Designing a Framework for Empowering Public Employees in the Age of Artificial Intelligence: Transition from Technical Competencies to Cognitive-Ethical Competencies
DOI:
https://doi.org/10.63053/ijmea.90Keywords:
Empowering Public Employees, Artificial IntelligenceAbstract
Introduction: The advent of artificial intelligence in the field of public administration has created the necessity for a fundamental redefinition of employee empowerment. The present study aimed to design a comprehensive framework for empowering public employees in the age of artificial intelligence, with emphasis on the transition from purely technical competencies to cognitive-ethical competencies.
Methodology: This study is applied-developmental in terms of purpose and mixed (sequential exploratory) in terms of method. In the qualitative phase, using the grounded theory method (Strauss and Corbin approach) and conducting 22 semi-structured interviews with experts in public administration, artificial intelligence, and organizational behavior, data were collected and analyzed in three stages of open, axial, and selective coding. In the quantitative phase, a researcher-made questionnaire based on the extracted components was designed and administered to a sample of 384 managers and senior experts of Iranian public organizations. Quantitative data were analyzed using structural equation modeling and confirmatory factor analysis in AMOS software.
Findings: Analysis of qualitative data led to the identification of 112 open codes, 24 concepts, and 12 main categories. The main categories were categorized into 6 paradigm components: (1) cognitive competencies (critical thinking, creative problem solving, data literacy, self-regulated learning), (2) ethical competencies (ethical judgment, algorithmic accountability, data privacy, transparency-seeking), (3) metacognitive competencies (awareness of biases, oversight of intelligent decisions, critical intervention ability, and hostility), (4) human-human competencies (including cooperation, management of cognitive conflict, and algorithmic modeling), (5) design effectiveness (including new evaluation system, continuous learning infrastructure, and organizational excellence), and (6) psychological-occupational health, hybrid decisions, and continuous learning. Quantitative results showed that the extracted model has a desirable fit (GFI=0.92, CFI=0.94, RMSEA=0.045) and all paths were confirmed at the significance level of 0.001.
Conclusion: Empowering public employees in the age of artificial intelligence requires a paradigm shift from traditional approaches based on technical skills training to a comprehensive and multidimensional approach based on cultivating cognitive, ethical, and metacognitive competencies. The framework presented in this study...
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