Technological Unemployment Essay

Abstract

“We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come – namely, technological unemployment” stated John Maynard Keynes in 1930 [1]. In 1950, Norbert Wiener “saw the possible end to full employment and the obsolescence of all but a small fraction of the workforce because of computers” [2]. Both aforementioned quotes speak about unemployment and technology on a broader scale. But, is technology truly taking away jobs? Is technological unemployment, a fact? Or are we getting succumbed to the ease of technology that we let technology control us? Technological advancements do result in unemployment, but this does not apply to all. It applies to those low-skilled workers, who live in underprivileged areas, to whom newer technologies and upskilling are inaccessible. This is where inequality comes into the picture. In short, technology and automation are perpetuating inequality by depriving the lower socioeconomic groups, of their jobs. In this paper, I examine the truism behind technological unemployment and who is affected by advancements in technology.

Introduction

Imagine going to a restaurant to be welcomed and served by a robot. Once upon a time, this had to be just dreamt of but now it is reality. University of Berkley, California campus uses “Kiwi bots” which are mobile robots, to serve fast food to students [3,6]. Robots delivering food shows how technological advancements are taking over human jobs. But the hidden truth is that every 5-10 seconds, a worker sitting in Colombia feeds the bot with directions [3,6] while on the outside we believe the smart bot uses artificial intelligence (AI) to navigate. Does this mean robots are not taking over jobs, but instead opening up opportunities? Perhaps not! While a highly skilled worker, like the one in Colombia, has a job to work with the bot, multiple low-skilled workers (who would have worked to manually serve the students) might have lost their jobs. Martin Ford, in 2013, rightly quoted this by stating, “A substantial fraction of moderate wage, routine jobs in areas like manufacturing and white-collar clerical occupations have been eliminated by technology, leaving the remaining employment opportunities clustered at the top (high-wage/high-education jobs)…” [4]. Technological unemployment, thereby, is a fact, but the ones affected are those from a lower socioeconomic background, who are deprived of upskilling opportunities.

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Technological Unemployment

In Keynes's words, technological unemployment can be defined as “Unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor” [1, 3]. In simpler terms, technological unemployment means job loss that is caused by advancements in technology. Keynes coined this term in 1950 and it remains valid even today. From the decrease in farm workers between 1947 and 1965, owing to technological changes that made output increase [2] to the “Pepper” robots that replaced sales workers recently, to take over a Softbank cellphone shop in Tokyo [8], unemployment due to technological developments has been recurrent. As a result, people are struck by “Automation Anxiety” – “anxiety about the potential job-destroying rise of automation” [9]. However, there have been reports of how some believe that technological unemployment is a myth because “There isn’t much evidence that it’s happening” [10]. In Sweden, for instance, a survey showed that 80% of Swedes have positive views about AI and automation. On the contrary, a different survey found that 72 % of Americans seem to be expressing automation anxiety [9]. The ultimate question is, what is to be believed? Is technological unemployment a myth or is it truly affecting everybody? And the answer is that technological unemployment is indeed affecting, not all, but those low-skilled workers thereby making changes in technology, skill-biased.

What is Skill Biased Technological Change?

“A burst of new technology caused a rise in the demand for highly skilled workers that in turn led to a rise in earnings inequality -- has become known as the Skill Biased Technical Change (SBTC) hypothesis” [7]. Precisely, advancements in technology favor highly skilled workers. In other words, automation replaces routine tasks that are otherwise accomplished by low-skilled workers, resulting in their job loss. For instance, let us assume Taxicabs of New York being replaced by driverless “Robo Taxis”. This would result in job positions being opened for highly skilled workers like engineers for routine maintenance of the taxis. The downside? Every taxicab driver in New York would end up jobless! And it might be way too late for them to enhance their digital skills to get back to the booming technological market. “Far from being a destroyer of jobs, therefore, what technology does seem to do is help inequality between those with skills and those without” [5].

Technology and Inequality

“The recent Inequality literature reaches a virtually unanimous agreement that during the 1980s the relative demand increased for workers at the high end of the skill distribution [and this caused] earnings inequality [to] increase” [7]. Inequality regarding technological advancements can be described by how changes in technology are biased towards the high-skilled workers and how, as a result, low-skilled workers end up losing their jobs or end up being paid low wages. According to the National Bureau of Economic Research (NBER), “the major driving force behind the changes in the U.S. wage structure is technology…technical change favors more skilled (educated) workers, replaces tasks previously performed by the unskilled, and increases the demand for skills” [11]. The quotes extracted from NBER pretty much sum up how technology perpetuates inequality i.e., by providing more opportunities to the high-skilled workers and thereby putting the low-skilled worker’s jobs at risk. Further, technological innovations are directed towards efficiency (by automating routine tasks performed by multiple low-skilled workers) and profits. As a result, organizations are prepared to pay high-skilled workers (as much as they demand) while they hardly pay anything to the low-skilled workers.

Is there a fix?

There is no definite answer to this question. While we know that technological innovations are aimed towards making lives easy and increasing economy and wealth, we barely notice that their positive effects are directed only toward highly skilled workers and the ones higher on the ladder, within an organization. In other words, the ones reaping the benefits of technological advancements are doing so, at the cost of jobs and wages of workers from lower socio-economic backgrounds. Fixing this issue would require the government and organizations to take measures to assist low-skilled workers in developing their skills. As a designer, I would try to fix this issue by designing technological artifacts that are easy to use, thereby requiring minimum skill enhancements, to work with.

Conclusion

Technology is evolving by the day and automation has made our lives easy. As stated by Ekbia & Nardi “heteromation has provided a new logic and mechanism for wealth accumulation” [3]. However, along with the positive changes, technological advancements do bring negative effects on the lives of people from lower socio-economic groups. Technological unemployment, up to some extent, can be proven true, by stating examples from the lives of several low-skilled workers/low-paid workers. While improving the country’s economy is of prime importance, it is also equally important to ensure that there is social equality.

References

1. John Maynard Keynes, Essays in Persuasion, New York: W. W. Norton & Co., 1963, pp. 358-373.
2. A. Borodin and C. C. Gotlieb. 1972. Computers and employment. Commun. ACM 15, 7 (July 1972), 695-702. DOI: http://dx.doi.org/10.1145/361454.361530
3. Ekbia, H. R., & Nardi, (2019). B. A. Keynes's Grandchildren and Marx's Gig Workers: Why Human Labor Still Matters. International Labour Review.
4. Martin Ford. 2013. Could artificial intelligence create an unemployment crisis? Commun. ACM 56, 7 (July 2013), 37-39. DOI: https://doi.org/10.1145/2483852.2483865
5. https://www.forbes.com/sites/adigaskell/2019/05/03/technology-isnt-destroying-jobs-but-is-increasing-inequality/#5c08be895e78
6. Said, C. 2019. “Kiwibots win fans at UC Berkeley as they deliver fast food at slow speeds”, in San Francisco Chronicle, May 26. Available at: https://www.sfchronicle.com/business/article/Kiwibots-win-fans-at-UC-Berkeley-as-they-deliver-13895867.php [accessed 6 Aug. 2019].
7. David Card & John E. DiNardo, 2002. 'Skill-Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles,' Journal of Labor Economics, University of Chicago Press, vol. 20(4), pages 733-783, October.
8. https://medium.com/new-tech-revolution-sciencespo/technological-unemployment-why-this-keynesianism-term-is-more-than-ever-up-to-date-479a31d5592d
9. https://www.nytimes.com/2017/12/27/business/the-robots-are-coming-and-sweden-is-fine.html
10. https://www.wired.com/2017/08/robots-will-not-take-your-job/
11. https://www.nber.org/reporter/winter03/technologyandinequality.html