Challenges and Apprehensions in Adopting Artificial Intelligence
Author : K Rajyalaxmi
Abstract :
The integration of Artificial Intelligence (AI) into physics research and applications has opened new avenues for data analysis, simulation, and theoretical modeling. However, the adoption of AI in the physics community is accompanied by several challenges and apprehensions. This study investigates the key obstacles faced by physicists in embracing AI-driven methodologies, including concerns over data reliability, model interpretability, computational resource demands, and the potential erosion of traditional analytical skills. Ethical issues related to transparency, bias in algorithmic predictions, and the reproducibility of AI-assisted results are also explored. Through an extensive literature review and expert perspectives from different physics subfields, the research identifies gaps in technical expertise, infrastructure readiness, and interdisciplinary collaboration as critical barriers. The findings suggest that fostering AI literacy among physicists, ensuring explainable models, and promoting open-source frameworks can significantly alleviate these concerns. Ultimately, this study emphasizes the need for a balanced approach that integrates AI as a complementary tool—enhancing, rather than replacing, the scientific intuition and rigor that define the discipline of physics.
Keywords :
Artificial Intelligence, Algorithmic Predictions, Reproducibility, Transparency, Model Interpretability.
