The AI vantage: an exposition of global dynamics

Rohan Kishor, Bhumeshwar K. Patle, P. Bhojane
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Abstract

Over the past few years, there has been a growing interest in this field of Artificial Intelligence (AI). This review paper aims to examine the extent to which AI has been adopted across various domains in different regions of the world. Specifically, this study seeks to explore the effectiveness of AI in areas such as banking, governance, judiciary, and agriculture. While AI’s impact on these areas has been studied before, this research focuses on aspects that have not been given much needed attention so far. The study will begin by offering an overview of AI’s development from a regional perspective, analyzing 63 articles from leading journals and institutions to identify the most commonly used terminologies, theories, and technologies. The increasing computational power has played a crucial role in the advancement of AI. However, the role of AI in governance, judiciary, and legislature system has not been explored in depth in previous research. Furthermore, most studies tend to focus on single domain, whereas this paper aims to examine several domains and their relationship to AI. The study presents several AI-driven techniques, including Deep Neural Net (DNN), Artificial Neural Net (ANN), Candlestick Plots, Natural Language Processing (NLP), Explainable Deep Neural Net (xDNN), Attentional Maps, Digital Inventory, Deep Learning among others, that can be applied to enhance society’s performance in different domains. The research also delves deeper into the judiciary domain, proposing specific AI techniques that could be useful in this field. Additionally, tables summarizing different AI tactics relevant to each domain are presented.
AI优势:对全球动态的阐述
在过去的几年里,人们对人工智能(AI)这一领域的兴趣越来越大。这篇综述论文旨在研究人工智能在世界不同地区的各个领域被采用的程度。具体而言,本研究旨在探索人工智能在银行、治理、司法和农业等领域的有效性。虽然之前已经研究过人工智能对这些领域的影响,但这项研究的重点是迄今为止尚未得到太多关注的方面。该研究将首先从区域角度概述人工智能的发展,分析来自领先期刊和机构的63篇文章,以确定最常用的术语、理论和技术。不断增强的计算能力在人工智能的发展中发挥了至关重要的作用。然而,以往的研究并未深入探讨人工智能在治理、司法和立法体系中的作用。此外,大多数研究都集中在单个领域,而本文旨在研究多个领域及其与人工智能的关系。该研究提出了几种人工智能驱动的技术,包括深度神经网络(DNN)、人工神经网络(ANN)、烛台图、自然语言处理(NLP)、可解释深度神经网络(xDNN)、注意力地图、数字库存、深度学习等,可用于提高社会在不同领域的表现。该研究还深入研究了司法领域,提出了可能在该领域有用的具体人工智能技术。此外,还提供了与每个领域相关的不同人工智能策略的总结表。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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