This article is one of the foundational literature in the field of technology and labour. Most of the literature I have reviewed had the name of this author and this article as an important reference text. The article helped me to navigate through the diverse correlations between different sections of labour, different automation, and technological interventions. A holistic view of labour with regard to production patterns and technology lead us to the hidden social, economic and political factors involved in it. In fact, the graveness of the mistakes I always commit was reminded by the author. Totally speaking, the author's argument of heterogeneous labour and technology that must be understood in the context of time and space is sensible along with his empirical evidence. This study gives us a basic analytical tool and cautions us about the inevitability of influence by popular notions.
I. Automation and impact upon middle range service sector jobs: The paper gives an idea about how labour is heterogeneous in the context of automation. It helps me for further studies upon service sectors, especially upon the software workforce and the anticipated effect of automation. It also draws insights upon how technology helps them through complementing the labour.
II. It is very interesting to have a look into the argument of job polarisation and how technology, as one among the causal factors to deprive the labour, their chance for better wage and opportunities to work. The results may be different in different sections of labour, the author also argues that there are not many studies on how technology is mediating and complementing the jobs rather than substituting it. Hence this also should be looked into by future researchers.
III. The process of deskilling of labour (Braverman,) and its correlation to the technology should be examined thoroughly. The impact of skill and its possession is one of the reasons led to the polarisation of jobs. The engagement of automation with different skill sets give different results. So it is better to study how manual skilling or low skilled is not automated but sent to countries like India and other third world nations under the branding of offshoring. For example, the garment industry in Bengaluru is exporting the offshored business by multinational brands like Lewis, Arrow etc
The author mainly derives the concepts and ideas mainly from his own previous essays, articles etc.
I. “Acemoglu, Daron, David H. Autor, David Dorn, Gordon Hanson, and Brendan Price. Forthcoming. “Import Competition and the Great U.S. Employment Saga of the 2000s.” Journal of Labour Economics.
II. Autor, David H. 2013. “The ‘Task Approach’ to Labour Markets: An Overview.” Journal for Labour Market Research 46(3): 185–99.
III. Autor, David H. 2014. “Skills, Education, and the Rise of Earnings Inequality among the ‘Other 99 Per cent.’” Science 344(6186): 843–51.
IV. Autor, David H. 2015. “Polanyi’s Paradox and the Shape of Employment Growth.” In Re-Evaluating Labour Market Dynamics, pp. 129–79. Federal Reserve Bank of Kansas City.
V. Autor, David H. Forthcoming. “The Paradox of Abundance: Automation Anxiety Returns.” In Performance and Progress: Essays on Capitalism, Business and Society, edited by Subramanian Rangan. London: Oxford University Press.
VI. Autor, David H., and David Dorn. 2013. “The Growth of Low-Skill Service Jobs and the Polarization of the US Labour Market.” American Economic Review 103(5): 1553–97 “
These are few of works he cited in his essays and articles and in the references. These form the base of his arguments. From this and his own theoretical premises, he is trying to connect broad literature and theories on automation, social philosophy of Polanay's paradox to the theories of labour polarisation.
i. Theories of automation: Through the literature review of this particular aspect, which is an alarming phenomenon across the world, he finds out that the popular notion of automation as an evil is a bubble or myth than a reality. But he has never refused the impact of such panicking or automation anxiety. Few examples of the literature he reviewed to substantiate his point are,
I. “The National Commission on Technology, Automation, and Economic Progress: Volume I.” Washington: U.S. Government Printing Office.
II. Brynjolfsson, Erik, and Andrew McAfee. 2014. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York and London: W.W. Norton & Company. TIME. 1961. “The Automation Jobless. “February 24. “
He argues that only routine tasks will be automated. Even though the humanisation of automated technology is taking place tremendously, it is difficult to modify the technology, by making it understand as we understand things. The biggest failure of technology comes from its actions which are solely oriented towards codes and patterns. The algorithms and artificial intelligence are getting better day by day. Like Virginia Eubanks argued, the technology is more grasping and improving its knowledge system on every second of data adding. But the question she raises is about 'automating inequality'? she gives plenty of examples of how machine algorithms or artificial intelligence is unable to discrete which one is a fraud and which one is genuine. The automation can detect 1000's of fraud cases in a fraction of seconds using data analysis, which a human will take one hour at best. The patterns emerging from a fraudulent account and a family with regular issues will be the same. It is the human discretion that solves the issue rather than ' red flagging ' the desperate needful people from poor sections of society (Eubanks, 2017). Autor argues that technology should not always be regarding substitution, it should be more about complementing the labour ().
ii. The social philosophy of Polanyi's paradox: This paradox is named after the philosopher, economist and scientist aka chemist Polanyi, whose valuable observation on the contradiction of human knowledge gathering and ability to express it. He observed in 1966, “We know more than we can tell” (Polanyi 1966; Autor 2015). "When we break an egg over the edge of a mixing bowl, identify a distinct species of birds based on a fleeting glimpse, write a persuasive paragraph, or develop a hypothesis to explain a poorly understood phenomenon, we are engaging in tasks that we only tacitly understand how to perform. Following Polanyi’s observation, the tasks that have proved most vexing to automate are those demanding flexibility, judgment, and common sense—skills that we understand only tacitly". When we follow the logic of Polanyi, it suggests that high-level reasoning is going to be computerized whereas certain sensory motor skills attached to the manual jobs are not.
“Autor, David H. 2015. “Polanyi’s Paradox and the Shape of Employment Growth.” In Re-Evaluating Labour Market Dynamics, pp. 129–79. Federal Reserve Bank of Kansas City.” The author already spent much time in understanding this paradox and its consequent phenomenon through another of his own book.
iii. Theories of polarisation as a consequence of what I have explained above, the Polanyi’s paradox leads to the polarisation of labour and polarisation of wages. The former stems from the automation of middle-skilled employment and people either focusing on high skilled empirical ones and lower skilled manual jobs. Autor explains that this polarisation will seize to exist in the immediate future. One of his argument is regarding how there is unemployment’s related to manual, low skilled ones and how their wages are increased after a short interval of deprivation. He also explains how abstract jobs are reduced into small circles after a prosperous period before the 1980s. He also points out to the empirical reality of how certain middle-class jobs survived the ‘onslaught (as it is perceived in the popular imagination) of automation. He assumes through his empirical analysis that these jobs like that of radiologist, nurse and other works were human sensibility is more important in decision making becomes a barrier to automation. This does not mean that these areas of employment have escaped from the grips of technology. In a different way, this section of work and its labour is complemented by technology rather than substitution. The pieces of literature that he referred to know about the process of polarisation and its impact are mentioned below;
I. “Kremer, Michael. 1993. “The O-Ring Theory of Economic Development.” Quarterly Journal of Economics 108(3): 551–75.
II. Foote, Christopher L., and Richard W. Ryan. 2014. “Labour-Market Polarization over the Business Cycle.” Public Policy Discussion Paper 12-8, Federal Reserve Bank of Boston, April.
III. Goos, Maarten, and Alan Manning. 2003. “Lousy and Lovely Jobs: The Rising Polarization of Work in Britain.” Center for Economic Performance Discussion Papers DP0604, December
IV. Goos, Maarten, and Alan Manning. 2007. “Lousy and Lovely Jobs: The Rising Polarization of Work in Britain.” Review of Economics and Statistics 89(1): 118–33.
V. Autor, David H., Lawrence F. Katz, and Melissa S. Kearney. 2006. “The Polarization of the U.S. Labour Market.” American Economic Review 96(2): 189–94”.
"What explains the slowing growth of abstract task-intensive employment? One interpretation is that automation, information technology, and technological progress, in general, are encroaching upward in the task domain and is beginning to substitute strongly for the work done by professional, technical, and managerial occupations. While one should not dismiss this possibility out of hand, it does not fit well with the pattern of computer and software investment. If information technology is increasingly replacing workers high in the skill distribution, one would expect a surge of corporate investment in computer hardware and software. Instead, data from early 2014 shows that information processing equipment and software investment was only 3.5 per cent of GDP, a level last seen in 1995 during the outset of the “dot-com” era.
I. Humanistic approach - non-routine tasks: most people look on to work as monotonous, impersonal, regular works. But before the onset of these works, there were works which were atypical to democratized routine works. For example, a medical nurse who needs to give doses of medicine should use her immediate discretion power of whether to use it or not in an already sedated patient. Even though he/she might think about her work as something routine, it is not always a pre-planned setting, where automated machines can apply their coded response. “Computers largely substitute for routine tasks, how do we characterize the no routine tasks for which they do not substitute?"
In Autor, Levy, and Murnane (2003), they distinguish two broad sets of tasks that have proven to be stubbornly challenging computerization. One category includes tasks that require problem-solving capabilities, intuition, creativity, and persuasion. These tasks, which we term “abstract,” are characteristic of professional, technical, and managerial occupations. They employ workers with high levels of education and analytical capability, and they place a premium on inductive reasoning, communications ability, and expert mastery.
The second broad category includes tasks requiring situational adaptability, visual and language recognition, and in-person interactions—which we refer to as “manual” tasks." Both of these extreme ends of the labour spectrum shows the diverse characteristics in it, and how they respond to automation and other accused technologies supremacy. The author also opines that this polarisation will not exist for a longer period. The prosperous period for abstract, high skill jobs in the one end of the spectrum are getting complimented by the technology and the low- skilled, manual works are overflowed from the supply of labour force, who were belonged previously to the middle range, mediated jobs such as office staffs and clerks. It is also important to note how much per cent of the labour force was previously working in this post-world war middle range service sector jobs or before the advent of the so-called technological interventions and automation. The increased accessibility and lowered skills make the lower stratum of work called manual works became a "daunting challenge for automation" in the US labour markets.
II. The over-emphasis upon literary tools in social sciences such as postmodernism and post-industrial society, had hidden the empirical truth upon production? Does production really cease to exist? As David Harvey noted in his book 'Spaces of capitalism’ (2001), the biggest advantage of capitalism is its flexibility and that the opposition to this is highly fragmented and not united. Clearly depicting a Marxist interpretation. But when we look deeper into the strategy of capitalism, behind the boogeymen of globalization and technological digital world, the real production became an invisible project. Theoreticians are contesting upon whether our society is passing through modernity or postmodernity, but the basic empirical scene is yet hidden under the name of the automation. The author argues that most of the semi-skilled and skilled jobs are offshored to the 'third world ' where the labour and resources are cheap. This shows that there are many factors apart from the influence of technology and automation which causes the reduced number of jobs in North America and the European Union. As noted earlier," technological change is far from the only factor affecting US labour markets in the last 15 years. For example, the deceleration of wage growth and changes in occupational patterns in the US labour market after 2000, and further after 2007, is for sure associated to some extent with two types of macroeconomic events. First, there are the business cycle effects—the bursting of the “dot-com” bubble in 2000, and the collapse of the housing market and the ensuing financial crisis in 2007–2008—both of which curtailed investment and innovative activity. Second, there are the employment dislocations in the US labour market brought about by rapid globalization, particularly the sharp rise of import penetration from China following its accession to the World Trade Organization in 2001 (Autor, Dorn, and Hanson 2013; Pierce and Schott 2012; Acemoglu, Autor, Dorn, Hanson, and Price forthcoming,)
According to the author this 'multidimensional complementarity among causal factors' leads to a faraway conception of single and pure reason for job losses and shift in production paradigm.
The Polanyi's paradox and automation: The social philosopher Polanyi’s idea of our inherent inability to express completely on the matters we know is used by the author to explain how certain ideas upon discretion and aesthetic knowledge cannot be translated and being unable to be expressed into the language of technology. "Polanyi's paradox—“we know more than we can tell”—presents a challenge for computerization because, if people understand how to perform a task only tacitly and cannot “tell” a computer how to perform the task, then programmers cannot automate the task—or so the thinking has gone to one." As an impartial researcher, the author gives accounts of how technology “through a process of exposure, training, and reinforcement, machine learning algorithms may potentially infer how to accomplish tasks that have proved dauntingly challenging to codify with explicit procedures(). But, “an irony of machine learning algorithms is that they also cannot “tell” programmers why they do what they do. “He gives examples of google car and automation programs started by Amazon and how they paradoxically highlighted the limitation of technology to accomplish certain non-routine tasks where the capacity of 'human ingenuity' is integral in removing such obstacles and ‘reengineering the environment' while the particular tasks are accomplished. He also argues that " the issue is not that the middle-class workers are doomed by automation and technology, but instead that human capital investment must be at the heart of any long-term strategy for producing skills that are complemented by rather than substituted for"
The main theme of the article is its focus on how certain popular notions regarding technology and labours and its linear correlation are misleading towards certain assumptions in academia. The emphasis put upon technology destroying labour opportunities is critically evaluated in the text. The main argument of the article is that technology is not antithetical to labour power. In most cases, it complements the existing structure of labour. A cause and effect analysis of technologies related to production and labour gives a picture of how automation swept out most of the jobs. The author argues that it is one of the factors that determine the production, labour cost and employment opportunities. There are many social, political, economic and cultural factors which determine the pattern of employment, production and nature of work. These factors do vary across different sections of labour. From high skilled abstract jobs to low skilled manual jobs the impact of technology and other factors showcase different results. The author breaks the conventional assumptions through different studies conducted by himself.
"This essay has emphasized that jobs are made up of many tasks and that while automation and computerization can substitute for some of them, understanding the interaction between technology and employment requires thinking about more than just substitution. It requires thinking about the range of tasks involved in jobs, and how human labour can often complement new technology. It also requires thinking about price and income elasticity’s for different kinds of output, and about labour supply responses"
"[W]hat about the Marxian concern that automation will immiserate workers by obviating the demand for labour? In simple economic models, this outcome cannot really occur because capital is owned by the economic agents who are presumably also the workers; but, alternatively, the returns could accrue to a narrow subset of agents. Sachs and Kotlikoff (2012) and Sachs, Benzell, and LaGarda (2015) explore multigenerational economic environments in which a burst of robotic productivity can enrich one generation of capital owners at the expense of future generations. These later generations suffer because the fruits of the productivity surge are consumed by the old, while the young face diminished demand for their labour and, in some cases, also experience credit constraints that inhibit their human capital investment”
"[E]ven if automation does not reduce the quantity of jobs, it may greatly affect the qualities of jobs available".
"[I]f computers largely substitute for routine tasks, how do we characterize the no routine tasks for which they do not substitute? In Autor, Levy, and Murnane (2003), we distinguish two broad sets of tasks that have proven stubbornly challenging to computerize. One category includes tasks that require problem-solving capabilities, intuition, creativity, and persuasion. These tasks, which we term “abstract,” are characteristic of professional, technical, and managerial occupations. They employ workers with high levels of education and analytical capability, and they place a premium on inductive reasoning, communications ability, and expert mastery. The second broad category includes tasks requiring situational adaptability, visual and language recognition, and in-person interactions—which we call “manual” tasks"