Human Perception of Intelligent Systems and Its Relationship to Professional Information Processing Among a Sample of Workers – The Biometric Technical Center – A Field Study in the City of Laghouat.
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Keywords

Perception of Smart Systems; Professional Information Processing.

How to Cite

Merzouk Naima, & Farsi Ibrahimelkhalil. (2026). Human Perception of Intelligent Systems and Its Relationship to Professional Information Processing Among a Sample of Workers – The Biometric Technical Center – A Field Study in the City of Laghouat. `Cadernos De Pós-Graduação Em Direito Político E Econômico, 26(2), 235–251. Retrieved from https://ceapress.org/index.php/cpgdpe/article/view/348

Abstract

The present study aimed to explore the relationship between the perception of smart systems and professional information processing among employees at the National Biometric Center in the Wilaya of Laghouat. Additionally, it sought to determine the levels of these variables and detect any statistically significant differences based on gender (male/female). To achieve these objectives, a descriptive correlational and comparative method was adopted. Appropriate psychometric measurement tools were applied to a sample of center employees. Following the statistical analysis of the data, the study revealed the following main results:

  • There is a statistically significant positive (direct) correlational relationship between the perception of smart systems and professional information processing among the sample members.
  • There are no statistically significant differences in the levels of perceiving smart systems and professional information processing attributable to the gender variable (males/females), reflecting cognitive and professional homogeneity within the digital work environment.

Based on these findings, the study recommended the necessity of enhancing digital awareness by organizing specialized training courses that focus on understanding the philosophy of smart systems. It also emphasized designing user-friendly interfaces to reduce cognitive load under work pressure and prioritizing the psychological and cognitive well-being of employees to minimize technical distractions.

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