Topic 16: Artificial Intelligence (AI) and HRD
Abstract
Topic 16 allows students to discuss scenarios of how artificial intelligence (AI) and HRD are linked. The expertise of AI is not ethically sound, and the human expertise of HRD professionals can alleviate some of these concerns. Understanding the gap between HRD and explainable AI is important as technology becomes more integrated into workplace activities.
Scenario 1: AI and Data Analysis
Bethany started her new position two weeks ago and is excited to be doing data entry work. She has to analyze the human resource materials before inputting the content into the human resource information system (HRIS). Unbeknownst to Bethany, her organization has a plan to begin, in three months, using AI to replace the work that she does. Bethany has been asked to work with information system (IS) and information technology (IT) employees to make sure that the process that she is using to input the data is correct. Bethany does not discuss the way that she analyzes the data. She only informs IS and IT employees of the steps that she takes to input the data.
When the organization implements its new AI generated HRIS, sensitive confidential employee data is incorrectly inputted throughout the system. Bethany is asked to meet with leaders including her supervisor and leaders from IS and IT. When asked why the data is incorrect in the new system, Bethany informs them that she has an analysis process that she did not share because she did not know that AI would be used to input the data.
Discussion Questions:
- What do you believe to be the main reason that data was incorrectly inputted into the HRIS?
- How would you correct this situation and make amends to employees whose data was incorrectly distributed throughout the organization?
- What could have been to prevent this situation from occurring?
Scenario 2: Fairness of AI in Promotion
Randy has been with his organization for 10 years and has been working towards a promotion on his job for five years. He has done everything that his supervisor has asked and has been proactive in leading new initiatives. Despite all of Randy’s hard work, his organization has determined that they can save money by using machine learning and AI to replace him. They also used AI to determine how much work Randy actually performed each day. The organization used AI data in its decision to downsize and has informed Randy that his position is being eliminated. They do let him know that should he want to apply for other jobs in other divisions of the organization, that opportunity is available. Randy is in shock and decides to meet with HR to find out why his position was eliminated. When told about his work being done by AI, Randy becomes angry.
Discussion Questions:
- Do you think that it was a fair use of AI by the company? Why?
- Pretend that you are Randy, would you seek another job with the organization?
- Please find and share a real world example of how AI is being used to replace employees?
Supplemental Readings
Bellamy, R. K., Dey, K., Hind, M., Hoffman, S. C., Houde, S., Kannan, K., … & Nagar, S. (2019). AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM Journal of Research and Development, 63(4/5), 4-1.
Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 24(2), 239-257.
Chermack, T. J. (2003). Decision-making expertise at the core of human resource development. Advances in Developing Human Resources, 5(4), 365–377.
Davies, J. (2016). Program good ethics into artificial intelligence. Nature, 538, 291.
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Githens, R. P., Dirani, K., Gitonga, J. W., & Teng, Y. T. (2008). Technology-related research in HRD publications: An analysis of content and metaperspectives from 2000 to 2006. Human Resource Development Quarterly, 19(3), 191–215. doi:10.1002/hrdq.1236
Hew, P. C. (2014). Artificial moral agents are infeasible with foreseeable technologies. Ethics and Information Technology, 16(3), 197-206.
Hirschi, A. (2018). The fourth industrial revolution: Issues and implications for career research and practice. The Career Development Quarterly, 66(3), 192-204.
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Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. University of Louisville Law Review, 57(2), 313.
Kok, J. N., Boers, E. J. W., Kosters, W.A., & Van der Putten, P. (2009). Artificial intelligence: Definition, trends, techniques, and cases. In J. N. Kok (Ed.), Artificial intelligence (pp. 1 – 20). Encyclopedia of Life Support Systems.
McQuay, L. (2018). Will robots duplicate or surpass us? The impact of job automation on tasks, productivity, and work. Psychosociological Issues in Human Resource Management, 6(2), 86-91. http://doi.org/10.22381/PIHRM6220189
Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2020, January). Mitigating bias in algorithmic hiring: Evaluating claims and practices. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 469-481).
Rai, A. (2020). Explainable AI: From black box to glass box. Journal of the Academy of Marketing Science, 48(1), 137-141.
Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020). Designing fair AI for managing employees in organizations: A review, critique, and design agenda. Human–Computer Interaction, 1-31. DOI: 10.1080/07370024.2020.1735391
Roy, V. V., Vértesy, D., & Vivarelli, M. (2018). Technology and employment: Mass unemployment or job creation? Empirical evidence from European patenting firms. Research Policy, 47(9), 1762-1776. doi:10.1016/j.respol.2018.06.008
Tzafestas, S. G. (2018). Ethics in robotics and automation: A general view. International Robotics & Automation Journal, 4, 229–234.
Upadhyay, A., & Khandelwal, K. (2019). Artificial intelligence-based training learning from application. Development and Learning in Organizations: An International Journal, 33(2), 20-23. doi:10.1108/DLO-05-2018-0058
