Psychological Mechanisms Influencing Preferences for AI-Based and Human Counselling in India

Abstract

This research explores the psychological reasons behind people's preference for AI (artificial intelligence) over human-based counseling in India, focusing on five major areas including stigma, emotional safety, relational trust, accessibility, and privacy concerns. Although AI usage is beginning to be integrated into mental health care, research has not adequately studied the psychological influences affecting individuals' overall attitudes toward these two modalities, especially since mental health care infrastructures in much of the world are deficient. The researchers conducted a cross-sectional survey of 56 adults currently residing in India who responded to a series of structured questionnaires that consisted of demographic items, multiple-choice questions, and a 5-point Likert scale measuring response level. Data analyses using non-parametric statistics were conducted using the Mann-Whitney U test, Kruskal-Wallis test, Spearman correlation coefficients, and Chi-Square tests. Results indicate that those with interpersonal anxiety and those fearing judgment found AI effective in addressing emotional safety concerns associated with counseling. Additionally, privacy concerns significantly reduce trust in AI, and participants indicated that privacy concerns caused them to have even greater concerns regarding misuse of their data. Participants also feel that human counselors perform better than AI when dealing with emotionally complex cases because humans can read non-verbal communications. Participants indicated that both accessibility and affordability were major benefits of AI counseling. Finally, participants view AI and human-based counseling as competing systems, not complementary systems. These findings suggest that emotional safety, stigma, and privacy perceptions are central determinants of counselling preferences in India. Developers and policymakers should prioritise transparency, ethical data practices, and human-centred design to improve public acceptance of AI-assisted mental healthcare.