What Predicts AI Usage? Investigating the Main Drivers of AI Use Intention over Different Contexts
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Abstract
Artificial Intelligence (AI) based applications are an ever-expanding field, with an increasing number of sectors deploying this technology. While previous research often focused on understanding AI usage in one domain, we aimed to investigate the main drivers of AI usage over a broad range of contexts. To this end, we conducted two studies (N = 450, representative for age and gender; N = 259, balanced for age and gender) covering a wide range of contexts (e.g., medical, autonomous driving, art), assessing well-established variables in AI research (trust, familiarity, attitudes) as well as AI aversion, knowledge about AI, and risk-opportunity perception. We further investigated the influence of AI use-related ratings (i.e. context-specific opinions of AI) on AI usage. Generally, higher trust in AI, more positive use-related ratings, and lower risk perception significantly predict general AI usage intention. Additionally, both studies revealed that willingness to use AI varied significantly depending on the context. These findings highlight the relevance of trust, risk-opportunity perception, and use-related ratings in understanding laypeople’s general intention to use AI-based applications while at the same time emphasizing the importance of taking context into account.
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