From computing science to intelligent computing: A review of artificial and computational intelligence in data and information analysis

Abstract

Artificial intelligence put forward using human intelligence index by use of advanced algorithms and models that transform computational principles of AI. Deep learning is a category of Artificial intelligence that shows the best problem-solving techniques and ways across different domains. Also, Computational Intelligence (CI) enhances conventional computing strategies through processes such as fuzzy logic, evolutionary algorithms, and neural networks that enables smarter decision-making among vague variables. Intelligent computing's impact is expanded over technological domains, that shows transformative changes in healthcare systems, finance industry, and other industrial processes. Having access to these technologies through collective platforms and open-source initiatives look after innovation. This review shatter perspectives from research scholars, industrial persons, and research communities, highlighting the current landscape and future prospects of A.I. and computational intelligence. Interdisciplinary applications and cross-cutting research initiatives represent the transformative potential of integrating intelligent computing techniques into expanded strategies. This wide scattering of A.I. and computational intelligence gives rise to the ethical concerns that majorly includes algorithmic biases and privacy issues to the end user. Meaningful dialogues and ethical practices are imperative to harnessing A.I. for social good in our interconnected world. This article represents the interdependent relationship between A.I., computational intelligence, and data science, offering deep knowledges into their synergistic applications and societal implications. It highlights the need for responsible A.I. deployment and ethical considerations to ensure the beneficial use of intelligent computing technologies.