Blackbox or Revolution : Machine Learning Models Shaping the Future of Artificial Intelligence - Bhattacharjee, Sandeep (Indian Journal of Computer Science, 2025)
The disagreement on Artificial Intelligence (AI) relatedness has been a difficult phenomenon, in terms of its rapid emergence and participation into human cognition and decision making. The concept of Artificial Intelligence depicts dualism with respect to its consideration as a remarkable potential and as a disruptor of established standards. The current study investigates the delicate relationship between the argument of AI adoption and its transformational influence towards an improved future vision. The study explores the contrasting views of AIâ€™s capabilities that includes predictive analytics and automation with trepidations that ranges from ethical dilemmas to the anxiety of displacement that creates cognitive and emotional dissonance. This contradiction possibly functions as a catalytic agent that can compel co-evolutionary growth by reinvention of established models by confronting limitations. The essence lies in combining AI's computational efficiency with human creativity, empathy, and intuition to create a more sustainable AI approach. The study demonstrates the application of topic modeling, a deep learning tool for analysis of market sentiments from two databases â€œAI tool of remarkable potentialâ€ and â€œdisruptor of established standardsâ€ for identification of dominant topics, sentimental trend analysis, and similarity scores to test model fitness. Results indicate the presence of higher positive sentiments in the longer run that negates negative positive sentiments in the shorter run. This article redefines the role of AI as a fundamental component of constructing a sustainable, egalitarian, and inspired future for humanity and not just as a mere tool of automation.