Impact Of The Use Of AI (ANSWERED)

QUESTION

Assessment 2 – Individual report

Link to Module Learning Outcomes

This assessment is specifically linked to the following learning outcome:

Demonstrate critical awareness of current management problems by selecting a suitable research topic and conducting a literature review on the chosen topic.
Systematically analyse published academic research and evaluate and critique the techniques and methodologies employed in those publications.
Propose new, coherent, and strong arguments, using clear academic writing.

Preparation

Students will be working individually.
Each student selects ONE topic from the list below:
1. Drivers and barriers of adoption of electronic vehicles (you can choose one specific type of buyer)
2. Supply chain sustainability in the luxury sector (you can choose one specific industry – e.g., fashion, food…)
3. Opportunities and challenges of the metaverse for product innovation (you can choose one specific industry – e.g., clothing, gaming…)
4. How co-working spaces can support vs. hinder innovation
5. Impact of protest demonstrations on public attitudes towards climate activist groups
6. Impact of the use of artificial Intelligence in the recruitment on young jobseekers
7. Initiatives to improve food waste disposal practices at home
8. Factors that impact on online information literacy for health-related topics (you can choose one specific health area – e.g., antibiotics, vaccination, obesity…)
Students conduct a review of the academic literature about the chosen topic, and write a report including:
1. Keywords and databases used for the search
2. Criteria for selecting 4-6 journal papers relevant to the topic, published since 2021
3. Critical discussion of the findings from the papers selected, including a concept-centric analysis of the main arguments presented
4. Conclusions that may be derived from the literature review
The report is 1,000 words long (+/- 10%), excluding references, tables and figures
The following structure is recommended, for the report:
1. Introduction: Chosen topic and its relevance for managers (cc. 50 words)
2. Approach: Keywords and databases used for the search, and criteria for selecting the papers to review (cc. 200 words)
3. Analysis and discussion: Main arguments presented in the papers reviewed, and critical discussion of findings (cc. 500 words)
4. Conclusion: Critical evaluation of the implications from the papers reviewed, and suggestions for further investigation to be conducted in order to further understanding of the chosen topic (cc. 250 words)
Use APA or Harvard referencing style

ANSWER

Impact Of The Use Of Artificial Intelligence In The Recruitment On Young Jobseekers

Artificial Intelligence (AI) has become an important topic in recent years. Some of the new areas include AI use in recruitment, which has various impacts on young job seekers. The impacts of using AI to recruit on young job seekers are highly relevant to managers because of the legal compliance, considerations to candidate experience, thinking on the effective talent acquisition strategy, and the assessment of whether using AI aligns with the organization’s culture.

Approach

The literature search was done mainly on Google Scholar, which redirected to various journal websites like Springer. The main keywords phrases entailed “the use of AI in recruitment,” “Impacts of AI recruitment on young job seekers,” and” “how does using AI recruitment impact young job seekers.” The search was narrowed down to articles published within the last 3 years, i.e., since 2021. The first search used the keyword phrase, “the use of AI in recruitment.” Most of the first result articles assessed the perception of AI use in recruitment, its impacts on employment, and the public perspectives. Again, the articles seemed to provide information about the effects on recruiters instead of job seekers. However, 2 of them were found to provide insight into employers and job seekers.

The second search used the keyword phrase, “how does using AI impact young job seekers.” This search yielded 15 articles, peer-reviewed and from established journals. However, access was limited in 13 articles, remaining with two peer-reviewed journals. Of the two articles, only one indicated a likely impact of AI on job seekers. The third search utilized the keyword phrase, “Impacts of AI recruitment on young job seekers,” which resulted in rich literature but excluded “young job seekers.” A total of 4 articles were selected from the overall search.

Analysis and Discussion

The use of AI in the recruitment process is no longer news as it has been normalized. In the four articles, the authors provide different perspectives on how AI in recruitment affects young job seekers. For instance, Kandoth and Shekhar (2022) found that AI use in job applications mediates personal innovativeness, social influence, and perceived trust. Therefore, AI benefits job seekers because of its real-time and not-so-intuition-based mode of operation. Again, AI in recruitment enables more young people to participate in applications and stand a chance at getting hired due to the thorough screening (Kandoth and Shekhar, 2022).

Wong (2021) assesses students’ employability after college and the need to deploy AI early in their school activity to enable a smooth transition into work. Wong (2021) states that young people can’t find jobs, and yet employers can’t find the right people with the right skill set. Since AI has taken over the recruitment process, learning institutions have looked for ways to balance off this mismatch. Therefore, using AI has created challenges among young people because they lack sufficient capability in skills and career mapping to fit the needs of AI. Again, some students lack a clear career path, and AI may not have access to their information to provide a recommendation because of its main recruitment function.

On the other hand, Weiss et al. (2022) investigated how prospective job applicants viewed AI in their application process. Consequently, they studied how receiving assistance impacts interpersonal perceptions. Weiss et al. (2022) found that AI’s influences on decision-making and personal perception as an area of psychological interest have not been explored, but its algorithmic biases impact job candidates’ prospects. Additionally, the results of the study showed that AI’s strict criterion is likely to alienate young people whose skill set in the English language is not proficient or who are non-native English speakers. Therefore, AI in recruitment negatively affects the perception of job applicants regardless of their English language prowess (Weiss et al., 2022).

Desiere and Struyven (2021) base their argument on the impacts of using AI in the recruitment process on young people on fairness. In their methodology, they argue that AI recruitment contributes to discrimination because of its capability to identify vulnerable job seekers. AI has a profiling technique that ensures the priorities in contacting applicants. Years ago, AI ranked whom to be contacted first depending on the rules and interpretation by caseworkers. According to the AI used in this case study, jobseekers are divided into groups from those likely and those unlikely to be hired. Job seekers most at-risk of becoming unemployed are contacted first. This and other strategies Desiere and Struyven (2021) discuss lead to discrimination. This discrimination results from job seekers from a disadvantaged group and other characteristics such as age being left out of the list to be contacted. Young job seekers may fail to meet the criteria used to profile job seekers (AI-based profiling).

Conclusion

Education relates to employment because of the transition from education to the job market. Reviewing the inclusion of AI into the education system is important because of the impact it can have on the employment of young people. As Wong (2021) has discussed, AI can impact the education for employment process, which means students must be accustomed to the job market placement process.

Together, this research suggests that AI can sometimes lead to discrimination due to the group it selects to be contacted. Sometimes, job seekers may not have the experience, or they may not meet the algorithm, which means they may be left out. For instance, young people may encounter difficulties landing a job because, while the employer is looking for a certain skill, they are also looking for a job but missing the point of matching the skills as described in the AI. Some other issues that arise from using AI include discrimination against people lacking fluency in the English language. This element may need further research since it seems to be complex, especially in this age when diversity is a significant consideration in employment.

Lastly, AI seems to be less warm than the human element would. Therefore, as a recommendation, the impression of the warmth of using AI for recruitment is a relevant area for future research compared to the human element.

References

Desiere, S., & Struyven, L. (2021). Using Artificial Intelligence To Classify Jobseekers: The Accuracy-Equity Trade-Off. Journal of Social Policy, 50(2), 367-385.

Kandoth, S., & Shekhar, S. K. (2022). Social Influence And Intention To Use AI: The Role Of Personal Innovativeness And Perceived Trust Using The Parallel Mediation Model. In Forum Scientiae Oeconomia (Vol. 10, No. 3, pp. 131-150).

Weiss, D., Liu, S. X., Mieczkowski, H., & Hancock, J. T. (2022). Effects Of Using Artificial Intelligence On Interpersonal Perceptions Of Job Applicants. Cyberpsychology, Behavior, and Social Networking, 25(3), 163-168. https://doi.org/10.1089/cyber.2020.0863

Wong, Y. K. (2021). Skills Mapping And Career Development Analysis Using Artificial Intelligence. In Proceeding Of Computer Science & Information Technology (CS & IT) Computer Science Conference Proceeding (CSCP) 2021 (pp. 185-192).