My research focus is on the psychology of digitization and modern technologies. The aim is to create excellent psychological research to contribute to addressing societal changes that are driven by advancing digitization and the development of AI-based systems. Thus, AI must not be considered as a pure or optimized replacement for humans but should be understood as a supporting tool for human activities. To realize that people need to be enabled to use AI in a meaningful, productive, and beneficial way.<\/p>\n\n\n\n
In the past two years, I have investigated the acceptance and perceptions of modern technologies (e.g., AI: Hudecek et al., 2024<\/a>; blockchain: Hudecek et al., under review; smartphones: Hudecek et al., 2023a<\/a>) in different contexts (e.g., healthcare: Gaube et al., 2023<\/a>; organizations: Hudecek et al., 2023b, Hudecek & Gr\u00fcnwald, in prep.; finance: Hudecek & B\u00f6hm, in prep.). An important milestone was my successful acquisition of a third-party funded project (project volume: \u20ac\u00a0451,998.60) dealing with autonomous driving in the context of autonomous shuttle buses. The main focus of our research was on the passengers\u2019 acceptance, attitudes, and intention to use (e.g., Schandl et al. 2023a<\/a>, 2023b<\/a>).<\/p>\n\n\n\n The results of my research on the acceptance of AI show that people\u2019s perception is very context-specific. For example, data from a 2×3 scenario-based experiment (N<\/em>=266) show that people prefer the advice of human doctors compared to an AI when it comes to their own situation. In contrast, the participants made no differences between the sources of medical advice when it comes to assessing the situation of an average person (Hudecek et al., 2024<\/a>). <\/p>\n\n\n\n Regarding financial investments, results follow a different pattern (N<\/em>=360): here, people do not care whether they are advised by a human or an AI. Rather, the crucial factor is whether profit (positive assessment of both human and AI adviser, respectively) or loss (negative assessment of both human and AI adviser, respectively) is made (Hudecek et al., in prep.). <\/p>\n\n\n\n Regarding the organizational context, two studies comparing AI-assisted feedback to human feedback (N<\/em>=491; Hudecek & Gr\u00fcnwald, in prep.) and decisions of human recruiters to AI-based recruiters (N=379; Hudecek et al., 2023b<\/a>, S. 2.768) revealed again a more general pattern: positive feedback and hiring decision provided by a human source were significantly better accepted and evaluated as higher in quality compared to the equivalent feedback or hiring decision provided by AI.<\/p>\n\n\n\n These findings underpin that adoption of AI tends to be context-specific and should not be considered simply in terms of algorithm aversion (Dietvorst et al., 2015<\/a>) or algorithm appreciation (Logg et al., 2019)<\/a>.<\/p>\n\n\n\n As part of a research project on the passengers’s acceptance of and attittudes towards autonomous shuttle buses, my team and I were able to conduct several empirical studies. For this purpose, two autonomous shuttle buses were available which could be tested under real conditions in the industrial park in the city of Regensburg, Germany.<\/p>\n\n\n\n Using a latent profile analysis, four user groups were identified on the basis of 16 indicator variables (Schandl et al., 2023a<\/a>). The identified profiles predict the intention to use (ITU) and differ significantly in their characteristics, which suggests that a target group-oriented approach might be beneficial from a practical perspective.<\/p>\n\n\n\nDigitization and artificial intelligence<\/h6>\n\n\n\n
Mobility<\/h6>\n\n\n\n