Subjective Recruiting and Hiring
Unbiased Hiring Process Cannot Be Resolved with Artificial Intelligence
Unbiased Hiring Process Cannot Be Resolved with Artificial Intelligence
The hiring process involves the interviewers hiring the highly qualified employee for a specific position in a company. As a result, not all applicants who apply for a particular position get to be hired. There exists a specific criterion that interviewers or a company use in hiring or selecting potential employees for a vacancy. The criterion can be subjective or objective. Subjective recruitment process involves personal feelings, opinions, and perspectives of the interviewer interfering with the decision-making process. The particular traditional approach to hiring and recruiting may contribute to bias and prevent an interviewer from hiring the most qualified and relevant candidate (Breaugh, 2013). On the other hand, objective hiring involves assessing the most qualified candidate without any bias. Objective recruiting and hiring mostly focuses on assessing the skills and qualifications of a candidate without the interviewer developing personal feelings, opinions, or perspectives.
The understanding of the two facets of recruiting and hiring shapes the direction for this particular study. In this case, the study will involve the assessment of the prevalence of subjective recruitment and hiring. Subjective recruitment suffices to be one of the oldest approaches to hiring whereby interviewers mostly assessed previous working experience and the number of corporations that one has worked for (Breaugh, 2013). The assessment of the particular aspects would sometimes give false negatives and positives which led to a company failing to hire competent employees and selecting the incompetent ones. Moreover, the study involves an assessment of how corporations began incorporating artificial intelligence for the recruiting and hiring processes. Therefore, the study will evaluate how subjective recruitment or unbiased hiring process cannot be resolved with artificial intelligence by incorporating a literature review of peer-reviewed journals.
Importance/Relevance of the Study
Initially, corporations incorporated subjective recruiting and hiring process to select qualified candidates from a list of various applicants. The approach sufficed to be biased and to prevent employers from acquiring the appropriate employees for specific positions. Often, some qualified candidates would be disqualified due to lack of experience from working in other organizations (Breaugh, 2013). Additionally, the approach prevented graduates from attaining specific positions due to lack of experience. Hence, there was a need for the modern business community to come up with an alternative method to facilitate objective recruiting to ensure employers high qualified and skilled candidates regardless of their background or previous working experience. The integration of artificial intelligence was to facilitate the abolition of the subjective recruiting method and the integration of objective recruiting and hiring process. Therefore, this particular study is essential to enable business people to understand the actual impact of artificial intelligence on recruiting and hiring processes.
The assumptions made in this study is that biasness in recruiting and hiring process is not based on gender but rather the approach that an organization implements.
Also, the researcher will assume that all the peer-reviewed article journals which will be used as the primary source of information in the study are accurate.
Moreover, the researcher will assume that the artificial intelligence systems discussed in the peer-reviewed articles in the study are state of the art and of the latest technology.
Henceforth, the assumptions will ensure that the results of the study are based on the meta-analysis of the peer-reviewed articles concerning the prevalence of subjective or the failure of artificial intelligence to resolve the issues of subjective recruitment and hiring processes.
Changes in Recruitment and Hiring processes
Traditionally, interviews would be carried out on a face-to-face basis and would involve both the interviewer and the interviewee. However, the approach has changed in the recent past and contributed to the integration of information technology to facilitate an alternative to achieving objective recruitment and hiring. The traditional approach has a lot of bias and would sometimes be objective (Jiang, Li, Du, & Wang, 2018). For instance, the physical interaction between the interviewer and interviewee could lead to a lot of prejudice. That is, the interviewer may be racist and become subjective as he or she may develop negative feelings or perceptions of a candidate. Eventually, a candidate could lack a job opportunity at the moment the interviewer became subjective and began giving an employee negative scores. Therefore, it was the assumption of the many that the integration of artificial intelligence would consequently make the recruitment and hiring processes objectively.
Additionally, the traditionally hiring and recruitment processes contained bias due to the perceptions that interviewers intuitively developed during interview processes. In most of the face-to-face interviews, it is likely for an interviewer to develop an unconscious bias against an interviewee. In an interview session that may involve a white person as the interviewer and a black person as the interviewee, the interviewer may develop an unconscious bias against the black interviewee and perceive him or her as incompetent (Noon, 2018). Hence, without even evaluating the skills and expertise of a candidate, the interviewer’s mind becomes with the unconscious biases which consequently leads to subjective recruitment and hiring. Therefore, the integration of artificial intelligence according to the perceptions of the many ways to minimize the unconscious bias that develop during face-to-face interaction such as the judgment of a person’s physique and skin colour.
The advancement in technology suffices to have impacted various facets in the society. Particularly, the business sector suffices to be leading in integrating information technology for the execution of multiple tasks. Information technology facilitates knowledge-based systems that complement human resources for the execution of various tasks within the workplace. Moreover, information technology facilitates artificial intelligence which has a major contribution to the business sector. Artificial intelligence makes work easier by ensuring that the knowledge-based systems work in the same way or close to the same way as human beings (Mishra & Shekhar, 2018). Hence, business entrepreneurs consider it crucial to include artificial intelligence in various aspects including the recruitment and hiring process. In this case, rather than human beings carrying out the interviews and hiring processes, machines are used to carry out the tasks on behalf of human beings.
The integration of machine learning and chatbots are one of the interventions that contributed to the emergence and inclusion of artificial intelligence for hiring and recruitment. Conducting interviews suffices to be one of the essential phases in the hiring and recruitment process. Hence, corporations opt to integrate machines or robots that hold the interview sessions with a candidate. The process can involve a robot asking questions and requesting a response from a candidate through voice input. Additionally, a candidate may be required to type in answers depending on the computer-generated questions (Mishra & Shekhar, 2018). The interview processes using artificial intelligence involves the machine posing questions and relying on the candidate’s response as well as the archived data on the computer to formulate and generate another question.
Subjective Versus Objective Selection
Interviewers or companies hiring focus on selecting the most competent, experienced, and qualified candidate to fill a vacant position. Two methods appear to prevail in interview processes. First, subjective selection process involves shortlisting candidates based on emotions, feelings, and perspectives. For instance, an interviewer may assume that having studied in an ivy league school gives an individual the expertise to excel at the workplace. This hinders the ability to assess how skilled an individual is, and the problem-solving abilities he or she has. In subjective selection, unconscious bias prevails whereby an interviewer may look at a candidate and see himself or herself. Hence, the interviewer may start to assume that the particular candidate will perform or achieve success like he or she did (Miles & Sadler-Smith, 2014). As such, the interviewer may end up making decisions based on emotions and prejudice rather than evaluating actual skills and expertise of a candidate.
Secondly, an interview session may involve objective selection. Objective selection process suffices to be the opposite of subjective selection process. In objective selection, the interviewer looks for specific skills and expertise (Breaugh, (2013). For instance, an interviewer assesses aspects of problem-solving skills of an individual, creativity, and the ability to meet goals. On the other hand, the selection process may disguise information such as past organizations that one has worked in, gender, religion, or race. Sometimes, an assessment based on gender or sex may lead to discrimination if a candidate does not identify with one’s sexual orientation or religions. Therefore, objective selection process involves the elimination of factors that could lead to bias in selecting a candidate.
Impact of Artificial Intelligence on Hiring Process
According to the perceptions of the many, artificial intelligence suffices to be some form of supernatural technology that is efficient. The integration of artificial intelligence in business operations such as the interview process was one way to minimize human interaction and ensure that the chatbots used for the interview processes assessed the skills and expertise of an individual. Artificial intelligence is thought to be the ultimate solution to minimize biases during the interview process. In this case, an interviewer cannot see a candidate and judge them based on their physique. The artificial intelligence machines which could be robots or computers get to ask relevant interview questions that evaluate the problem-solving skills of an individual and his or her expertise (Mishra & Shekhar, 2018). Artificial intelligence systems are assumed that they cannot develop unconscious biasness which is common only in the human brain. The particular assumptions led many to believe that artificial intelligence resolves the issues relating to subjective hiring and the development of unconscious bias which could make an experienced and skilled candidate to lack a vacancy.
However, there are various factors that people should understand. Artificial intelligence is a multitude of algorithms developed by a programmer who is a human being. In this case, the algorithms are a series of tests that have to run before the correct or the true one is selected. Therefore, the coded language may contain bias as well. For instance, the algorithm of an artificial intelligence system may be built to reject or ignore applications of candidates with academic transcripts from some universities. Moreover, it is crucial to understand that the data saved in the archives can influence the performance of an artificial intelligence system. For instance, if most of the searches include doctors, plumbers, or president, terms which are associated with male tasks, then the artificial intelligence system is likely to function based on the particular information (Loftin et al., 2016). Therefore, it is crucial to note that the inclusion of artificial intelligence system does not entirely resolve bias in recruiting and hiring processes.
Conclusion and Recommendation
Interview process suffices to be one of the essential phases in initiating an employee into an organization. Hence, the process involves assessing the most competent and skilled candidate for a position and hiring them. The assessment process does involve not only the skills gained through education or training but also the creativity, innovativeness, and problem-solving skills. Traditionally, a typical interview session would involve the presence of an interviewer and the interviewee. Henceforth, the interviewer would ask the interviewee preset questions or develop new questions based on the responses from the interviewer (Breaugh, 2013). As such, the selection of a candidate would be based on the decisions of an interviewer as to whether an applicant meets specific parameters essential for the vacancy. However, the presence of both an interviewer and interviewee in one room prompted aspects of unconscious bias whereby personal feelings, emotions, and perspectives could interfere with the decision concerning the selection of the successful applicant. Therefore, the traditional interview sessions promoted aspects of subjective selection.
Effective interventions to counter subjective selection and promote objective selection were required. At first, employing professional interviewers sufficed to be a solution to ensure an organization does not fail in selecting the competent, skilled, and qualified employee. However, the interviewers were vulnerable to aspects of unconscious biases whereby one could develop prejudice based on gender, race, physique, academic institution attended among other aspects. Hence, the involvement of human resources in the interview translated to mean subjective selection. The effective alternative with the advancement of technology was the integration of artificial intelligence to minimize interviewer-interviewee interaction and the development of unconscious bias. Henceforth, artificial intelligence systems through a series of programmed algorithms would carry out the interviews by assessing expertise and problem-solving skills in an applicant (Mishra & Shekhar, 2018). This created the impression that the integration of artificial intelligence was an effective intervention to minimize aspects of unconscious bias and subjective selection.
The integration of artificial intelligence systems for carrying out interviews suffices to be an essential aspect but does not necessarily resolve the issue of unconscious biases. This is because artificial intelligence systems rely on algorithms and machine learning and rely on archived data to make decisions (Loftin et al., 2016). For instance, if the system has male-coded data, the selection process would have biasness against women applicants. Similar, artificial intelligence system may be set to ignore specific data of applicants and accept information from applicants who are alumni of ivy league universities. The particular research topic is essential to inform entrepreneurs about the prevalence of subjective and objective selection processes. Additionally, the topic is relevant in eliminating the myth that artificial intelligence systems can resolve issues of biasness. Lastly, the research topic is essential as it enables researchers to understand that there is a need for further study concerning an intervention to prevent biasness and resolve subjective selection processes.
Breaugh, J. A. (2013). Employee recruitment. Annual review of psychology, 64, 389-416.
Jiang, F., Li, J., Du, M., & Wang, F. (2018). Research on the Application of Artificial Intelligence Technology in Human Resource Management.
Loftin, R., Peng, B., MacGlashan, J., Littman, M. L., Taylor, M. E., Huang, J., & Roberts, D. L. (2016). Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning. Autonomous agents and multi-agent systems, 30(1), 30-59.
Miles, A., & Sadler-Smith, E. (2014). “With recruitment I always feel I need to listen to my gut”: the role of intuition in employee selection. Personnel Review, 43(4), 606-627.
Mishra, D., & Shekhar, S. (2018). Artificial Intelligence Candidate Recruitment System using Software as a Service (SaaS) Architecture. Artificial Intelligence, 5(05).
Noon, M. (2018). Pointless diversity training: Unconscious bias, new racism and agency. Work, employment and society, 32(1), 198-209.
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