Artificial Intelligence in Information Science , Approaches and Effects

Abstract

The recent advances in artificial intelligence (i.e., AI) in information science have resulted in unparalleled growth in businesses. This development came from the adoption of smart machines, which integrate mathematics, psychology, computer science, linguistics, and various other features in decision-making. Therefore, this research conducted a comprehensive review of available literature and explored the various approaches to AI and the overall ramifications of such technology. A wide range of literature produced from the 1950s to the present is examined to determine the trends and effects of AI. From the findings, it is determined that different approaches facilitate a machine's ability to rely on previous experiences when making decisions rooted in memory and self-awareness. Examined methods include machine learning, natural language processing, robotic process automation, and computer vision. This research also highlighted both positive and negative implications, which indicate that this is possibly a contentious technology. It concluded that businesses should engage in extensive research to ensure the pros of such technologies outweigh the risks.

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