Artificial Intelligence (AI) has rapidly evolved from a specialized computational tool into an integral part of social, economic, and intellectual life. As Al systems increasingly demonstrate capabilities such as learning, problem-solving, and decision-making, questions regarding their relationship with human intelligence have become more significant. This study examines how artificial intelligence and human intelligence are conceptualized, evaluated, and compared, particularly in contexts where task-based performance metrics are treated as substitutes for intelligence, leading to conceptual ambiguity. A cross-sectional survey was conducted for this research, involving postgraduate students and early-career professionals with prior exposure to Al applications. The survey assessed perceptions of Al and human intelligence across multiple dimensions, including analytical ability, adaptability, creativity, contextual understanding, ethical judgment, trust, and decision-making. Descriptive statistical analysis was used to identify response patterns, while qualitative responses provided contextual depth to the quantitative trends. The findings indicate that respondents generally perceive Al as superior in data analysis, memory capacity, and repetitive task execution. In contrast, human intelligence was perceived as stronger in emotional understanding, ethical reasoning, creativity, and adaptability in novel situations. Trust in Al for high-stakes decision-making remained at a moderate to low level, reflecting cautious acceptance rather than full reliance. Overall, the results support a complementary rather than competitive relationship between artificial and human intelligence. This study contributes to ongoing debates by emphasizing the need for multidimensional and conceptually grounded frameworks when comparing intelligence across human and artificial systems.
Zeenat Ansari (Wed,) studied this question.