great innovations originated from government funding for research; not investing could push the country away from its world position as a frontrunner in technology. Secondly, the U.S. must upgrade its infrastructure to support the entire economy. In 2013, The American Society for Civil Engineers summarized America’s infrastructure in the form of a report card. They assessed the U.S.’s overall infrastructure as a D+ and estimated a necessary investment of $3.6 trillion by 2020.51 In order to keep up with the continually increasing output in sectors like manufacturing, America’s infrastructure needs to be modernized. Analogous to research, the positive externalities of infrastructure are too beneficial to ignore. Lastly, it is important to develop a more diverse technologically savvy workforce. Research has shown that “diverse groups are more effective at problem solving than homogeneous groups,” and policies that strive for this goal will aid technological advancements.52 One example of the innovative power of diversity is how over half of Silicon Valley startups from 1995 to 2005 had at least one immigrant founder.53 Overall, by pursuing increased investments in research, infrastructure, and diversity, the U.S. can continue to be at the forefront of technological advancement and capture the bounty of such advancements. The biggest concern about AI may have been correctly stated when Jason Furman, the former Chairman of the Council of Economic Advisors, said his biggest worry is “that we do not have enough.”54
4.2 Bettering Education
The second main goal in ensuring success for the upcoming transition should be to increase the abilities of all Americans through education. While this starts with better educational opportunities for children, it also involves retraining adults for a shifting economy. Much of the economic growth of the 20th century can be attributed to America’s premier primary education; in 1955, nearly 80% of fifteen to nineteen-year-olds were enrolled in high school, which was more than twice the rate of any European country.55 Currently, America’s educational system is ranked about average for developed countries with fifteen-year-olds ranking 14th in reading, 17th in science, and 25th in math out of 34 countries.56 The U.S. needs to address these low levels of proficiency by supporting policies that push for all children to have access to high-quality education. This is vital as those with lower levels of basic skills are at a higher risk of displacement.57 In order to continue the economic growth of the 20th century, America needs better basic educational opportunities. Secondly, the issue of retraining workers must be addressed. Because the economy and its jobs are rapidly becoming more technical, displaced workers should be assisted in pursuing different types of employment. Increasing technological literacy through training and retraining increases displaced workers’ involvement in the economy. Recently, these training programs have experienced a decline in federal funding as the U.S. only spends half as much as 30 years ago, relative to the overall economy.58 Increasing education opportunities for all Americans will increase the participation of future workers and displaced residents in the future economy.
4.3 Ensuring Shared Growth
Even though this paper is intended to be apolitical, this section may appear biased. This is coincidental. In fact, though some of the proceeding solutions are politically radicalized, they are simply possible solutions. In this upcoming transition, society must separate from divisive politics and unite to find solutions.
In sum, the biggest and most apparent challenge posed by the second machine age originates from its ability to increase the overall bounty. As discussed before, corporations have received larger percentages of net income in the U.S. while labor’s share of this income is decreasing. This partially results from corporations collecting most of the returns of increasing productivity; so as productivity continues to increase, the wealth of corporations also does. Since 84% of stocks are owned by the wealthiest 10% of America, the wealthiest Americans will continue to collect a majority of the bounty from the second machine age.59 This further exacerbates growing economic inequality. Though income inequality is a common trend in recent American history, as of 2015, Americans in the top 1% averaged over 40x more income than the bottom 90%, and the inequality is accelerating.60 Over half of the increase in national income from 1993-2010 has been collected by the top 1% in income distribution and after the Great Recession, from 2009-2012, 95% of the income gains went to the richest 1%.61 As labor collects less and corporations accumulates more, so do the rich become richer and everybody else becomes poorer. Income inequality is further aggravated by continuing technological unemployment as the wealthy’s income will persist while all others’ income slowly disappears. There is no reason to expect this trend to end so correctly proceeding forward with inflating economic inequality and citizens who are unemployable through no fault of their own is vital.
Some suggestions from that same White House report seem to be simple and relatively moderate solutions to growing income inequality. These consist of strengthening unemployment insurance, raising the minimum wage, fortifying the safety net, modernizing overtime, and bolstering unions and workers’ power.62 While this list offers a good start, America should consider more permanent changes. Providing free access to higher education would better prepare workers for the changing economy, thus addressing the second strategy (4.2 Bettering Education). It would also help rectify the collective $1.5 trillion of student debt, which burdens the bottom of the economic spectrum the most.63 As job-based health plans cover almost 56% of Americans, a public option or single payer healthcare system should be considered.64 Then, if mass unemployment occurs, Americans don’t lose their healthcare with their jobs. Additionally, as workers drive consumption in the economy, they must retain the ability to consume. A universal basic income or negative income tax are simple policies to ensure worker purchasing power and consequently, a healthy economy. The implementation of some of these may originally appear implausible, but radical solutions could become necessary to prevent unrest from mass unemployment.
5. Conclusion
The amalgamation of recent technology’s exponential and digital nature with several economic trends suggests that society is entering a period of massive economic growth. Because this growth originates from the increasing quality and implementation of automation and artificial intelligence in the economy, it will continually decrease overall participation in the workforce. Thus throughout the next century, individuals’ time will increasingly be spent on leisure, creativity, or fighting for their lost jobs. The subsequent mass unemployment can be assisted through continuing technological advancement, improving education, and implementing policies that ensure broadly shared growth. Mass unemployment will likely be one of the largest problems humans face in the upcoming century, but it is society’s responsibility to determine its impact on society. As Derek Thompson wrote: “Perhaps the 20th century will strike future historians as an aberration, with its religious devotion to work in a time of prosperity.”65 Humanity must decide how to proceed while progressing into this period of unprecedented opportunity and freedom.