Leveraging the potential of artificial intelligence (AI) in exploring the interplay among tax revenue, institutional quality, and economic growth in the G-7 countries

IF 4.7 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE AI & Society Pub Date : 2024-03-10 DOI:10.1007/s00146-024-01885-4

Charles Shaaba Saba, Nara Monkam

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Abstract

Due to G-7 countries' commitment to sustaining United Nations Sustainable Development Goal 8, which focuses on sustainable economic growth, there is a need to investigate the impact of tax revenue and institutional quality on economic growth, considering the role of artificial intelligence (AI) in the G-7 countries from 2012 to 2022. Cross-Sectional Augmented Autoregressive Distributed Lag (CS-ARDL) technique is used to analyze the data. The study's findings indicate a long-run equilibrium relationship among the variables under examination. The causality results can be categorized as bidirectional, unidirectional, or indicating no causality. Based on the CS-ARDL results, the study recommends that G-7 governments and policymakers prioritize and strengthen the integration of AI into their institutions to stimulate growth in both the short- and long-term. However, the study cautions against overlooking the interaction between AI and tax revenue, as it did not demonstrate support for economic growth. While the interaction between AI and institutional quality shows potential for contributing to growth, it is crucial to implement robust measures to mitigate any potential negative effects that may arise from AI's interaction with tax systems. Therefore, the study suggests the development of AI-friendly tax policies within the G-7 countries, considering the nascent nature of the AI sector/industry.

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利用人工智能 (AI) 的潜力探索七国集团国家税收、机构质量和经济增长之间的相互作用

由于七国集团国家致力于维持以可持续经济增长为重点的联合国可持续发展目标8，因此有必要考虑到人工智能（AI）在2012年至2022年七国集团国家中的作用，研究税收和制度质量对经济增长的影响。采用截面增强自回归分布滞后（CS-ARDL）技术对数据进行分析。研究结果表明，所考察的变量之间存在长期均衡关系。因果关系结果可分为双向、单向或无因果关系。根据CS-ARDL的结果，该研究建议七国集团政府和政策制定者优先考虑并加强人工智能与其机构的整合，以刺激短期和长期的增长。然而，该研究警告说，不要忽视人工智能与税收之间的相互作用，因为它并没有显示出对经济增长的支持。虽然人工智能与制度质量之间的相互作用显示出促进增长的潜力，但实施强有力的措施以减轻人工智能与税收制度相互作用可能产生的任何潜在负面影响至关重要。因此，该研究建议在考虑到人工智能部门/产业的新生性质的情况下，在七国集团国家内制定有利于人工智能的税收政策。

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来源期刊

AI & Society COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

8.00

自引率

20.00%

发文量

257

期刊介绍： AI & Society: Knowledge, Culture and Communication, is an International Journal publishing refereed scholarly articles, position papers, debates, short communications, and reviews of books and other publications. Established in 1987, the Journal focuses on societal issues including the design, use, management, and policy of information, communications and new media technologies, with a particular emphasis on cultural, social, cognitive, economic, ethical, and philosophical implications. AI & Society has a broad scope and is strongly interdisciplinary. We welcome contributions and participation from researchers and practitioners in a variety of fields including information technologies, humanities, social sciences, arts and sciences. This includes broader societal and cultural impacts, for example on governance, security, sustainability, identity, inclusion, working life, corporate and community welfare, and well-being of people. Co-authored articles from diverse disciplines are encouraged. AI & Society seeks to promote an understanding of the potential, transformative impacts and critical consequences of pervasive technology for societies. Technological innovations, including new sciences such as biotech, nanotech and neuroscience, offer a great potential for societies, but also pose existential risk. Rooted in the human-centred tradition of science and technology, the Journal acts as a catalyst, promoter and facilitator of engagement with diversity of voices and over-the-horizon issues of arts, science, technology and society. AI & Society expects that, in keeping with the ethos of the journal, submissions should provide a substantial and explicit argument on the societal dimension of research, particularly the benefits, impacts and implications for society. This may include factors such as trust, biases, privacy, reliability, responsibility, and competence of AI systems. Such arguments should be validated by critical comment on current research in this area. Curmudgeon Corner will retain its opinionated ethos. The journal is in three parts: a) full length scholarly articles; b) strategic ideas, critical reviews and reflections; c) Student Forum is for emerging researchers and new voices to communicate their ongoing research to the wider academic community, mentored by the Journal Advisory Board; Book Reviews and News; Curmudgeon Corner for the opinionated. Papers in the Original Section may include original papers, which are underpinned by theoretical, methodological, conceptual or philosophical foundations. The Open Forum Section may include strategic ideas, critical reviews and potential implications for society of current research. Network Research Section papers make substantial contributions to theoretical and methodological foundations within societal domains. These will be multi-authored papers that include a summary of the contribution of each author to the paper. Original, Open Forum and Network papers are peer reviewed. The Student Forum Section may include theoretical, methodological, and application orientations of ongoing research including case studies, as well as, contextual action research experiences. Papers in this section are normally single-authored and are also formally reviewed. Curmudgeon Corner is a short opinionated column on trends in technology, arts, science and society, commenting emphatically on issues of concern to the research community and wider society. Normal word length: Original and Network Articles 10k, Open Forum 8k, Student Forum 6k, Curmudgeon 1k. The exception to the co-author limit of Original and Open Forum (4), Network (10), Student (3) and Curmudgeon (2) articles will be considered for their special contributions. Please do not send your submissions by email but use the "Submit manuscript" button. NOTE TO AUTHORS: The Journal expects its authors to include, in their submissions: a) An acknowledgement of the pre-accept/pre-publication versions of their manuscripts on non-commercial and academic sites. b) Images: obtain permissions from the copyright holder/original sources. c) Formal permission from their ethics committees when conducting studies with people.

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