Unified Intelligence: A Comprehensive Review of the Synergy Between Data Science, Artificial Intelligence, and Machine Learning in the Age of Big Data

Abstract

The intensifying relationship between Data Science and Artificial Intelligence (AI) and Machine Learning (ML) may now be collectively referred to as unified intelligence. This analysis aims to understand the relationship between these three fields during the period of big data by identifying the relationship, enabling technologies, and their impact on the society. Let us start with the definition of each field, capturing their developmental story and defining their key ideas. Then, we focus on big data defined by volume, velocity, and variety as a critical factor dynamically catalyzing the integration of AI and ML to the current data science workflows. The paper emphasizes the data-related ones, especially the infrastructure, storage technologies, and information systems with their associated practical problems on massive scale data processing. Another primary focus of the paper is the applied interdisciplinary, cross-domain collaboration enabling the intelligent, automated systems, data pipelines, and intelligent systems with the support of cloud computing, AutoML, and large scale machine learning system architectures. Examples from health care, finance, and smart or intelligent industry demonstrated the powerful possibilities from unified intelligence. The review highlights important social and policy-related questions of ethics, fairness, and privacy, and the need to have AI systems which are understandable to the user. The review also presents critical issues such as the need for improved data quality and other issues.

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