Psychological reactions to the introduction of Artificial Intelligence (AI) in the professional context
In this section, we’ll examine the various psychological reactions to the use of AI, including anger, distress, pain, loss of control, and frustration, as well as feelings of flexibility, uncertainty, creativity, wonder, and solidarity. We will also examine the opportunities and challenges that artificial intelligence presents in the workplace context. In addition, we will analyse the concept of work and how these psychological reactions affect both employers and workers. Ultimately, we aim to make the emotional and psychological impact of using AI in the workplace more visible, thereby integrating these elements to foster a deeper understanding of its influence.
The psychological reactions of individuals are unique to each. Still, their causes can be traced back to three different modes of thinking: firstly, subjectivity, which is the mode of thinking by which the individual constructs their knowledge from their own experience; secondly, rationality, which refers to the process of creating knowledge based on logic and reasoning; and finally, belief, which is characterized by the individual’s mode of thinking, constructing knowledge from revealed elements and which does not need to be strictly logical (Altomare, 2005).
Advances in artificial intelligence give rise to a variety of psychological reactions in the workplace. Employees may experience emotions such as anger, distress, and pain due to the fear of AI replacing their jobs or even the role of their superiors (Actupool, 2024). Moreover, employees’ fear is intensified by the feeling of constant surveillance and the possible mistakes that AI could make.
Advances in artificial intelligence give rise to a variety of psychological reactions in the workplace. Employees may feel emotions such as anger, distress and pain, due to the fear of AI replacing their jobs, or even the role of their superiors (Actupool, 2024). Moreover, employees’ fear is intensified by the feeling of constant surveillance and the possible mistakes that AI could make.
On the other hand, employers face their own set of concerns. According to Garcia (2024), the strategic optimization cycle, a process designed to improve decision-making, increase efficiency, and reduce costs, involves a paradigm shift in thinking. As a result, employers fear making the wrong strategic decisions and losing control of these processes.
At a societal level, concerns exist about employee acceptance of the profound changes occurring in the job market. These concerns are amplified by alarming media messages, which increase uncertainty and resistance to change.
Automation and Artificial Intelligence are transforming the workforce by replacing repetitive tasks in many industries, which can lead to job losses, as Dávila & Agüero point out in 2023. To mitigate this impact, it is essential to offer training programs that prepare workers to adapt to new roles. If automation is not managed correctly, there is a risk of losing human control over the key decisions that affect people’s lives. This underlines the importance of responsible oversight of AI use to ensure that decision-making remains under human control.
A more subtle form of loss of control is associated with the concept of the “black box”, which refers to a characteristic inherent in many Artificial Intelligence systems. This characteristic makes it difficult to understand how decision-making processes are conducted thoroughly, and it also implies that these systems may face limitations in predicting both their decisions and outcomes (Bathaee, 2018).
In the analysis carried out by Todolí (2019), it is highlighted how the implementation of algorithms in work management can generate frustration among workers due to the loss of autonomy and control over their tasks, the lack of empathy and context in automated decisions, constant monitoring via sensors, and errors in system operation.
In the same vein, the author notes that the decision-making criteria of algorithms, as well as the perception of dehumanization and the risk of discrimination, significantly increase employee anxiety and dissatisfaction, underscoring the need to program these systems to ensure respect for human capabilities and mental health (Todolí, 2019).
The flexibility of AI systems is reflected in chatbots, which possess remarkable versatility, enabling them to be applied in a variety of fields. Their flexible design and ability to adapt to each user’s pace guarantee a comfortable experience, avoiding exhaustion. This translates into interaction free of cognitive overload for those who use them, as indicated in the paper presented at the 14th International Scientific Conference on eLearning and Software for Education, held in Bucharest in April 2018 (Goldbach et al., 2018).
Flexibility is a key element of any AI system. Although significant progress has been made in implementing AI for specific, isolated tasks, the main challenge in developing AI-based robotics technology lies in the effective integration of subsystems within an environment (Duckett & Pearson, 2018).
Cardenas’ (2023) article examines the uncertainty that AI is causing in academia due to several factors. AI, while capable of generating content and analyzing data, lacks the human context, empathy, and sensory experience that are essential for understanding social and cultural interactions. In addition, tools such as ChatGPT are transforming traditional dynamics, calling into question the value of skills such as writing and peer review. It is also noted that Generative AI can produce erroneous information and fail to ensure the quality of sources, thereby raising mistrust.
In research on Generative Artificial Intelligence (GAI), such as ChatGPT-3, it is established that it has an impact on the creativity of university students, as reported by (Valencia et al., 2024), who conclude that collaboration between humans and AI can enhance creativity, improving skills such as originality, flexibility, and divergent thinking. However, ethical challenges are highlighted, such as the risk of over-reliance, algorithmic biases, and the preservation of authenticity in creative processes. The emphasis is on the fact that AI should be a complementary tool for fostering human creativity, rather than replacing it.
Skills such as creativity and usefulness are reinforced by the data voluntarily provided by users, thus avoiding the dubious practices of large corporations. However, despite its reward system designed to generate responses, AI can provide incorrect information or fail to respond when it tries to anticipate user intentions through contextual analysis. Nevertheless, it can generate innovative content by combining concepts, which makes it akin to a creative process capable of exploring original ideas and offering unique perspectives (Tijerina2024).
Although Artificial Intelligence systems cannot experience human emotions, their programming enables them to respond to emotions expressed in a text through what is known as “algorithmic sympathy”, as mentioned by Tijerina in 2024. According to this author, Artificial Intelligence can interpret and recognize words associated with different emotions, adjusting its responses in an empathetic manner to offer support tailored to each situation.
In the field of psychological research, cognitive functions are primarily explored; however, a significant question remains: can machines learn, perceive, plan, reason, make decisions, solve problems, and process language in a natural way, just as the human brain does? (Coeckelbergh, 2020).
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