BUSN410_Week_3_Editorial
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Unemployment in Information Technologies
American Public University
BUSN410: Critical Thinking Strategies for Business Decisions
Larry Woods
November 26, 2023
Unemployment in Information Technologies
Summary
Lin, B. (2023, October 6). IT unemployment Soars to 4.3% Amid Overall Jobs Growth. WSJ. https://www.wsj.com/articles/it-unemployment-soars-to-4-3-amid-overall-jobs-growth-2bbb1140
Although there is an increase in job opportunities in the U.S., the IT field is suffering from low employment rates, given the introduction of Artificial Intelligence (AI) technology. Unfortunately, the latter has overtaken manpower, and employers prefer it to human labor for cost-effectiveness. The unemployment rate in Information Technology has skyrocketed from 3.8%, which is a general jobless rate, to 4.3%. Although counterarguments propose that this is false and that IT experts are in demand for data analytics and IT project management, research suggests that many entry-level roles, such as customer service, have been overtaken by AI. Employers have begun training employees on AI usage, avoiding the employment of new workforces. The nation is suffering from unemployment in the IT sector, and the supply is much higher than demand. Unemployment in the IT field covers the larger percentage of the total unemployment rates in the country.
Article Premise
The article stems from the introduction of AI technologies into the marketplace. Although AI has led to numerous advancements in the contemporary world, it has been associated with increased unemployment. According to Guliyev (2023), these technologies have replaced human labor, as employers prefer them for efficiency, which humans may otherwise not
provide. The article thus elaborates on this issue by focusing on technology's impact on the IT field. Some may argue that AI does not replace human labor and thus does not impact unemployment (Georgieff & Hyee, 2022). However, the article bases its arguments on these
facts, elaborating that the IT departments have faced significant changes since skills previously portrayed by humans have now been incorporated into machines, thus dismissing human labor.
Evidence Presented
The author supports her argument by mentioning that unemployment in the IT field has increased to 4.3%. Statistics prove credibility, particularly by relating these numbers to national unemployment rates. The author’s explanation for relating AI to IT unemployment is credible, as
Lima et al. (2021) discuss that invented machines often take over the roles of humans. Further, she incorporates a graph by Janco Associates on unemployment rates affecting information technologies. This evidence is credible enough to support her arguments, given that the statistics accompanying the data are reliable. According to Matuzeviciute et al. (2017), technological advancement increases unemployment in various circumstances and fields and may lead to long-
term consequences. Thus, this information supports the evidence provided on the graph indicating the length of unemployment in the IT field. The evidence provided by Lin (2023) is verified, given the vast amount of data supporting it. The journals included, for example, offer insight into the impacts of AI on unemployment, thus supporting the author’s evidence.
Counterarguments
The author presents numerous counterarguments through quotes and statements from opposers. This aspect proves the openness and reliability of the author's arguments since the opposing views are respected. She mentions that technology leaders hold that AI does not lead to
unemployment as areas such as cybersecurity outpace supply. She gives evidence of these counterarguments by quoting CompTIA's chief research officer, Tim Herbert. The counterarguments are effectively presented, leaving no room for doubt regarding the author's
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arguments. The author addresses the counterarguments by stating facts to prove her point. She does not disregard opponents but acknowledges their standpoints.
Writer’s Interest
The writer’s interests in the IT field are evident. She highlights that unemployment has affected this field despite an increase in employment in other fields. Her focus on IT elaborates her discontent with AI. Although she does not outrightly state this factor, her arguments highlight that she believes AI has adversely impacted information technologies. Although counterarguments prove otherwise, the writer mentions statistics and attaches proof to indicate the negative outcomes of improved technology. She thus demonstrates interest in the IT field, and in having a solution discovered for this ongoing menace, the writer is direct about her fears, which may be long-term, as AI developments continue to increase. Lin is direct in her take on technological innovations and does not hide the fact that their negative consequences dishearten her.
Language Use
The language used is simple and direct. Lin uses simple terms despite this being a business and technology paper to bring out her argument. She simplifies her take by ensuring the
use of layman's language. Further, the author summarizes opponents' arguments for comprehension. She draws critical facts from their statements and quotes statements that readers easily understand. Further, Lin uses correct grammar, enhancing comprehension. When language
is used appropriately, readers do not struggle to understand. English has been used throughout, which is the primary language of Lin's audience. Additionally, the language is respectful and cannot be misunderstood or misquoted. Understanding has no complications, as the author is
simple, direct, and clear. Anyone with an interest in business or technology will understand the concept of Lin's argument.
Errors
Arguments have been presented coherently, and so has the supporting evidence. However, the author fails to attach direct links to the references, which raises questions. Although she quotes counterarguments from renowned people and organizations, she does not support her arguments against them with any references. Data and statistics were incorporated into the paper, but one must dig into internet sources before finding this evidence. Lin has added direct links to some information, but the primary evidence sources are absent. Thus, individuals may assume that the evidence is not credible, especially if they do not do internet searches for specific information.
Appeals and Fallacies
The author uses logos, an appeal to logic. The author highlights how ideas connect to facts by mentioning statistics. She, for example, begins by arguing that the high unemployment rates affect the IT field. Following this statement is evidence in the form of statistics, highlighting the percentage of increased unemployment in information technologies compared to
the overall unemployment rates in the country. Further, Lin incorporates a graph elaborating on the same issue, which proves the use of logos. However, she does not incorporate ethos, as nothing is said about her or her qualifications. Similarly, pathos and fallacy use are not evident.
Conclusion
Despite the lack of evidence of some claims, the article is compelling. The relationship between AI and unemployment is evident, particularly due to the focus on the IT field. Readers can easily follow through the data provided and use it to find support from other sources, as has
been done in this paper. The author’s use of clear and simple language and statistics increases understanding due to the focus on unemployment rather than technological influences. Statistics on unemployment make the article trustworthy, thus increasing the compelling nature of the article. The author did an excellent job by being direct and specific, sparing her audience from reading substantial amounts of data that do not make sense.
References
Georgieff, A., & Hyee, R. (2022). Artificial Intelligence and Employment: New Cross-Country Evidence.
Frontiers in Artificial Intelligence
,
5
. https://doi.org/10.3389/frai.2022.832736
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Guliyev, H. (2023). Artificial Intelligence and Unemployment in High-Tech Developed Countries: New Insights from Dynamic Panel Data Model.
Research in Globalization
,
7
,
100140. https://doi.org/10.1016/j.resglo.2023.100140
Lima, Y., Barbosa, C. E., Dos Santos, H. S., & De Souza, J. M. (2021). Understanding Technological Unemployment: A Review of Causes, Consequences, and Solutions.
Societies
,
11
(2), 50. https://doi.org/10.3390/soc11020050
Lin, B. (2023, October 6).
IT unemployment Soars to 4.3% Amid Overall Jobs Growth
. WSJ. https://www.wsj.com/articles/it-unemployment-soars-to-4-3-amid-overall-jobs-
growth-2bbb1140
Matuzeviciute, K., Butkus, M., & Karaliute, A. (2017). Do Technological Innovations Affect Unemployment? Some Empirical Evidence from European Countries.
Economies
,
5
(4), 48. https://doi.org/10.3390/economies5040048