Aspects of Automation in the Workplace

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Introduction

Millions of workers across the globe lost their jobs due to the COVID-19 pandemic. Although some of them have already gone back to their jobs, there are fears that many might not return due to automation. According to Autor (12), a third of the global jobs could be threatened by automation by mid-2030s. The use of machinery to replace workers has caused anxiety for centuries. With introduction of technology to enhance job performance, someone somewhere is facing the prospect of becoming jobless.

The history of automation can be traced back to the 16th century. During this time, all labor was manual until William Lee, a clergyman, came up with an idea to mechanize stockings production. Subsequently, Lee adapted looms for use in rugs manufacture by making a long stocking material sheet (Autor 15). This could be cut and then stitched into stockings before use. The process was cheaper and quicker as compared to the traditional method. Lee’s innovation put the welfare of then stocking knitters into jeopardy, prompting Queen Elizabeth I to reject his patent request. However, it was this innovation that laid the foundation for subsequent textile machine developments. Nonetheless, it was during the Industrial Revolution that automation became a reality (Autor 16). Steam-powered machines replaced handcrafts done by artisan workers. Machines were adopted to handle large-scale production of food to feed the growing populations. These replaced farm workers who previously used manual labor to cultivate their farms. A section of workers rioted and smashed equipment in an expression of their anger over the use of machines to replace them.

In the last half of the 20th century, robots became increasingly used to manufacture vehicles. Initially, they were used to performing tasks that were simple and repetitive. Robots helped manufacturing companies standardize the quality of their production, control production costs, and increase output. Tasks such as spray painting and welding were the very first ones to transit from humans to robots. However, humans still played a crucial role in supervising the robots. With improvements in technology, the range of jobs migrating to robots has continued to increase as well (Grigoli, Koczan and Topalova 38). Today, a robot can perform more complex procedures like fixing vehicles with windscreens as well as moving bulky and heavy items in factories.

Micro and Macro Effects of Automation

Automation has always been taunted to lead to higher rates of production, enhance efficient use of materials, achieve better quality, reduce lead times in factories, increased productivity, and safety improvement. Increased productivity and higher output are two of the main micro effects of automation. Automated systems often perform work with less variability when compared to humans (Mckay, Pollack and Fitzpayne 38). This results in greater consistency and control of the quality of products. Increased control processes ensure that materials are used efficiently, reducing volumes of scrap.

Since automated systems ensure that workers are removed from their places of work, they are safeguarded from the hazards associated with their work environments. Therefore, the fact that automation assists in protecting the well-being of workers are a significant micro effect that cannot be ignored. On the other hand, automation leads to a reduction in the number of hours that workers interact with machines (Wood 126). As a result, the workers get an opportunity to spend time with their family members or engage in other productive activities. Those who hold more than one job can be assisted by automation as well.

Conversely, the effects of automation go beyond working hours, safety, and increased productivity. The macro effects associated with automation have long term effects on the affected populations. Employees whose jobs have been taken over by machines and consequently rendered jobless go through painful periods of emotional stress and depression. As a result of being displaced by a machine, an employee can also be physically or geographically displaced and forced to relocate (Wood 129). Sometimes, one is even forced to remove his or her children from school to look for cheaper options. Indeed, these are very trying moments that can have more devastating mental problems.

In addition to the inconveniences that automation brings to individuals, organizations are also forced to invest huge amounts of capital in designing, fabricating, and installing automation machines. Moreover, these machines require millions of dollars to maintain as opposed to machines that are manually operated. Automated machines have less versatility as compared to humans, hence, lower flexibility degree. Furthermore, there are fears that automation will subdue humans rather than serve them. Workers who operate these machines are slowly being turned into slaves to the robots. This is because they must be available all the time and operate in tune with the machines (Mckay, Pollack and Fitzpayne 26). Moreover, the automated machines operate by relying on vast amounts of data networks, a factor that compromises the privacy of humans. It is a danger to civilization if the entire human race depends on automation for its survival and economic well-being.

Synergetic Production Between Humans and AI

Humans and artificial intelligence can work together in synergy to come up with sustainable products that guarantee the success of the other. To assist the automated machines, humans must do three crucial roles; training, explaining, and sustaining. It is mandatory to teach the machine learning algorithms to perform the works that they have been developed to do. As AI arrive at complex and opaque conclusions, human experts need to explain their behaviors to users who do not have the know-how. These explainers serve a crucial role in such industries as medicine and law that are evidence-based (Mckay, Pollack and Fitzpayne 49). This is one of the areas that artificial intelligence has immensely contributed to employment since organizations continue to rely on such experts to explain their automation procedures to different stakeholders.

To continue to function safely, responsibly, and properly, organizations need sustainers. These are arrays of experts that work round the clock to ensure that the factory systems are prevented from any harm posed by AI. This implies that robots who work alongside human beings must be developed in such a way that they can recognize humans and refrain from endangering their lives. Sustainers also ensure that AI procedures are done in accordance with ethical standards and norms (Grigoli, Koczan and Topalova 48). On the other hand, in helping humans expand their abilities, machines amplify our cognitive strengths, interact with employees and customers as well as embody human skills. By providing the right information at the right time, AI helps boost humans’ decision-making and analytical abilities and heightens creativity.

From the above discussion, it can be concluded that humans and machines need each other and that there is none that can function appropriately without the other. Thus, machines cannot completely displace humans from their jobs because it is humans who operate them. The significant value that humans play in the success and operation of artificial intelligence cannot be ignored. However, it must be noted that less-skilled jobs are the ones that are most at risk of being taken over by machines. This calls for humans to acquire relevant expertise on the different aspects of machine functionalities.

Works Cited

Autor, David H. “Why Are There Still So Many Jobs? The History and Future of Workplace Automation.” The Journal of Economic Perspectives, vol. 29, no.3, 2015, pp. 3-30.

Grigoli, Francesco, et al. “Automation and Labor Force Participation In Advanced Economies: Macro and Micro Evidence.” European Economic Review, vol. 126, 2020.

Mckay, Conor, et al. Automation and the Changing Economy. The Aspen Institute, 2019.

Wood, Robert J. “The Challenge of Manufacturing Between Macro and Micro.” American Scientist, vol. 102, no. 2, 2014, pp. 124-131.

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