Browsing by Author "Kalashnyk, Yevhenii"
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- Comparing Generational Differences in Perceptions of AI-Mediated Communication in the Workplace
School of Business | Bachelor's thesis(2023) Kalashnyk, YevheniiObjectives This study investigates the impact of beliefs about email generation on perceived trustworthiness and examines potential moderating effects of AI attitude, propensity to trust, and generational cohort. The research objectives included exploring the current state of AI-mediated communication in the workplace, empirically examining how the belief that AI is involved in writing emails affects sender trustworthiness and comparing generational differences in perceived trustworthiness of AI-generated emails. Summary Results indicated that belief about email generation significantly affected perceived trustworthiness, with participants rating emails believed to be written by AI as less trustworthy than those believed to be written by human. However, contrary to expectations, AI attitude and propensity to trust did not significantly moderate this relationship. Additionally, generational cohort did not significantly predict perceived trustworthiness. Conclusions The study highlights the impact of belief about email generation on trustworthiness and the limited role of AI attitude, propensity to trust, and generational cohort in AI-mediated communication. As the use of AI in communication increases, understandin trust perception factors is crucial for fostering AI technology acceptance and adoption.