EXPLORING INTERRELATIONSHIPS AMONG FACTORS INFLUENCING CONSUMER TRUST IN AI-DRIVEN VEHICLES: A CORRELATION ANALYSIS - Mali, Rahul Mohan; Shinde, Santosh; Waghulkar, Shrikant (ShodhKosh: Journal of Visual and Performing Arts, 2024)
The rapid advancement of artificial intelligence (AI) in the automotive industry has introduced AI-driven vehicles that promise enhanced safety, efficiency, and decision-making capabilities. However, consumer trust remains a critical factor influencing the adoption and acceptance of these technologies. This study investigates the relationship between perceived safety, AI decision-making capabilities, and consumer trust in AI-driven vehicles. A quantitative research approach was employed, with data collected from 389 respondents using a structured questionnaire based on a five-point Likert scale. Correlation analysis was conducted to assess the strength and significance of relationships between key variables, with hypotheses tested at a 95% confidence level. The findings reveal a strong positive correlation between perceived AI safety features and consumer trust, highlighting the importance of AI's ability to interpret traffic rules, adapt to unpredictable scenarios, and enhance road safety. The study provides practical implications for automobile manufacturers, policymakers, and AI developers by emphasizing the need for transparent AI decision-making, enhanced safety measures, and user education to foster greater consumer trust. While offering significant insights, the study acknowledges limitations such as sample bias, reliance on self-reported data, and the evolving nature of AI technology. Future research should explore trust dynamics across diverse cultural and regulatory landscapes and incorporate longitudinal studies to track shifts in consumer attitudes over time.