Leveraging AI-Driven ChatGPT for Automated Data Preprocessing in Data Science

In the rapidly evolving landscape of data science, the integration of AI-driven solutions has garnered increasing attention, particularly in the domain of data preprocessing. This study embarked on a comprehensive exploration of the potential, challenges, and implications inherent in incorporating AI-driven preprocessing solutions. Through a meticulous mixed-methods research design encompassing surveys, this study addressed three distinct research objectives. The findings reflect the intricate interplay of perspectives within the data science community. The comparative performance evaluation revealed a diverse range of opinions regarding the efficiency and accuracy of AIdriven preprocessing solutions. The ethical framework development highlighted the recognition of the significance of ethical considerations in AI-driven data preprocessing and its potential to enhance accountability and fairness. This study contributes a nuanced understanding of AI-driven ChatGPT for automated data preprocessing, encompassing technical, ethical, and practical dimensions. The elaborate analysis provides insights that guide responsible AI adoption and informed decision-making in data science workflows. As AI technologies continue to shape the landscape, these findings stand as a compass, guiding practitioners, researchers, and organisations toward a harmonious fusion of human expertise and AI capabilities in the realm of data preprocessing.