Flawed Deployment of AI Sensor Technologies and Tools in National Security and Biodefense Executive Recruitment
DOI:
https://doi.org/10.26740/vubeta.v3i2.43923Keywords:
Artificial Intelligence , Talent Management , Hiring, Discrimination , RecruitingAbstract
Artificial intelligence (AI) and sensor-enabled technologies are reshaping recruitment and human resources (HR) management by enabling automated, data-driven candidate evaluation. However, sensor-driven AI systems, such as facial analysis, voice recognition, and biometric monitoring, pose significant ethical and operational risks, particularly the perpetuation of historical biases and opaque decision-making processes. This study investigates these tensions through qualitative analysis of expert interviews with AI developers, HR professionals, and diversity, equity, and inclusion (DEI) strategists, coupled with real-world case examples, including a biodefense firm whose vision-based AI system unintentionally excluded qualified candidates. Findings reveal that while AI-sensor platforms offer efficiency and personalized experiences, they can amplify bias, obscure accountability, and challenge legal compliance if not carefully designed and governed. Participants highlighted urgent needs for algorithmic transparency, human oversight, and inclusive system design to mitigate these risks. In response, this study proposes a human-centered framework for the ethical deployment of AI-sensor technologies in hiring, emphasizing continuous bias auditing, clear governance structures, and regulatory alignment. Ultimately, it argues that the transformative potential of intelligent sensing in HR depends not only on technical sophistication but on embedding these tools within sociotechnical systems committed to fairness, accountability, and inclusion.
References
[1] Hmoud B., Laszlo V. Will, “Artificial Intelligence Take Over Human Resources Recruitment and Selection?,” Netw Intell Stud, vol. 7, no. 13, pp. 21–30, 2019.
[2] Raveendra P., Satish Y., Singh P., “Changing Landscape of Recruitment Industry: A Study on the Impact of Artificial Intelligence on Eliminating Hiring Bias from Recruitment and Selection Process,” J Comput Theor Nanosci, vol. 17, no. 9, pp. 4404–4407, 2020. https://doi.org/10.1166/jctn.2020.9086
[3] Johansson J., Herranen S., “The Application of Artificial Intelligence (AI) in Human Resource Management: Current State of AI and Its Impact on the Traditional Recruitment Process,” Bachelor thesis. Jonkoping University, Jönköping, Sweden, 2019.
[4] Zhang J., Chen Z., “Exploring Human Resource Management Digital Transformation in the Digital Age,” J Knowl Econ, vol. 15, pp. 1482–1498, 2023. https://doi.org/10.1007/s13132-023-01214-y
[5] Bornstein S., “Antidiscriminatory Algorithms,” Alabama Law Rev, vol. 70, no. 519, 2018
[6] Miasato A., Silva F.R., “Artificial Intelligence as an Instrument of Discrimination in Workforce Recruitment,” Acta Univ Sapientiae: Legal Stud, vol. 8, no. 2, pp. 191–212, 2019. https://doi.org/10.47745/AUSLEG.2019.8.2.04
[7] Raub M. Bots, Bias and Big Data, “Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices,”Ark Law Rev, vol. 71, no. 529, 2018
[8] Burrell D.N., McAndrew I., “Exploring the Ethical Dynamics of the Use of Artificial Intelligence (AI) in Hiring in Healthcare Organizations,” Land Forces Acad Rev., vol. 28, no. 4, pp. 309–321, 2023. https://doi.org/10.2478/raft-2023-0037
[9] Burrell D.N., Diperi D.L., Weaver R.M., “Creating Inclusive Cultures for Women in Automation and Information Technology Careers and Occupations,” I. Management Association (Ed.), Research Anthology on Challenges for Women in Leadership Roles IGI Global, pp. 749–765, 2021. https://doi.org/10.4018/978-1-7998-8592-4.ch041
[10] Malik A., “AI Bias In Recruitment: Ethical Implications And Transparency,” Forbes, 2023.
[11] Lytton C., “AI Hiring Tools May Be Filtering out the Best Job Applicants,” BBC, February 16, 2024.
[12] Zapata D., “New Study Finds AI-Enabled Anti-Black Bias in Recruiting,” Thomson Reuters, 2021.
[13] Tran T.B.H., Choi S.B., “Effects of Inclusive Leadership on Organizational Citizenship Behavior: The Mediating Roles of Organizational Justice and Learning Culture,” J Pacific Rim Psy., vol. 13, e17, 2019. https://doi.org/10.1017/prp.2019.10
[14] Graso M., Camps J., Strah N., Brebels L., “Organizational Justice Enactment: An Agent-Focused Review and Path Forward,” J Voc Behavior, vol. 116, 103296, 2020. https://doi.org/10.1016/j.jvb.2019.03.007
[15] Kelan E.K., “Algorithmic Inclusion: Shaping the Predictive Algorithms of Artificial Intelligence in Hiring,” Hum Res Man J, vol. 34, no. 3, pp. 694–707, 2023. https://doi.org/10.1111/1748-8583.12511
[16] Zoričić D., Knežević G., Miletić M., Dolinar D., Sprčić D.M., “Integrated Risk Analysis of Aggregators: Policy Implications for the Development of the Competitive Aggregator Industry,” Energies, vol. 15, no. 14, 2022. https://doi.org/10.3390/en15145076
[17] Nandonde F.A. A, “Pestle Analysis of International Retailing in the East African Community,” Global Business & Organizational Excellence, vol. 38, no. 4, pp. 54–61, 2019. https://doi.org/10.1002/joe.21935
[18] Collins R., “A Graphical Method for Exploring the Business Environment”, Henley Business School: Henley-on-Thames, England, 2010.
[19] An M., Lin J., Luo X.R., “The Impact of Human AI Skills on Organizational Innovation: The Moderating Role of Digital Organizational Culture.,” J Bus Res., vol. 182, 114786, 2024. https://doi.org/10.1016/j.jbusres.2024.114786
[20] Bley K., Fredriksen S.F.B., Skjærvik M.E., Pappas I.O., “The role of organizational culture on artificial intelligence capabilities and organizational performance,” Conference on e-Business, e-Services and e-Society Cham, Springer International, pp. 13-24, 2022. https://doi.org/10.1007/978-3-031-15342-6_2
[21] Chaudhary S., Kumar S., Kumar K., Kathuria S., Negi P., Chhabra G., “Role of artificial intelligence in organizational culture and workplace,” International Conference on Sustainable Computing and Data Communication Systems, pp. 528–532, 2023. https://doi.org/10.1109/ICSCDS56580.2023.10104697
[22] Chourasia S., Dhama A., Bhardwaj G., “AI-driven organizational culture evolution: A critical review. In 2024 International Conference on Communication,” Computer Sciences and Engineering, pp. 1839–1844, 2024. https://doi.org/10.1109/IC3SE62002.2024.10592949
[23] Cuevas A.G., Boen C., “Tip of the Iceberg: Measuring Racial Discrimination in Studies of Health,” SH, vol. 37, no. 5, 1043–1050, 2021. https://doi.org/10.1002/smi.3047
[24] Wazed S., “Council Post: Grow Your Organization with Top Talent Using the Iceberg Interview Model,” Forbes, August 2, 2018.
[25] Kotter J.P., “Leading Change, with a New Preface by the Author,” Harvard Business Press: Cambridge, Massachusetts, 2013.
[26] Caulfield J.L., Brenner E.F., “Resolving Complex Community Problems: Applying Collective Leadership and Kotter’s Change Model to Wicked Problems within Social System Networks,” NML, vol. 30, no. 3, pp. 509–524, 2020. https://doi.org/10.1002/nml.21399
[27] Miller J.L., “Managing Transitions: Using William Bridges’ Transition Model and a Change Style Assessment Instrument to Inform Strategies and Measure Progress in Organizational Change Management,”12th International Conference on Performance Measurement in Libraries Proceedings, p. 357, 2017.
[28] Huff A., Burrell D.N., Richardson K., Springs D., Aridi A.S., Crowe M.M., Lewis E., “Illegal Pregnancy Discrimination Is a Severe Business, Legal, and Public Health Issue,” D. Burrell, Ed., IGI Global, pp. 119–129, 2023. https://doi.org/10.4018/978-1-6684-8691-7.ch008
[29] Burrell D.N., Morin S.L., “The Importance of White Males with Power, Resources, and Influence as Allies Supporting Diversity in the US Workplace,” Societies, vol. 15, no. 5, 128, 2025. https://doi.org/10.3390/soc15050128
[30] McLester Q., Burrell D. N., Nobles C., and Castillo I., “Advancing Knowledge About Sexual Harassment Is a Critical Aspect of Organizational Development for All Employees,” International Journal of Knowledge-Based Organizations, vol. 11, no. 4, pp. 48-60, 2021. http://doi.org/10.4018/IJKBO.2021100104
[31] Hunkenschroer AL, Luetge C., “Ethics of AI-enabled recruiting and selection: A review and research agenda,” Journal of Business Ethics Jul., vol. 178, no. 4, pp. 977-1007, 2022. https://doi.org/10.1007/s10551-022-05049-6
[32] Ujlayan A, Bhattacharya S, Sonakshi, “A Machine Learning-Based AI Framework to Optimize the Recruitment Screening Process,” International Journal of Global Business and Competitiveness, pp. 38-53, 2023. https://doi.org/10.1007/s42943-023-00086-y
[33] Koechling A, Wehner MC, Warkocz J., “Can I show my skills? Affective responses to artificial intelligence in the recruitment process,” Review of Managerial Science, vol. 17, no. 6, 2109-38, 2023. https://doi.org/10.1007/s11846-021-00514-4
[34] Lukacik ER, Bourdage JS, Roulin N., “Into the void: A conceptual model and research agenda for the design and use of asynchronous video interviews,” Human Resource Management Review, vol. 32, no. 1, 100789, 2022. https://doi.org/10.1016/j.hrmr.2020.100789
[35] Ajunwa I., “Automated video interviewing as the new phrenology,” Berkeley Technology Law Journal, vol. 36, no. 3, 1173-226, 2021.
[36] Kammerer B., “Hired by a robot: The legal implications of artificial intelligence video interviews and advocating for greater protection of job applicants,” Iowa L. Rev., 107, 817, 2021.
[37] Basch JM, Melchers KG, Kurz A, Krieger M, Miller L., “It takes more than a good camera: which factors contribute to differences between face-to-face interviews and videoconference interviews regarding performance ratings and interviewee perceptions?” Journal of business and psychology, vol. 36, 921-40, 2021. https://doi.org/10.1007/s10869-020-09714-3
[38] Roulin N, Wong O, Langer M, Bourdage JS., “Is more always better? How preparation time and re-recording opportunities impact fairness, anxiety, impression management, and performance in asynchronous video interviews,” European Journal of Work and Organizational Psychology, vol. 32, no. 3, 333-45, 2023. https://doi.org/10.1080/1359432X.2022.2156862
[39] Albaroudi E, Mansouri T, Alameer A., “A comprehensive review of AI techniques for addressing algorithmic bias in job hiring,” Ai, vol. 5, no. 1, pp. 383-404, 2024. https://doi.org/10.3390/ai5010019
[40] Peng A, Nushi B, Kiciman E, Inkpen K, Kamar E., “Investigations of performance and bias in human-AI teamwork in hiring,” Proceedings of the AAAI conference on artificial intelligence, vol. 36, no. 11, pp. 12089-12097, 2022. https://doi.org/10.1609/aaai.v36i11.21468
[41] Kassir S, Baker L, Dolphin J, Polli F., “AI for hiring in context: a perspective on overcoming the unique challenges of employment research to mitigate disparate impact,”AI and Ethics, vol. 3, no. 3, 845-68, 2023. https://doi.org/10.1007/s43681-022-00208-x
[42] De Almeida PG, dos Santos CD, Farias JS., “Artificial intelligence regulation: a framework for governance,” Ethics and Information Technology, vol. 23, no. 3, 505-25, 2021. https://doi.org/10.1007/s10676-021-09593-z
[43] Wirtz BW, Weyerer JC, Kehl I., “Governance of artificial intelligence: A risk and guideline-based integrative framework,” Government information quarterly, vol. 39, no. 4, 101685, 2022. https://doi.org/10.1016/j.giq.2022.101685
[44] Balasubramaniam N, Kauppinen M, Rannisto A, Hiekkanen K, Kujala S., “Transparency and explainability of AI systems: From ethical guidelines to requirements,” Information and Software Technology, 159, 107197, 2023. https://doi.org/10.1016/j.infsof.2023.107197
[45] Patidar N, Mishra S, Jain R, Prajapati D, Solanki A, Suthar R, Patel K, Patel H., “Transparency in AI decision making: A survey of explainable AI methods and applications,” Advances of Robotic Technology, vol. 2, no. 1, 2024. https://doi.org/10.23880/art-16000110
[46] Balasubramaniam N, Kauppinen M, Hiekkanen K, Kujala S., “Transparency and explainability of AI systems: ethical guidelines in practice,” International working conference on requirements engineering: foundation for software quality, pp. 3-18, 2022. https://doi.org/10.1007/978-3-030-98464-9_1
[47] Oyeniran CO, Adewusi AO, Adeleke AG, Akwawa LA, Azubuko CF., “Ethical AI: Addressing bias in machine learning models and software applications,” Computer Science & IT Research Journal, vol. 3, no. 3, 115-26, 2022. https://doi.org/10.51594/csitrj.v3i3.1559
[48] Varona D, Suárez JL., “Discrimination, bias, fairness, and trustworthy AI,” Applied Sciences, vol. 12, no. 12, 5826, 2022. https://doi.org/10.3390/app12125826
[49] Prapanca A, Nasreddine Belhaouas, Imed Mahmoud, “Modified FATA Morgana Algorithm Based on Levy Flight,” Vokasi Unesa Bull. Eng. Technol. Appl. Sci., vol. 2, no. 1, pp. 1-11, 2025. https://doi.org/10.26740/vubeta.v2i1.37066
[50] Hamam H., “Rethinking Intelligence: From Human Cognition to Artificial Futures,” Vokasi Unesa Bull. Eng. Technol. Appl. Sci., vol. 2, no. 3, 531-48, 2025. https://doi.org/10.26740/vubeta.v2i3.44232
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Darrell Norman Burrell, Patricia Haley

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Abstract views: 38
,
PDF Downloads: 14





