Beyond Human Judgment: Exploring the Impact of Artificial Intelligence on HR Decision-Making Efficiency and Fairness

Authors

  • Md Abul Khair Solutions Architect, Hitachi, USA
  • Ravikiran Mahadasa Senior ETL Lead, Data Inc., Charlotte, NC 28262, USA
  • Ferdouse Ara Tuli Assistant Professor, Department of Business Administration, ASA University Bangladesh, Dhaka, Bangladesh
  • Janaki Rama Phanendra Kumar Ande Architect, Tavant Technologies Inc., 3945 Freedom Cir #600, Santa Clara, CA 95054, USA

DOI:

https://doi.org/10.18034/gdeb.v9i2.730

Keywords:

Artificial Intelligence, Human Resources, HR Decision Making, Human Judgment, AI in HR, Ethical AI

Abstract

This study aims to evaluate the impact of artificial intelligence (AI) on the efficiency and fairness of human resources (HR) decision-making. The key goals are to determine how artificial intelligence improves decision-making efficiency, investigate the fairness issues involved in AI-driven human resource practices, and make policy suggestions for engaging in ethical HR practices. The approach utilized is known as secondary data analysis. It is used to synthesize insights and patterns by pulling upon previously published literature and empirical investigations; even though artificial intelligence technologies present an opportunity to optimize human resource operations and improve organizational performance, significant findings demonstrate that these technologies also create ethical problems connected to algorithmic biases and an absence of transparency. Regulatory oversight, ethical standards, data governance, diversity and inclusion programs, and constant monitoring and assessment are some of the policy implications that should be considered to guarantee responsible deployment of artificial intelligence in human resource contexts. When it comes to human resource decision-making, companies can embrace the revolutionary potential of artificial intelligence (AI) while maintaining ethical standards if they prioritize justice, openness, and accountability.

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References

Ande, J. R. P. K. (2018). Performance-Based Seismic Design of High-Rise Buildings: Incorporating Nonlinear Soil-Structure Interaction Effects. Engineering International, 6(2), 187–200. https://doi.org/10.18034/ei.v6i2.691 DOI: https://doi.org/10.18034/ei.v6i2.691

Ande, J. R. P. K., & Khair, M. A. (2019). High-Performance VLSI Architectures for Artificial Intelligence and Machine Learning Applications. International Journal of Reciprocal Symmetry and Theoretical Physics, 6, 20-30. https://upright.pub/index.php/ijrstp/article/view/121

Ande, J. R. P. K., Varghese, A., Mallipeddi, S. R., Goda, D. R., & Yerram, S. R. (2017). Modeling and Simulation of Electromagnetic Interference in Power Distribution Networks: Implications for Grid Stability. Asia Pacific Journal of Energy and Environment, 4(2), 71-80. https://doi.org/10.18034/apjee.v4i2.720 DOI: https://doi.org/10.18034/apjee.v4i2.720

Cervantes, J-A., Rodríguez, L-F., López, S., Ramos, F., Robles, F. (2016). Autonomous Agents and Ethical Decision-Making. Cognitive Computation, 8(2), 278-296. https://doi.org/10.1007/s12559-015-9362-8 DOI: https://doi.org/10.1007/s12559-015-9362-8

Goda, D. R. (2016). A Fully Analytical Back-gate Model for N-channel Gallium Nitrate MESFET's with Back Channel Implant. California State University, Northridge. http://hdl.handle.net/10211.3/176151

Goda, D. R., Yerram, S. R., & Mallipeddi, S. R. (2018). Stochastic Optimization Models for Supply Chain Management: Integrating Uncertainty into Decision-Making Processes. Global Disclosure of Economics and Business, 7(2), 123-136. https://doi.org/10.18034/gdeb.v7i2.725 DOI: https://doi.org/10.18034/gdeb.v7i2.725

Kahraman, C., Kaya, I., Çevikcan, E. (2011). Intelligence Decision Systems in Enterprise Information Management. Journal of Enterprise Information Management, 24(4), 360-379. https://doi.org/10.1108/17410391111148594 DOI: https://doi.org/10.1108/17410391111148594

Kapoor, B., Sherif, J. (2012). Human Resources in an Enriched Environment of Business Intelligence. Kybernetes, 41(10), 1625-1637. https://doi.org/10.1108/03684921211276792 DOI: https://doi.org/10.1108/03684921211276792

Katou, A. A. (2017). How Does Human Resource Management Influence Organisational Performance? An Integrative Approach-Based Analysis. International Journal of Productivity and Performance Management, 66(6), 797-821. https://doi.org/10.1108/IJPPM-01-2016-0004 DOI: https://doi.org/10.1108/IJPPM-01-2016-0004

Khoong, C. M. (1996). An Integrated System Framework and Analysis Methodology for Manpower Planning. International Journal of Manpower, 17(1), 26-46. https://doi.org/10.1108/01437729610110602 DOI: https://doi.org/10.1108/01437729610110602

Mahadasa, R. (2016). Blockchain Integration in Cloud Computing: A Promising Approach for Data Integrity and Trust. Technology & Management Review, 1, 14-20. https://upright.pub/index.php/tmr/article/view/113

Mahadasa, R. (2017). Decoding the Future: Artificial Intelligence in Healthcare. Malaysian Journal of Medical and Biological Research, 4(2), 167-174. https://mjmbr.my/index.php/mjmbr/article/view/683

Mahadasa, R., & Surarapu, P. (2016). Toward Green Clouds: Sustainable Practices and Energy-Efficient Solutions in Cloud Computing. Asia Pacific Journal of Energy and Environment, 3(2), 83-88. https://doi.org/10.18034/apjee.v3i2.713 DOI: https://doi.org/10.18034/apjee.v3i2.713

Mahadasa, R., Goda, D. R., & Surarapu, P. (2019). Innovations in Energy Harvesting Technologies for Wireless Sensor Networks: Towards Self-Powered Systems. Asia Pacific Journal of Energy and Environment, 6(2), 101-112. https://doi.org/10.18034/apjee.v6i2.727 DOI: https://doi.org/10.18034/apjee.v6i2.727

Mahadasa, R., Surarapu, P., Vadiyala, V. R., & Baddam, P. R. (2020). Utilization of Agricultural Drones in Farming by Harnessing the Power of Aerial Intelligence. Malaysian Journal of Medical and Biological Research, 7(2), 135-144. https://mjmbr.my/index.php/mjmbr/article/view/684

Mallipeddi, S. R., & Goda, D. R. (2018). Solid-State Electrolytes for High-Energy-Density Lithium-Ion Batteries: Challenges and Opportunities. Asia Pacific Journal of Energy and Environment, 5(2), 103-112. https://doi.org/10.18034/apjee.v5i2.726 DOI: https://doi.org/10.18034/apjee.v5i2.726

Mallipeddi, S. R., Goda, D. R., Yerram, S. R., Varghese, A., & Ande, J. R. P. K. (2017). Telemedicine and Beyond: Navigating the Frontier of Medical Technology. Technology & Management Review, 2, 37-50. https://upright.pub/index.php/tmr/article/view/118

Mallipeddi, S. R., Lushbough, C. M., & Gnimpieba, E. Z. (2014). Reference Integrator: a workflow for similarity driven multi-sources publication merging. The Steering Committee of the World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp). https://www.proquest.com/docview/1648971371

Mandapuram, M., Mahadasa, R., & Surarapu, P. (2019). Evolution of Smart Farming: Integrating IoT and AI in Agricultural Engineering. Global Disclosure of Economics and Business, 8(2), 165-178. https://doi.org/10.18034/gdeb.v8i2.714 DOI: https://doi.org/10.18034/gdeb.v8i2.714

Meskó, B., Hetényi, G., Gyorffy, Z. (2018). Will Artificial Intelligence Solve the Human Resource Crisis in Healthcare?. BMC Health Services Research, 18. https://doi.org/10.1186/s12913-018-3359-4 DOI: https://doi.org/10.1186/s12913-018-3359-4

Surarapu, P. (2016). Emerging Trends in Smart Grid Technologies: An Overview of Future Power Systems. International Journal of Reciprocal Symmetry and Theoretical Physics, 3, 17-24. https://upright.pub/index.php/ijrstp/article/view/114

Surarapu, P. (2017). Security Matters: Safeguarding Java Applications in an Era of Increasing Cyber Threats. Asian Journal of Applied Science and Engineering, 6(1), 169–176. https://doi.org/10.18034/ajase.v6i1.82 DOI: https://doi.org/10.18034/ajase.v6i1.82

Surarapu, P., & Mahadasa, R. (2017). Enhancing Web Development through the Utilization of Cutting-Edge HTML5. Technology & Management Review, 2, 25-36. https://upright.pub/index.php/tmr/article/view/115

Surarapu, P., Mahadasa, R., & Dekkati, S. (2018). Examination of Nascent Technologies in E-Accounting: A Study on the Prospective Trajectory of Accounting. Asian Accounting and Auditing Advancement, 9(1), 89–100. https://4ajournal.com/article/view/83

Surarapu, P., Mahadasa, R., & Dekkati, S. (2018). Examination of Nascent Technologies in E-Accounting: A Study on the Prospective Trajectory of Accounting. Asian Accounting and Auditing Advancement, 9(1), 89–100. https://4ajournal.com/article/view/83

Triki, C., Zekri, S., Al-maktoumi, A., Fallahnia, M. (2017). An Artificial Intelligence Approach for the Stochastic Management of Coastal Aquifers. Water Resources Management, 31(15), 4925-4939. https://doi.org/10.1007/s11269-017-1786-3 DOI: https://doi.org/10.1007/s11269-017-1786-3

Tuli, F. A., Varghese, A., & Ande, J. R. P. K. (2018). Data-Driven Decision Making: A Framework for Integrating Workforce Analytics and Predictive HR Metrics in Digitalized Environments. Global Disclosure of Economics and Business, 7(2), 109-122. https://doi.org/10.18034/gdeb.v7i2.724 DOI: https://doi.org/10.18034/gdeb.v7i2.724

Verma, N., Rangnekar, S. (2015). General decision making style: evidence from India. South Asian Journal of Global Business Research, 4(1), 85-109. https://doi.org/10.1108/SAJGBR-09-2013-0073 DOI: https://doi.org/10.1108/SAJGBR-09-2013-0073

Wirtky, T., Laumer, S., Eckhardt, A., Weitzel, T. (2016). On the Untapped Value of e-HRM: A Literature Review. Communications of the Association for Information Systems, 38(2). https://doi.org/10.17705/1CAIS.03802 DOI: https://doi.org/10.17705/1CAIS.03802

Wisler, J. C. (2018). U.S. CEOs of SBUs in Luxury Goods Organizations: A Mixed Methods Comparison of Ethical Decision-Making Profiles. Journal of Business Ethics: JBE, 149(2), 443-518. https://doi.org/10.1007/s10551-016-3069-y DOI: https://doi.org/10.1007/s10551-016-3069-y

Yerram, S. R., & Varghese, A. (2018). Entrepreneurial Innovation and Export Diversification: Strategies for India’s Global Trade Expansion. American Journal of Trade and Policy, 5(3), 151–160. https://doi.org/10.18034/ajtp.v5i3.692 DOI: https://doi.org/10.18034/ajtp.v5i3.692

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Published

2020-12-31

How to Cite

Khair, M. A., Mahadasa, R., Tuli, F. A., & Ande, J. R. P. K. (2020). Beyond Human Judgment: Exploring the Impact of Artificial Intelligence on HR Decision-Making Efficiency and Fairness. Global Disclosure of Economics and Business, 9(2), 163-176. https://doi.org/10.18034/gdeb.v9i2.730

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