PSYCHOLOGICAL PROFILING FOR SECURITY-SENSITIVE ENGINEERING ROLES USING A HUMAN-CENTRIC SCREENING FRAMEWORK
Keywords:
psychological profiling, security-sensitive roles, human-centric screening, engineering psychology, situational judgment, behavioral assessment, risk suitabilityAbstract
Careers in security-sensitive industries such as aerospace, defence, and critical infrastructure will require more than simply technical skills, but also psychometric resilience and stress-honed reliability, along with demonstrated ethical reasoning. Human capacity, accessibility, and judgment are often overlooked in traditional hiring approaches. This article proposes a human-centric evaluation framework to support hiring decisions for security-focused activity roles within engineering. The framework proposes to introduce psychological profiling into the selection process. The human-centered framework would assess individual risk factors and resilience, and provide SJTs (situational judgement tasks) and behavioral simulations to measure a candidate's response and reaction to high-stakes situations. By presenting a potential candidate's psychometric sophistication along with emergent simulations, the appraisal framework provides a more comprehensive and contextual view of a person's suitability for risk-sensitive engineering. Together with a focus on psychometric statistical rigor and empirical acceptability, the human-centered framework proposed ensures fairness and transparency, in addition to maximizing ethical integrity in alignment with factors needed by organizations and best psychology practices surrounding human cognition and action. This paper suggests a systemic way of formalizing ethical hiring approaches to improve talent decisions in high-consequence engineering space and make systems safer by having the right people choose to be in the right places at the right times, and maximizing the chances in reliability, performance, and teamwork while providing a framework for longitudinal study in wound prediction and trust cue calibration; the presented framework is designed to support continuous improvement.
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