What Predicts AI Usage? Investigating the Main Drivers of AI Use Intention over Different Contexts

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Artificial Intelligence (AI) based applications are an ever-expanding field, with an increasing number of sectors deploying this technology. While previous research has focused on trust in AI applications or familiarity as predictors for AI usage, we aim to expand current research by investigating the influence of knowledge as well as AI risk and opportunity perception as possible predictors for AI usage. To this end, we conducted a study (N= 450, representative for age and gender) covering a broad number of domains (health, eldercare, driving, data processing, and art), assessing well-established variables in AI research (trust, familiarity) as well as knowledge about AI and risk and opportunity assessment. We further investigated the influence of AI use related ratings on AI usage. Results show that the newly investigated variables best predict overall intention to use, above and beyond trust and familiarity. Higher AI-related knowledge, more positive use related ratings, and lower risk perception significantly predict general AI use intention, with a similar trend emerging for domain-specific AI use intention. These findings highlight the relevance of knowledge, risk and opportunity assessment, and use related ratings, in understanding laypeople’s intention to use AI-based applications and open a new roster of research questions in understanding people’s AI use behavior intentions and their perception of AI.

Ryan Watkins