The Effect of Artificial Intelligence on Research Methodology By Dr. Taiyaba Nazli


The field of Artificial Intelligence (AI) has made remarkable paces in the recent years, revolutionizing various industries and domains. In the realm of social sciences, AI has gained increasing prominence as a tool for data analysis, information extraction, and even hypothesis generation. Though AI has emerged as a transformative force in the realm of research methodology, reshaping the way researchers collect, analyze, and interpret data. This paper explores the multifaceted effects of AI on research methodology, emphasizing its potential to enhance the efficiency, accuracy, and depth of research across various disciplines. There are many issues which remains to be resolved, such as doubts about algorithmic bias, data privacy, and ethical issues with the AI-driven research. To guarantee that AI enhances research technique, researchers need to be on the lookout for these problems and take proactive measures to resolve them.

Artificial Intelligence has significantly changed research methods by providing new opportunities for data gathering, processing, and sharing. Researchers need to adjust and take advantage of these technological developments as AI develops further in order to improve the quality and significance of their work. This paper emphasizes the necessity of continuing debates and moral standards in order to fully utilize artificial intelligence in research while minimizing the possible risks.

This paper also probes into the question of whether AI can completely replace human-driven research in the social sciences. While AI presents several advantages in terms of efficiency and data processing, it is argued here that it cannot fully replace human research due to the nuanced and context-dependent nature of social sciences.

Keywords: artificial intelligence, data processing, social sciences, research methodology 

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