Automation of Capitalist Hierarchy

Justin Tsang

HSS 371

Blog #6 – Automaton of the Capitalism

11/8/15

The Automation of Capitalist Hierarchy

            iRobot, Deep Blue, and Google’s Self-Driving Car have all shown the capabilities and potential of artificial intelligence and machine learning. However, many have been regarded as fictitious and non-significant achievements of robotics and were never viewed as plausible in humanity’s near-future. For example, during game six with IBM’s Deep Blue computer, Kasparov thought a human was controlling the computer and questioned the capability of computers and algorithms. Although this event happened a little less than 20 years ago, the question is brought back up. If a computer is capable of beating a Grand Master chess player, what other potentials does artificial intelligence have in modern day? A recent research by McKinsey and Company calculates that over 45 percent of paid jobs, or $2 trillion in annual wages, in America can be automated. While there are the primitive automated machines, such as the ATM, auto-pilot, and automated check-in kiosks, that have threatened the job safety for middle to lower class workers, high-paid occupations are also at risk of having their jobs automated as well. Although many people commonly link automated machines overtaking middle and lower class occupations, automated machines also have an impact on high-wage jobs, such as physicians and senior executives. Over 20 percent of a CEO’s task can be automated. This includes analyzing reports, preparing staff assignments, and reviewing status reports. As a result, robotics has redefined the roles of the individual in both high and low paying occupations. One of the advantages automated machines have over humans is speed. Quill, Kiva robots, and IBM’s Watson have proven to perform just as well as humans. Quill is able to analyze data to generate natural language and write reports that when read appear to be written by human authors. The Kiva robots are being utilized in Amazon and have displayed efficiency when coordinating and shipping Amazon orders out from the warehouse. Furthermore, IBM’s Watson has accurately suggested treatments for patients’ illnesses through its extensive database of medical research.

            Although most of this sounds frightening, it should be stated that only 5 percent of the current 40 percent of jobs at-risk of automation can be completely automated. For the most part, only specific tasks of most occupations can be automated, while the rest is still reliant on human operation. For example, mortgage-loan officers can spend less time processing rote paperwork and more time on reviewing exceptions. As a result, this will allow them to process more loans and advise their clients. Similarly, if automated technology is adopted in hospitals to handle diagnosis, doctors can handle acute cases. In the law scene, lawyers can use text-mining technology to analyze documents to identify details collected during discovery. In marketing, salespeople can use automated technology to cross-sell and upsell and increase interaction with the customers. As a result, I do not see automated machinery ever replacing humans to complete these occupations. Instead, I predict that humans and automated technology will hold a mutual relationship for each specialized occupation. Maybe it is not unrealistic for all humans to work in tangent with automated robots. If Will Smith and Sonny could do it, why cannot we all adopt it?

Works Cited

Chui, Michael, James Manyika, and Mehdi Miremadi. "Four Fundamentals of Workplace Automation." McKinsey & Company. n.p., Nov. 2015. Web. 8 Nov. 2015.