AI: Lost and Found

Artificial Intelligence (AI) refers to computer-based systems that can assist or automate decision-making, often replacing or augmenting human judgment. AI is transforming work management by not only supporting workplace processes but, in some cases, autonomously overseeing them through data-driven decision-making (Jarota, 2023). 

The increasing adoption of AI has significant implications for employee health, safety, and wellbeing. The COVID-19 pandemic accelerated digitalisation and the integration of AI-driven technologies in the workplace (Cebulla et al., 2023). AI englobes a wide range of technologies that interact with human workers in various ways, making it crucial to examine how tasks evolve and how these changes impact employees (Bankins et al., 2023). As AI becomes more present in work environments, it is essential to explore both its advantages and potential psychosocial risks, such as job displacement, social isolation, and changes in job roles.   

Meaningful work refers to the perception that one’s work holds value, significance, or a higher purpose, contributing positively to the worker’s wellbeing and flourishing. AI has the potential to expand the range of higher-order, meaningful human tasks by automating routine jobs and enabling employees to focus on more creative or strategic responsibilities. However, there are concerns that AI may degrade the nature of human work, deskilling workers, and even eliminating jobs entirely (Bankins et al., 2023). While AI can empower employees by enhancing their autonomy and upskilling them, it can simultaneously lead to increased control and dehumanization, resulting in a loss of meaningful engagement in work. 

The psychosocial risks associated with AI use in the workplace are significant, particularly regarding employee mental health. One of the most evident risks is stress, especially when AI alters the nature of the work or leads to job displacement. As tasks traditionally performed by humans become automated, employees may experience feelings of inadequacy, anxiety, and uncertainty about their roles. Job insecurity, particularly when workers fear losing their positions due to AI-driven technological advancements, further exacerbates this stress (Jarota, 2023). The anxiety stemming from such uncertainty can manifest as job strain, a condition associated with both psychological and physical health problems, including depression, anxiety, and cardiovascular issues (Madsen et al., 2017). 

Mental health is also influenced by physical risks linked to AI’s integration, particularly for remote workers. The use of electronic communication and AI tools in remote work environments can blur the boundaries between work and personal life. As work trespasses on personal time, employees may find themselves working longer hours to avoid the perception of falling behind or losing their jobs. This lack of clear boundaries between work and leisure can contribute to burnout, fatigue, and ultimately affect workers’ wellbeing (Jarota, 2023). 

On the bright side, AI offers significant benefits to organisations, enhancing service quality, efficiency, and profitability. By automating routine tasks, AI frees up employees to focus on higher-value work, boosting overall productivity. 

AI improves the quality and speed of services by automating repetitive tasks, leading to faster decision-making and higher customer satisfaction. It can take over dangerous or tedious tasks, reducing physical risks and mental strain for workers, particularly in hazardous environments. It is possible to optimize workforce scheduling, task allocation, and operational workflows, improving resource management and cutting costs (Bankins et al., 2023). 

How to balance both?  

The increasing integration of AI in the workplace presents both opportunities and challenges. AI has the potential to enhance work by automating ordinary tasks and amplifying employee capabilities, making work more meaningful for some. However, it can also make work less meaningful for others by creating new repetitive tasks, restricting autonomy, and unfairly distributing the benefits of AI away from less-skilled workers (Bankins et al., 2023). However, it has its downsides, like we just explored. 

To balance AI and mental health, organisations need to prioritise human-centered AI design, ensuring that technology supports rather than replaces human capabilities. Transparency and employee involvement in AI implementation are crucial to reduce anxiety and job insecurity, promoting trust within the workforce (Cebulla et al., 2023). Additionally, organisations should address psychosocial risks by offering clear fair job roles and providing mental health support as needed (Giorgi et al., 2022). 

In the absence of regulation regarding AI’s psychosocial impact, businesses must advocate for ethical guidelines and anti-discrimination policies to prevent bias and ensure fairness (Cebulla et al., 2023). Companies should also focus on evidence-based strategies, offering training, flexible work models, and health and well-being programs to create a sustainable, supportive work environment (Giorgi et al., 2022). 

Ultimately, balancing AI and mental health requires ongoing monitoring, feedback loops, and a commitment to creating workplaces where technology and human wellbeing coexist harmoniously. 

References  

Cebulla, A., Szpak, Z., & Knight, G. (2023). Preparing to work with artificial intelligence: assessing WHS when using AI in the workplace. International Journal of Workplace Health Management, 16(4), 294-312.  

Bankins, S., & Formosa, P. (2023). The ethical implications of artificial intelligence (AI) for meaningful work. Journal of Business Ethics, 185(4), 725-740.  

Giorgi, G., Ariza-Montes, A., Mucci, N., & Leal-Rodríguez, A. L. (2022). The dark side and the light side of technology-related stress and stress related to workplace innovations: From artificial intelligence to business transformations. International Journal of Environmental Research and Public Health, 19(3), 1248. 

Jarota, M. (2023). Artificial intelligence in the work process. A reflection on the proposed European Union regulations on artificial intelligence from an occupational health and safety perspective. Computer Law & Security Review, 49, 105825. 

Madsen, I. E., Nyberg, S. T., Hanson, L. M., Ferrie, J. E., Ahola, K., Alfredsson, L., … & IPD-Work Consortium. (2017). Job strain as a risk factor for clinical depression: systematic review and meta-analysis with additional individual participant data. Psychological medicine, 47(8), 1342-1356.