Article Review #2 – Cybersecurity and AI Affecting Users
Introduction
The article “Impact of Cybersecurity and AI’s Related Factors on Incident Reporting Suspicious Behaviour and Employees Stress: Moderating Role of Cybersecurity Training,” studies how cybersecurity and AI (Artificial intelligence) influence employee behavior and stress in the workplace. As organizations rely more on digital security and AI, it’s paramount to understand how these technologies affect workers, especially in high-pressure environments that require strict attention and compliance with rules. This study examines how factors related to cybersecurity and AI affect employees’ chances of reporting suspicious behavior and their stress levels, underlining the important role of cybersecurity training. The article provides insights into how these elements connect to social science, workplace climate, and marginalized groups’ mental health.
Research Questions and Methods
This study looks at how cybersecurity and artificial intelligence (AI) affect employee stress and how they report incidents. Cybersecurity training can reduce stress and encourage reporting. The main idea is that cybersecurity and AI can increase stress, but training can lower that stress and promote compliance with security measures. The study uses surveys to collect data on employee experiences and analyzes this data with statistical methods like regression and moderation analysis. This method helps to clearly understand how training can reduce stress and support better security practices.
Data and Analysis
The data analysis includes calculating descriptive statistics for cybersecurity awareness and behavior factors. These factors consist of Cyber Security Incident Management (CSIM), Cyber Security Awareness (CSA), Intention to Use AI (IU-AI), Perceived Threats in AI (PT-AI), Cyber Training (CT), Incident Reporting Suspicious Behavior (IRSB), and Employee Stress Level (ESL). Each factor is evaluated on a 1 to 5 scale, where the mean score represents the typical response, and the standard deviation shows response variability (Muthuswamy, 2024).
Social Science Principles
The article exemplifies a clearer understanding of social science principles, such as objectivity, ethical neutrality, and determinism. Their quantitative research method of conducting surveys to gather data on employee experiences with cybersecurity factors displays objectivity. Because of this, it relieves any chance of bias, which leads to Ethical Neutrality. This article achieves ethical neutrality by focusing on the effects of cybersecurity and AI measures, employee stress, and the impact of training. Lastly, the article displays determinism in the form of its research question that cybersecurity training can affect the impact of AI and cybersecurity factors on employees, thereby reducing stress and encouraging incident reporting.
Concepts
The article displays concepts discussed in class, such as human factors, behavioral theories, and human-centered cybersecurity. As mentioned previously, the article’s base is the human factor. It examines how cybersecurity measures and AI-related factors affect employees’ stress levels and behavior. Human factors research focuses on understanding how people interact with systems, especially in ways that impact their well-being and performance, and how that ties into stress and incident reporting. The human factor in the article ties in with the behavioral theory concept as the researchers analyze how the training may improve employee stress and increase reporting. These concepts found in the article contribute to a human-centered cybersecurity approach by recognizing that employees are essential actors in cybersecurity ecosystems, not just passive participants.
Contributions
The article highlights how cybersecurity training can address concerns specific to marginalized groups, like limited access to professional development and heightened stress from surveillance. Marginalized employees may need more equal opportunities for training, which can make handling cybersecurity tasks more challenging and stressful. Additionally, they may feel extra pressure from AI monitoring, which can sometimes feel targeted. The study’s findings support improved mental health through targeted training, helping reduce stress and promote security compliance. This approach strengthens cybersecurity and fosters a more inclusive and supportive work environment. This study provides a basis for improving overall cyber training programs at companies by improving morale and strengthening reporting frequency.
Conclusion
The article “Impact of Cybersecurity and AI’s Related Factors on Incident Reporting Suspicious Behaviour and Employees Stress: Moderating Role of Cybersecurity Training,” highlights the significant impact of cybersecurity and AI on employees’ stress and reporting behaviors, underscoring the essential role of targeted training in creating a supportive security environment. By focusing on human-centered cybersecurity and addressing marginalized groups’ unique challenges, the study emphasizes the importance of inclusive training programs to reduce stress, improve compliance, and enhance workplace fairness. These findings contribute to a stronger, more resilient organizational culture, where cybersecurity efforts are balanced with employee well-being, benefiting individual workers and overall security.
References
Muthuswamy, V. V. (2024, June 5). View of Impact of Cybersecurity and AI’s Related Factors on Incident Reporting Suspicious Behaviour and Employees Stress: Moderating Role of Cybersecurity Training. International Journal of Cyber Criminology, 18(1), 83-107. 10.5281