On 2024-02-22, at the 27th conference of the Gesellschaft für angewandte Wirtschaftspsychologie in Cologne, I had the honor of a speech. I spoke about the results of two vignette-experiments that were conducted by two of my Masters students, Verena Kalwa, and Darian Gorba, to investigate determinants of acceptance of AI-based interaction systems in organizations. Below I provide a short summary from this speech.
Introduction
As Artificial Intelligence (AI) becomes increasingly integrated into workplaces, understanding what influences its acceptance is essential. This study explores the determinants of acceptance for AI-based interaction systems, focusing on implementation strategies in organizations and AI’s role in personnel selection processes.
Key Findings
- Implementation Strategies of AI:
- Study Design: The first experiment involved 196 participants and examined different AI implementation strategies.
- Theories Applied: Insights were drawn from Self-Categorization Theory and the Stereotype Content Model.
- Results: Participative and transparent implementation strategies were found to significantly enhance acceptance indicators such as warmth, competence, affective attitudes, and perceived human similarity compared to top-down strategies.
- AI in Personnel Selection:
- Study Design: The second experiment included 288 participants and explored applicants’ perceptions of AI’s involvement in personnel selection.
- Key Factors: The study focused on intention to use AI, influenced by human similarity, social presence, and elements from the Unified Theory of Acceptance and Use of Technology (UTAUT).
- Results: Higher involvement of AI in the selection process correlated with lower acceptance levels.
Implications for Organizations
- Implementation Strategy: Organizations should consider participative and transparent strategies when integrating AI systems to enhance user acceptance.
- AI Involvement: Careful consideration is required regarding the level of AI involvement in processes like personnel selection to maintain or increase acceptance levels.
Conclusion
The research highlights the complexity of AI acceptance, emphasizing that both the implementation method and the degree of AI involvement significantly impact user acceptance. These findings are crucial for organizations aiming to integrate AI systems effectively.
Download the abstract.