Final project
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Professor Queen
ENGL 102-08
Researched Argument
Due: 17 Sept. 2020
Machine-Learning Systems: An Ultimate Man-made Creation Towards a Sustainable Environment
Whenever the thought of artificial intelligence (A.I.) rises atop of people's minds, they often overthink its fallouts and how destructive it could be, leading the creation of dystopias, depriving people of their jobs, and maintaining dominance over the most crucial industries. Nonetheless, how valid are these statements and was A.I. meant to be that way? GCC countries have been profoundly investing in human resources for almost half a century. In particular, Kuwait has been reliant on such a resource in banking, education, private companies, and even healthcare organizations. The huge dependency on human resources has negatively affected the country to capacitate and fulfill citizens' and residents' needs.
Moreover, it has eventually led to the evolvement of stress relationships among community members, notably intensifying throughout the COVID-19 crises. The pandemic has also urged the formation of several regulations that minimize the percentage of low-wage workers and expatriates, leading to several critical issues if their workplace gap has not been filled. With the new era of automation and the inclusion of A.I. as the necessary infrastructure of most breakout businesses, the young generation seeks hope in such technology. It eases them an opportunity to create successful careers with minimal resource consumption. Thus, it takes the initiative of both the community members and the government to collaborate into introducing artificial intelligence and machine-learning systems into our lives. Not for it to shape how we act in a workplace but to instead assist us in accomplishing tasks more efficiently, requiring minimal effort and saving the country millions of money. Although systems dependent on artificial intelligence would take years of planning to implement in Kuwait, this human-made creation is capable of sustaining the country’s resources while shaping a community with balanced demographics, where there is less need for low-wage workers and more impactful harmony between citizens, residents, and intelligent technology can be obtained.
When people were first introduced to different means of technology, they were meant to ease tasks and progress what could have taken days just in few hours. With the continuous innovations of technology, scientists have endowed robots with a human-made brain. These machines possess intelligent behavior that allows them to operate and function more than just being a blind task executor. Instead, they learn how to respond and behave to achieve complex goals, in a concept more known as cognitive robotics (El-Hady). Using computers into modeling human reasoning and stimulating intelligent behavior typically lies in a more generalized concept known to be artificial intelligence (“How Far” 00:00:35 - 00:00:50). Laymen, college professors, economists, and people in business have all argued and constructed opposing views on how useful A.I. is to industries and workplaces. Most of these discussions evolve over two central opposing claims. One argues that A.I. has tremendous potential in sabotaging industries by complete domination leading to job deprivation and high unemployment rates. While the other states that no matter how A.I. continuously develops, it has its limitations and finite progression, it can never exceed (Lichenthaler 12). Regardless of all the various misconceptions, A.I. was never meant to compete against human intelligence but rather augment it, as Lichtenhaler mentions in his scholarly article (13).
Artificial intelligence was further developed to provide us with ground-breaking machine-learning systems. The efficient application of A.I. in which these systems are is to perform specific tasks continuously evolve its algorithms by experience with minimal human interventions or assistance. Several countries have experimented with stepping forward towards the next phase of automation, involving A.I. Although scientists may refer to automation as "the fourth industrial revolution," it does not always offer industry and workplaces that profound impact it promises due to several reasons. The most significant reasons include the community members' initiative to collaborate with such systems to improve their skills and adapt to new working environments (IEEE).
Moreover, it requires industries to carefully consider which of the four human-machine interplays to adopt since each interplay utterly re-arranges a workplace, each in its way following different procedures. These interplays are showcased in being either: standard, as we notice from low-level automation of primary machines and naïve robots; substitute, where A.I. leads by replacing human intelligence in the workplace; superiority, where human intelligence takes the lead, especially in aspects and skills that A.I. cannot replicate such as creativity; or even synthesis ,where both human and machine intelligence are both integrated to optimize results (Lichtenhaler 12).
A.I. automation helps incorporations maintain economic momentum and detaches a workplace from being utterly dependent on human resources. Whether it is integrating machine-learning into systems or recruiting robots that possess A.I. behavior in the workplace, such technologies are considered to be capital cost, where they require nothing more than electricity and regular maintenance to operate (Schachte). “Robots work 24/7/365, and perform consistently”; moreover, "they work in environments that would kill a human, and do not raise occupational health and safety issues" (Schachte). Nevertheless, one can still argue that it is not always the case where the workplace is dangerously hazardous, which is a fair point. Thinking about economy and savings, one, as an investor, would prefer paying the capital cost at once, and then save his/her revenue for future necessities. One can replicate a customized A.I. system on limitless computer software at no additional cost as long as the original system exists; however, the ideal employee is just him/herself; people are not merely as spec-edited as machines.
A more vivid vision is a profound concept of a workplace hugely benefiting from the synthesized abilities and functions of both humans and artificial intelligence performing, especially for small businesses in the food industry. The general public has known Kuwait having a significant share of the food industry in the GCC. Currently, most people invest in supply chains, whether it was in malls such as "The Avenues" or even specialized home-delivery services similar to those of "Talabat" and "Carriage." Due to loads of demand, these incorporations get nearly teras of data every week, if not every day, but how effectively are such data employed for the benefit of sustaining resources, especially the economy, and simultaneously guarantee a high-quality service for consumers. The Age of A.I. documentary project, funded by Google and hosted by Robert Downey Jr., showcases a similar example. A pizzeria that has structured Zume, a machine-learning logistic system powered by algorithms to specifically gather, connect, and employ the data “to try and forecast how much pizza people want, what kind, and when. It crunches dozens of different variables [like] location, day of week, weather, what's on T.V., past ordering trends, and then predicts how many Sgt. Pepperonis San Francisco will want on a Tuesday, for example" (“Will” 00:29:45 - 00:30:07).
Such real-life examples call thoughtful subsequent investors to take the initiative towards implementing machine-learning investors to optimize target reach as it does also revolve on wasted material that would consequently lead to financial fallouts sometimes. "One of the classic tensions in every food business is producing too much and having waste, or not producing enough food, and having stock-outs” (“Will” 00:28:50 - 00:29:00). What affected the food market recently in Kuwait was the COVID-19 crisis; no one has ever predicted that the country would be experiencing a long-term lockdown. The crisis has led food businesses, especially restaurants, into severe casualties, including paying rent and producing tons of food waste without enough compensating incomes. By getting involved in enhancing the "synthesis" interplay into the working sector, we could not indeed predict industrial catastrophes, but "we could improve predictions, [and] eliminate most of [food] waste. We’d know what the demand was going to be, where the products were going to be, and ultimately, that would make us all better off” (“Will” 00:30:15 - 00:30:27).
Not only does such technology detaches us from human resources dominance and superiority, but it does also contribute to creating new opportunities during the phase of automation implementation that would eventually help re-arrange and maintain balance to the country's demographics. Currently, both citizens and residents in Kuwait have developed tensioned relationships, especially after the COVID-19 crisis. “A revealing example of the unbalanced socio-economic impact of the pandemic is how bank practices such as loan deferments and temporary relief were instituted. A decision from the Kuwait Banking Association (KBA) about refinancing and rescheduling loans did not include residents. It was first announced that only Kuwaitis could reschedule loans and credit card payments for up to six months” (“How Covid-19”). It was no one's fault but the imbalanced demographics the country acquires. Kuwait's 2020 has its residents making up 70% of the total population; moreover, there are 2,526,234 Non-Kuwaiti within the labor force compared to 440,022 Kuwaiti (Kuwait, The Public Authority For Civil Information). This imbalance has led both sides of the problem not to maintain their rights, whether health insurance, wages, and even stability and job security. Furthermore, with the restrictions the government imposed to capacitate the crisis’s effects, residents’ sources of income were directly impacted, “particularly the low-wage workers who run most of the affected businesses” (“How Covid-19”).
With the government precedent direction to deport expatriates who perform basic to minimal tasks —mostly low-wage workers—, there is no better option than automation to replace their crucial workplaces' absence. Taking Port of Long Beach as an example, it is considered to be “the second-busiest port in North America and the first fully-automated container terminal in the United States” (“Will” 00:15:00 - 00:15:16). Previously, the terminal’s design was constructively built to suite a “standard” human-machine interplay. However, both vessel and truck activity were competing for congestion and space when the vessel capacity was growing seven times larger. With the newly implemented automation model, human and artificial intelligence have integrated into creating a safer terminal with a more efficient workflow. Intelligent cranes carry containers to platforms where they are autonomously identified by OCR—Optical Character Recognition—and then placed on system-assigned yard blocks with minimal human assistance ("Will").
A.I. does take away the most difficult, hectic tasks a worker may be required to accomplish and does also lead to new opportunities in the workplace. "It's not taking away jobs; it's taking the place of the job that a [worker] doesn't want to do" ("Will" 00:13:48 – 00:13:56). Out of 50,000 workers, 20,000 may lose their jobs. However, the other 30,000 will synthesize and augment their A.I.'s abilities, eventually maintaining a healthier, more stable working environment. Using machine-learning as an automotive strategy would positively impact social relations. It sustains each community's human rights element in a healthy society that receives its balanced requirements and holds no stress towards an element or the other.
Nonetheless, one of the other issues that resurface is the dire consequences for those 20,00 who have lost their jobs and have not been compensated. Although automation may fill their position gap and maintain more balanced demographics, high unemployment rates are too crucial that they cannot just be ignored and not taken into consideration. Unstable rates of A.I. in the industry would not just widen the unemployment gap among community members. However, they can also lead to disastrous fallouts the A.I. systems were not ones of high reliability and accuracy. Moreover, a rushed transitional plan towards A.I. and machine-learning would quickly demolish industries, mainly if they have mistakenly employed ineffective human-machine interplays.
“By Moore’s Law, computers double in computing power every 2 years, and become a thousand times more powerful every 20 years, and a million times more powerful every 40 years. Humans may pick up a few I.Q. points every 20 or 30 years. Maybe” (Schachte). With the increased performance being unstoppable, human resources would need to face highly competitive technology to qualify for a job.
However, as mentioned earlier, to guarantee an A.I. integration plan that benefits more than it harms, companies must try out different human-machine interventions to gradually achieve optimal solutions. "General Electric" and "Siemens" have invested immense efforts into implementing machine-learning technology, dependent on A.I., to make production processes more efficient. Nonetheless, that technology has not prevented both companies from investing in human resources, as he mentions that there are outstanding human skills A.I. cannot replicate (Lichtenhaler). In the newspaper journalism, robo-journalism was one of the AI-dependent technologies that created sophisticated scripts and stories human interventions; however, a journalist would still oversee its data progression, not for it to announce outdated or inaccurate news or earthquake alerts, for example (Baraniuk).
It is noteworthy to mention that human dominance is the key to almost every industry. Regardless of their fallouts, A.I. technologies (whether they were machine-learning or cognitive robotics) should not be viewed as a complete alternative, at least in the upcoming few years, but rather as "prosthetic arms" that would contribute into easing the workflow off employees (Baraniuk). Besides, it offers an excellent opportunity to lessen the turnaround time —the time interval consumed to process a particular task and provide an output or a solution— in many industries (El-Hady). Machine-learning systems were never to replace but enhance employees' working abilities and productivity in the workplace.
Kuwait's banking industry is one of the most familiar industries with such a concept. In an interview with Mohammed El-Hady, a project manager in Kuwait Finance House (KFH), he has emphasized how A.I. automation has eased several processes, especially one that involves consumers applying for a loan. "Before automation, a custom would fill a loan request and wait in a cue for an employee who handles the process and is required to investigate the applicant's history through several databases that connect all banks operating in Kuwait. Eventually, after that process, the transaction is passed to other departments to progress further formalities —a long, hectic process that may require 10-15 business days to get done" (El-Hady). Thanks to the implementation of A.I. and basic automation, that process usually takes an average of 4-5 days; less turnaround time implies more efficiency into task progression.
Employees may have retained their jobs; automation has just transformed their working environment in more of a healthy, pressure-free, productive one. They are being re-allocated to accomplish professional tasks that may require decision-making and teamwork. "The banking industry in Kuwait is continuously improving the quality of A.I. technologies it acquires, maintaining more convenient digital transformation processes, and for the future A.I. to employ cognition robotics into analyzing and proposing solutions amid complex cases" (El-Hady). As one may notice, this successful machine-learning implementation is in one of Kuwait's most momentous industries that provide both its employees and customers with adequate experiences by applying integrated intelligence of both human and machine intelligence (Lichtenhaler 13).
The question is, for other industries in Kuwait that have not fully implemented A.I. into its system, how would they successfully progress a transformation plan of their workplace? Does it require a year? Maybe two? Or are there any other factors an effective plan has to fulfill? Kuwait is now one of the most known countries to have its community members invested into taking their path towards establishing businesses, whether it was an agriculture company, a restaurant, or even an online shopping website. With the increased demand lately, human resources are not always the perfect option to fulfill investor needs, especially if the investor is an amateur in the field. One could not just fire an entity's employees and substitute their positions with an A.I. technology or robots, not in a country like Kuwait. It is not a phase where an infrastructural system is being abruptly introduced; instead, it a long-term plan that requires years of monitoring and flexible augmentation of a complex system that not everyone is used to already (IEEE).
It is not always easy for an organization to fully use such technology as it is considered expensive and time-consuming. Moreover, in order for businesses to implement such systems, they are required to train their employees to create harmony in the workplace and be more familiar with novel systems and professional electronic platforms, improving their capabilities and easing their mental and professional workplace transition (IEEE). Like us, ordinary people are not always going to deal much with big data and economic issues. However, we should instead understand how useful such a technology is to the country we live in, the workplace we contribute to, and us as consumers who benefit from other industries' resources and services.
With the target of saving great opportunities to future generations and obtaining balanced demographics with less tensioned relations between citizens and residents, artificial intelligence demands a drastic change where people live in a healthy, pressure-free environment. Additionally, it creates the ideal workplace experience as it substitutes tasks instead of jobs, maintaining dominance to humans. Simultaneously, industries experience their peak achievements and success having most of their resources sustained. Without the community members’ initiative to learn to congenialize their skills with A.I. and machines, no industry would progress into that path without people having a sense of social responsibility. "There is an opportunity here to build an economy and society that more accurately reflects our goals and values. Nevertheless, it's going to take a lot of us waking up and rising to the challenge” (Yang).
Works Cited
Baraniuk, Chris. “Would You Care If This Feature Had Been Written by a Robot?” BBC, 30 Jan. 2018, https://www.bbc.com/news/business-42858174. Accessed 19 Aug. 2020.
Bolton, Charlynne, et al. “The Power of Human-Machine Collaboration: Artificial Intelligence, Business Automation, and the Smart Economy.” Economics, Management & Financial Markets, vol. 13, no. 4, Dec. 2018, pp. 51–56. EBSCOhost, DOI:10.22381/EMFM13420184.
El-Hady, Mohammed. Personal Interview. 10 Sept. 2020.
“How Covid-19 Stress-Tested Relations between Residents & Citizens in Kuwait.” Gulf International Forum, https://gulfif.org/how-covid-19-stress-tested-relations-between-residents-citizens-in-kuwait/. Accessed 26 Aug. 2020.
“How Far is Too Far? | The Age of A.I.” YouTube, uploaded by YouTube Originals, 18 Dec. 2019, https://youtu.be/UwsrzCVZAb8.
IEEE Innovation at Work. “How A.I. Is Transforming The Workplace.” IEEE, https://innovationatwork.ieee.org/how-ai-is-transforming-the-workplace/. Accessed 26 Aug. 2020.
Kuwait, The Public Authority For Civil Information. Population Stat. Statistics Services System, 31 Dec. 2019, https://www.paci.gov.kw/stat/.
Lichtenhaler, Ulrich. “Substitute or Synthesis? The Interplay between Human and Artificial Intelligence.” Research-Technology Management, vol. 61, no. 5, Sept. 2018, pp. 12–14. EBSCOhost, DOI:10.1080/08956308.2018.1495962.
Schachte, Peter. Comment on “People say that we don't have to worry about automation depriving people of jobs, because in the past automation has usually led to many new kinds of jobs. But is there a good reason to believe this may be about to change?” Quora, 3 Mar. 2019, https://qr.ae/pN2at8.
“Will a Robot Take My Job? | The Age of A.I.” YouTube, uploaded by YouTube Originals, 15 Jan. 2020, https://youtu.be/f2aocKWrPG8.
Yang, Andrew. Comment on "How will automation and A.I. change the workforce in the future, and what can we do to prepare for it?” Quora, 26 Sept. 2019, https://www.quora.com/How-will-automation-and-AI-change-the-workforce-in-the-future-and-what-can-we-do-to-prepare-for-it/answer/Andrew-Yang.