Generation Z's Trust Toward Artificial Intelligence:Attitudes and Opinions

Anna Dewalska-Opitek, Olgierd Witczak, Agnieszka Szostak, Marek Dziura and Bozena Wroniszewska-Drabek

European Research Studies Journal, 2024, vol. XXVII, issue Special B, 33-52

Abstract: Purpose: The article explores the attitudes and opinions of Generation Z (born 1995-2009) toward artificial intelligence (AI), emphasising their unique relationship with technology. Design/Methodology/Approach: The nature of the research was exploratory; three focus groups were organized, including a total of 34 participants, with each group containing between 8 and 12 individuals. The sample included both Gen Z’s males and females from various nationalities. They were either university students (Erasmus or first cycle program) or high school students (International Baccalaureate Program). Findings: The study uncovers familiarity with AI, sentiment variations, perceived benefits, and concerns Gen Z representatives. Results highlight positive sentiments about AI's potential and apprehensions about privacy and ethical challenges. Practical Implications: The results shed light on the components of Gen Z consumers' attitudes toward AI, revealing its dimensions and challenges. By addressing the perceived drawbacks and key trust issues identified by the participants, companies can better connect with this increasingly influential generation, which is drawing significant attention from researchers and practitioners and is set to become a dominant force in the future. Originality/Value: AI is quickly becoming a crucial field of scientific study, with its importance set to increase significantly in the coming years. As technological progress speeds up, AI's potential applications are expanding across various sectors. Additionally, as AI systems are more deeply integrated into daily life, thorough research is urgently needed to tackle key challenges like ethics, transparency, and bias.

Keywords: Trust; artificial intelligence; Generation Z. (search for similar items in EconPapers)
JEL-codes: J11 O33 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ersj.eu/journal/3475/download (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ers:journl:v:xxvii:y:2024:i:specialb:p:33-52

Access Statistics for this article

More articles in European Research Studies Journal from European Research Studies Journal
Bibliographic data for series maintained by Marios Agiomavritis ().