Artificial intelligence in a leadership context – acceptance of the use of robots in leadership positions

The development of artificial intelligence (AI) is changing the working environment. For example, artificial intelligence systems are increasingly applied in the field of employee leadership. Hereby AI can take over routine tasks or provide data-based decision support in employee-related processes. Advancements in robotics, coupled with AI technologies, also enable the construction of social robots. These kinds of robots can interact with their environment and thus theoretically offer the possibility of taking over leadership tasks completely. The successful use of social robots depends on employees’ acceptance of robot supervisors. Therefore, Lilly Mühlbauer, a student of our business psychology program, has conducted a quantitative online survey to gain insights into the acceptance of robots in leadership positions, as part of her bachelors’ thesis. In this context, the influence of the leadership entity (human vs. robot) as well as the impact of the leadership style (transactional vs. transformational) was examined.

Research Overview

The data collection was conducted in November 2023 through a quantitative online experiment using the platform Unipark. Participants were asked to imagine applying for a new job. Therefore, only individuals for whom this scenario realistically reflected their life stage were included. Accordingly, students and retirees were excluded by a filter question at the beginning of the survey.
Participants were initially assigned to the following four groups: G1 (human x transactional leadership style), G2 (human x transformational leadership style), G3 (robot x transactional leadership style), G4 (robot x transformational leadership style).
The central element of the questionnaire was a fictional scenario. For this purpose, images depicting the manager in conversation with an employee were generated in Midjourney. Except for the manager, the pictures were created identically, with no variations in body posture for the different leadership styles. To operationalize the two leadership styles, an excerpt of the conversation between the manager and the employee was presented, consisting of a short monologue by the manager.
The analysis included a total number of 162 participants, with an average age of 23 years.

Main findings of the survey

    • Results indicated a significant difference in the acceptance between the two leadership entities (human vs. robot). The human manager received significantly higher acceptance ratings compared to the robot manager.
    • Results indicated a significant difference in the acceptance between the two leadership styles (transactional vs. transformational). The transformational leadership style led to a greater acceptance of managers.
    • The acceptance of the human manager and the robot manager is not dependent on the presented leadership style.
    • No significant correlation was found between prior knowledge about AI programs or AI-assisted robots and the acceptance of a robot manager. It should be noted that this analysis was based solely on the participants’ self-assessment of their own knowledge.
    • A positive correlation between the experience with AI programs or AI-assisted robots and the acceptance of a robot manager was found. It’s important to consider this result with the caveat that the responses are based on consciously perceived experiences of the participants, and individuals may encounter AI programs in their daily lives more frequently than they are actually aware of.
    • Additionally, results indicated that leadership entity and leadership style not only influence acceptance but also impact the organizational attractiveness of a company.

Conclusion

Overall, the data suggest that a human manager is significantly more accepted compared to a robot manager. Therefore, it can be stated, that employees currently demonstrate no clear willingness to work under the leadership of a robot. In addition, the expected difference in the acceptance rating in relation to the leadership style presented could be measured. Thus, the transformational leadership style scored higher than the transactional leadership style, consequently leading to greater acceptance of the manager. No interaction between the two factors, leadership entity and leadership style, could be observed. This implies that they independently influence the acceptance evaluation. As a result of high practical relevance, it can be stated that the robot manager achieved significantly lower values regarding organizational attractiveness compared to the human manager.
Accordingly, the deployment of a robot leader appears to have a negative impact on the organizational attractiveness of a company. This study contributes to the research field of human-robot interaction and provides statistically significant findings on the acceptance of robots in management positions.

What makes the implementation of collaboration tools successful? – A case study on employees’ acceptance when introducing MS Teams

Since the 1980s, Computer Supported Cooperative Work (CSCW) technologies have been developed and increasingly utilized to ensure digital collaboration of employees within and between organizations. The need for ways to work remotely and time-independently across various countries requires the implementation of digital collaboration tools now more than ever. Besides, the global Corona pandemic required a quick and efficient response of companies worldwide which served as a ”digitalization booster” regarding digital and remote working. Yet, the employees’ missing acceptance and corresponding resistance towards using these tools represents a substantial obstacle for organizations. Hence, employers need to consider which implementation measures are effective in securing acceptance and successful adaptation of novel technologies.

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