Artificial Intelligence in Human Resource Management

Part 1: Introduction/Summary

“artificial intelligence” refers to a machine’s capacity to carry out operations that require human intellect, such as learning, solving problems, making decisions, and processing natural languages. AI applications may be taught to learn from data, find out sequences, anticipate outcomes, and get better with practice (Nawaz, 2020). AI has several uses in client service, banking, medical care, transportation, and human resources management (HRM). In organizations worldwide, the use of artificial intelligence (AI) in human resources management (HRM) has grown in acceptance. Automating different HR processes, such as hiring, staff engagement, performance tracking, and workforce planning, is called artificial intelligence (AI) in HRM (Nawaz, 2020).

This paper attempts to assess, examine, and explore the use of AI in HRM and its benefits and moral dilemmas in the workplace. This report aims to critically examine how AI has affected HRM and offer well-considered suggestions for Canadian businesses. The report’s objectives include defining the benefits and drawbacks of AI in HRM, assessing various viewpoints, and offering suggestions for how businesses can approach using AI in HRM while considering ethical concerns. I studied several publications and journals published between 2019 and 2023 to produce this research. The paper will also include policy suggestions that may be put into place to guarantee the moral and appropriate use of AI in HRM. Additionally, it will make recommendations for future studies to help us comprehend how AI is affecting HRM and how to solve ethical issues.

Part 2: Analysis and Discussion

Proponents’ views on the advantages of AI in HRM

AI in HRM advocates assert that the technology may significantly increase the effectiveness and output of human resources departments. Hogg (2019) States that AI can help HR managers save a lot of labor and time by automating some operations like applicant screening and resume analysis. This enables them to concentrate on more strategic tasks that call for human judgment and imagination, such as creating strategies for attracting and retaining talent. AI may also improve HR procedures by eliminating repetitive activities and enabling more effective contact with job applicants and staff members (Bongard, 2019).

Further claim supporters make is that AI may help businesses save much cost. Businesses can decrease the need for human labor and make long-term financial savings by automating some HR operations (Amritaa & Achwani, 2018). By evaluating potential employees based on their abilities and credentials rather than variables like age, color, or gender, AI can also aid in eliminating recruiting biases (Florentine, 2016). This may result in a more inclusive and varied workforce, which might help save expenses related to high employee turnover.

AI in HRM also has the potential to lead to better decision-making. AI can swiftly and correctly analyze vast volumes of data, which may give HR professionals insightful data for hiring, performance management, and other HR tasks. For instance, using a candidate’s talents and prior performance, AI may assist in determining which potential employees have the most excellent chance of succeeding in a particular position. Similarly, HR may use AI to detect which employees are most likely to leave the firm and take preventative actions to keep them.

AI in HRM proponents also contend that the technology may aid in developing more individualized working environments. AI may assist HR departments in better adjusting their services to better fit the needs of specific workers by analyzing worker information such as their preferences, abilities, and career aspirations (Rodney et al., 2019). AI, for instance, can assist in determining which options for training and development are most pertinent to a worker’s professional objectives. Higher output and staff retention rates may result from this, as well as more employee engagement and happiness.

In addition, proponents contend that AI may be applied to real-time employee behavior monitoring. AI may assist HR departments in identifying potential problems before they worsen by monitoring employee engagement, stress levels, and work behaviors. AI may notify HR personnel, for instance, if a worker is displaying symptoms of burnout so they can take action to resolve the situation. AI may also assist in identifying which workers are the most effective and efficient, enabling HR to reward the best employees.

Opponents’ views on ethical issues of AI in HRM

AI in HRM critics expresses worries about the moral ramifications of utilizing AI at work. The possibility of prejudice and discrimination is one of the key worries. By evaluating job candidates based on their abilities and credentials, AI can help reduce recruiting prejudices but is not resistant to bias (Jade Taryn, 2022). If AI systems are calibrated incorrectly or are trained on partial data, they could bolster existing prejudicial views. This may result in discriminatory repercussions, such as excluding eligible applicants because of their ethnicity, gender, or age.

Additionally, opponents express worries about data security and privacy. Large volumes of personal data, including resumes, performance reviews, and social media activity, are frequently collected and analyzed by AI in HRM from prospective applicants and staff (Bankins, 2021). This raises questions about how this data is being gathered, stored, and used, as well as whether they are being done in an honest and moral way. Additionally, there is a chance of security breaches, which may reveal private information to unauthorized people or organizations.

The possibility for AI to dehumanize the recruiting and management process is another ethical concern cited by opponents. According to Oracle (2022), by leaning too much on AI, HRM risks losing its human component, which might leave prospective employees and workers without compassion and comprehension. Adverse effects, including diminished motivation and work satisfaction, may result. Furthermore, the use of AI in HRM raises concerns regarding who is accountable for the choices made by the system and if they are being made with the organization’s and its workers’ best interests in mind.

The possibility for AI to be utilized for monitoring and control is another issue brought up by opponents. Artificial intelligence can assist in identifying possible problems like burnout or low productivity by continuously monitoring employee behavior (Jade Taryn, 2022). Opponents counter that this can result in a culture of control and surveillance where workers are continuously watched over and assessed. As a result, there may be less cooperation and trust inside the company, and employee stress levels may rise. Finally, whereas supporters of AI claim that it can result in cost savings and improved efficiency, detractors claim that this could put human employment at risk. Inequalities and socioeconomic problems already present, such as the digital divide and the automation of low-skilled professions, run the danger of getting worse.

Evaluate, analyze, and discuss

According to proponents, AI may improve HR processes by decreasing prejudice, enhancing decision-making, and boosting productivity. Opponents, however, cite legitimate, ethical issues around the possibility of prejudice, discrimination, privacy infringement, dehumanization, and job loss (Nawaz, 2020). The moral concerns highlighted by critics are not specific to AI in HRM but represent larger social worries about how technology may affect people’s privacy, security, and dignity. In order to guarantee that ethical standards and best practices constrain the application of AI in HRM, organizations should carefully weigh the potential advantages and hazards of the technology.

Despite the possibility of using AI in HRM to improve organizational performance, it is crucial to be mindful of the ethical concerns it brings. Supporters should address opponents’ concerns to guarantee that AI is applied transparently, morally sound, and responsibly. The potential advantages of AI will need to be carefully weighed against the requirement to safeguard the security, confidentiality, and integrity of job applicants and workers. It is crucial for AI supporters in HRM to prioritize ethical issues during the development and use of technology to allay these worries. This entails making sure that AI is utilized responsibly, transparently, and in accordance with moral ideals and industry standards. Also, organisations should carefully calibrate and monitor AI algorithms to make sure that they are not reinforcing current prejudices in order to address issues related to bias and discrimination.

Part 3: Conclusions and Recommendations

The use of AI technology, according to proponents, may significantly improve HR procedures by decreasing bias, enhancing decision-making and boosting productivity. Critics, however, cite legitimate ethical issues around the possibility of prejudice, discrimination, privacy infringement, dehumanization, and loss of employment. Organizations must give ethical considerations top priority while creating and using AI in HRM in order to successfully handle these issues. This entails making sure that the technology is utilised responsibly, transparently, and in accordance with moral ideals and industry standards. Furthermore, organisations should carefully calibrate and analyze artificial intelligence algorithms to make sure that they are not reinforcing current prejudices in order to cope with issues related to discrimination and prejudice.

Based on my above analysis, I suggest the following recommendations for organisations wishing to integrate AI into their HR procedures:

• Prioritize ethical issues: When creating and implementing AI in HRM, organisations should give ethical issues first priority. This includes making sure that the technology is utilised responsibly, transparently, and in accordance with moral ideals and industry standards.
• Be mindful of possible biases: Although AI has the ability to lessen prejudice in HR procedures, it’s crucial to be mindful of the possibility that bias may be introduced through the technology. To make sure that AI algorithms are not perpetuating preexisting prejudices, organisations should properly calibrate and monitor the algorithms.

• Maintain transparency: This includes being open about how AI is being utilised in HRM, as well as how information is being gathered and used.

• Provide training: Businesses should educate their staff on how to utilise AI in HRM, including how to do it safely and successfully.
• Monitor and assess: To make sure that AI is producing the intended results and is being used in an accountable and ethical way, organisations should monitor and assess how it is being used in HRM.

I believe organisations can successfully integrate AI into their HR operations by heeding this advice in a way that maximizes the potential advantages of the technology while minimizing its potential hazards and ethical problems.

References

Amritaa, K. S., & Achwani, S. (2018). A Study on Use of Artificial Intelligence in Human Resource Management. Gavesana Journal of Management, 10(2), 45-56. https://www.proquest.com/docview/2256525681/fulltextPDF/860D29EB9399403CPQ/1?accountid=39331

Bankins, S. (2021). The ethical use of artificial intelligence in human resource management: a decision-making framework. Ethics and Information Technology, 23(4), 841-854. https://doi.org/10.1007/s10676-021-09619-6

Bongard, A. (2019). Automating talent acquisition: Smart recruitment, predictive hiring algorithms, and the data-driven nature of artificial intelligence. Psychosociological Issues in Human Resource Management, 7(1), 36-41. https://www.proquest.com/docview/2237548106/fulltextPDF/749D43BB481546DEPQ/1?accountid=39331

Florentine, S. (2016). How artificial intelligence can eliminate bias in hiring. CIO Magazine. https://www.proquest.com/docview/1855471294/fulltext/E51ECDA428214DEFPQ/1?accountid=39331

Hogg, P. (2019). Artificial intelligence: HR friend or foe?. Strategic HR Review. https://doi.org/10.1108/SHR-11-2018-0094

Jade Taryn, G. (2022). How is AI disrupting human resources management? – proquest. https://www.proquest.com/docview/2645542378

Nawaz, N. (2020). Exploring artificial intelligence applications in human resource management. Journal of Management Information and Decision Sciences, 23(5), 552-563. https://www.proquest.com/openview/caf951e06e5ad3d6a24548f262c90d92/1/advanced

Oracle. (2022). AI in Human Resources The Time is Now. https://www.oracle.com/a/ocom/docs/applications/hcm/oracle-ai-in-hr-wp.pdf

Rodney, H., Valaskova, K., & Durana, P. (2019). The artificial intelligence recruitment process: How technological advancements have reshaped job application and selection practices. Psychosociological Issues in Human Resource Management, 7(1), 42-47. https://www.proquest.com/docview/2237548043/fulltextPDF/A62257E495224CE0PQ/1?accountid=39331