Ethical aspects of using a job application revised

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1 Ethical aspects of using a job application with a focus on privacy Student Name Date

2 Table of content Ethical aspects of using a job application with a focus on privacy ............................................................ 3 Evolution of AI in Recruitment ................................................................................................................... 3 Candidate Sourcing ................................................................................................................................ 4 Candidate Screening .............................................................................................................................. 4 Real-Time Insights .................................................................................................................................. 5 References ................................................................................................................................................. 6

3 Ethical aspects of using a job application with a focus on privacy Evolution of AI in Recruitment The recruiting industry is a great example of how the global impact of artificial intelligence (AI) has transformed many other sectors. Companies of all sizes and in all sectors have begun to embrace AI-powered recruiting tools, which have recently achieved notoriety and developed into sophisticated solutions (Balamurugan et al., 2022). These changes show how far AI has come and how useful it may be in the field of talent acquisition. Artificial intelligence (AI) recruiting technologies may automate formerly labor-intensive processes, which is a major benefit (Rudolph, 2021). Back in the day, recruiters had to put in a lot of time and effort to go through a mountain of resumes and applications (Rudolph, 2021). Tasks like initial applicant screening, communication scheduling, and resume processing are tedious and repetitious; however, AI can automate these processes. Not only does this minimize the hiring process, but it also frees up HR staff to work on higher-level, more strategic initiatives ( Saraswathi et al., 2023 ). Conventional approaches to applicant screening sometimes depend on predetermined criteria, which might unintentionally lead to prejudice or fail to recognize outstanding people with remarkable abilities or experiences (Tabassam et al., 2023). In contrast, artificial intelligence programs can sift through mountains of data in search of hidden connections and patterns (Rudolph, 2021). The use of machine learning allows these tools to improve their screening criteria over time, making the assessment of applicants more nuanced and fairer (Wood et al., 2018). This helps build more diverse and inclusive workforce and also leads to better recruiting choices. One other benefit of AI-powered technologies is the real-time information they provide into the hiring process (Wood et al., 2018). These tools provide data-driven analytics that show the whole recruiting process (Pessach et al., 2020). Job posting status, sourcing channel efficacy, and time to fill are just a few of the real-time indicators that recruiters have access to ( Cappelli and Rogovsky, 2023 ). Because of their analytical abilities, businesses are able to improve their recruiting tactics, react quickly to changes in the talent market, and make choices based on facts Eighty percent of companies are using AI-powered recruiting tools, according to a report by the Institute for AI and Ethics, which shows a revolutionary

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4 change in talent acquisition techniques (Black and van Esch, 2021). There are certain concerns about using AI in recruiting, especially around privacy and ethics, despite the clear advantages. Fairness, openness, and adherence to privacy legislation are crucial to the appropriate use of AI (Jobin et al., 2019). To fully use AI-powered recruiting tools while maintaining the honesty of the hiring process, it is crucial to find the sweet spot between efficiency and ethical concerns (Ahmed et al., 2023). Recruiters can see data in real time, like the state of job ads, how well sourcing methods are working, and how long it takes to fill roles ( Chowdhury et al., 2023). This ability to analyze data gives companies the power to make choices based on facts, improve their hiring methods, and quickly adapt to new talent market trends or problems (Allal-Chérif, et al., 2021). Even though there are clear benefits, using AI in hiring comes with some issues, especially when it comes to privacy and ethics. To use AI in a responsible way, one needs to pay close attention to fairness, openness, and privacy laws (Ahmed et al., 2023). Candidate Sourcing AI has had a profound impact on talent sourcing because to its ability to efficiently scour vast databases such as online resumes, social media profiles, and professional networks (Bresciani et al., 2021). Companies may find qualified applicants who meet their exacting standards with the help of this automated method (Ahmad et al., 2023). Artificial intelligence's speed and accuracy in analyzing and classifying large datasets gives recruiters a significant time advantage (Ahedo et al., 2023). Automating the first steps of talent discovery frees up recruiters to focus on higher-value activities, including interacting with applicants and developing genuine relationships. Utilizing AI for candidate sourcing streamlines the hiring process and opens up new avenues for talent acquisition ( Cohen & Feferman, 2016 ). When compared to more conventional approaches, AI algorithms have the potential to unearth varied candidates and hidden gems ( Cohen & Feferman, 2016 ). In addition to helping to build more diverse and inclusive workplaces, this also provides businesses with a wider range of talents and experiences.

5 Candidate Screening Artificial intelligence has transformed candidate screening by bringing in a new age of effectiveness and accuracy that surpasses those of conventional approaches ( Pasquale, 2015 ). Algorithms driven by artificial intelligence use data collected via video interviews and online quizzes to determine if a candidate is a good cultural fit and whether they have the necessary capabilities ( Pasquale, 2015 ). Artificial intelligence (AI) allows for a more detailed and thorough assessment of applicants by studying their replies and trends ( Pasquale, 2015 ). This solves the problem of inherent bias in conventional screening approaches and also decreases the likelihood of missing out on eligible people (Fu et al., 2020). Artificial intelligence systems are built to gain knowledge and adjust, honing their evaluation standards as they go (Ahedo et al., 2023). Flexibility like this helps make screenings more objective and fair, which in turn leads to better recruiting choices and promotes an inclusive and diverse work environment. Real-Time Insights Artificial intelligence (AI) plays an important part in the hiring process from sourcing and screening candidates all the way through to providing firms with actionable insights on the process in real-time. Tools powered by AI can monitor the recruiting process and find any inefficiencies or bottlenecks by following applicants' progress (Ahedo et al., 2023). Recruiters and businesses may improve recruiting results, streamline recruitment methods, and make data-driven choices with this analytical capacity (Tambe et al., 2019). Using data collected in real-time, businesses may see patterns, compare the efficacy of various sourcing channels, and make adjustments as needed. This guarantees that firms can adapt quickly to the changing dynamics of the talent market and simplifies the recruiting process (Ahmed et al., 2023). Moreover, a different survey from the Society for Human Resource Management highlights how 75% of HR experts believe that AI will have a major influence on the future of recruiting (Vrontis et al., 2022). A major worry among human resources experts is the possibility of bias in AI algorithms, which the survey confirm (Tewari and Pant, 2020).

6 References Ahedo, M., Al-Omari, H. H., & Al-Mazrui, M. N. (2023). Artificial intelligence in recruiting: A literature review and research agenda. Human Resource Management Review , 33(3), 100852. Ahmad, I., Aftab, M., & Shah, S. A. R. (2023). Artificial intelligence in human resource management: A review of its potential and challenges. International Journal of Human Resource Management, 34(8), 1543-1569. Allal-Chérif, O., Aranega, A.Y. and Sánchez, R.C., 2021. Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence. Technological Forecasting and Social Change, 169, p.120822. Balamurugan, S., Pathak, S., Jain, A., Gupta, S., Sharma, S. and Duggal, S. eds., 2022. Impact of Artificial Intelligence on Organizational Transformation. John Wiley & Sons. Black, J.S. and van Esch, P., 2021. AI-enabled recruiting in the war for talent. Business Horizons, 64(4), pp.513-524. Bresciani, S., Ferraris, A., Romano, M. and Santoro, G., 2021. Human resource management and digitalisation. In Digital transformation management for agile organizations: A compass to sail the digital world (pp. 117-138). Emerald Publishing Limited. Cappelli, P., & Rogovsky, N. (2023). Artificial intelligence in human resource management: A challenge for the human-centred agenda? International Labour Office Research Department Working Papers, 9953205929260. Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A. and Truong, L., 2023. Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), p.100899. Cohen, I. L., & Feferman, A. M. (2016). Unconscious bias in computer science education. ACM Transactions on Computing Education , 16(4), 1-12. Detroit center. 2023. talent and workforce effects in the age of AI. Retrieved by https://www2.deloitte.com/content/dam/insights/us/articles/6546_talent-and- workforce-effects-in-the-age-of-ai/DI_Talent-and-workforce-effects-in-the- age-of-AI.pdf

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7 Fu, R., Huang, Y. and Singh, P.V., 2020. Artificial intelligence and algorithmic bias: Source, detection, mitigation, and implications. In Pushing the Boundaries: Frontiers in Impactful OR/OM Research (pp. 39-63). INFORMS. Hewage, A., 2023. Exploring the Applicability of Artificial Intelligence in Recruitment and Selection Processes: A Focus on the Recruitment Phase. Journal of Human Resource and Sustainability Studies, 11(3), pp.603- 634. Jobin, A., Ienca, M. and Vayena, E., 2019. The global landscape of AI ethics guidelines. Nature machine intelligence, 1(9), pp.389-399. Pasquale, F. A. (2015). The black box society: The secret algorithms that control money and life. Harvard Business Review. Pessach, D., Singer, G., Avrahami, D., Ben-Gal, H.C., Shmueli, E. and Ben-Gal, I., 2020. Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming. Decision Support Systems, 134, p.113290. Rudolph, M., 2021. Artificial Intelligence in Recruiting. A Literature Review on Artificial Intelligence Technologies, Ethical Implications and the Resulting Chances and Risks. Saraswathi, T., Karthikeyan, M., Balakrishnan, C., Nithya, T. D., Maheswari, B., and Subramanian, S. R. 2023. Artificial Intelligence in Human Resource Management: Advancements, Implications and Future Prospects. Journal of Engineering and Technology Management , 27(3). Tabassam, A., Yaqoob, G., Cuong, V.H., Syed, M., Shahzadi, A. and Asghar, F., 2023. The Ethical Implication of Using Artificial Intelligence in Hiring and Promotion Decisions. Journal of Management & Educational Research Innovation, 1(2), pp.1-15. Tambe, P., Cappelli, P. and Yakubovich, V., 2019. Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), pp.15-42. Tewari, I. and Pant, M., 2020, December. Artificial intelligence reshaping human resource management: A review. In 2020 IEEE international conference on advent trends in multidisciplinary research and innovation (ICATMRI) (pp. 1- 4). IEEE.

8 Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A. and Trichina, E., 2022. Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management, 33(6), pp.1237-1266. Walford-Wright, G. and Scott-Jackson, W., 2018. Talent Rising; people analytics and technology driving talent acquisition strategy. Strategic HR Review, 17(5), pp.226-233. Wood, G., Cooke, F.L., Demirbag, M. and Kwong, C., 2018. International Journal of Human Resource Management (IJHRM) Special Issue on: International human resource management in contexts of high uncertainties. Zhang, J. and Chen, Z., 2023. Exploring Human Resource Management Digital Transformation in the Digital Age. Journal of the Knowledge Economy, pp.1- 17.

Ethical aspects of using a job application revised

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