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The Limits of Global Inclusion in AI (Artificial Intelligence) Development

This article is devoted to the theme of the development and implementation of elements of artificial intelligence (AI) in the context of various countries. While this technology can significantly simplify many people’s lives, according to the authors, those with the greatest economic power will benefit most from it (Chen et al., 2021). Thus, improving the life of society with the help of this technology is complicated by the presence of global inequality, which Western institutions are actively trying to eliminate.

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However, the measures taken often consist only in forming more multinational groups, which makes it possible to tackle the problem of inclusion only in the context of direct research. Since the overwhelming majority of experimentation is still focused on the West, especially in America, unfair distribution of resources will hinder the future implementation of this technology. As the main existing barriers, the authors highlight the need for data collection, which requires high-quality technology and a reliable Internet connection and is much more expensive in the southern hemisphere (Chen et al., 2021). The second limitation is insufficient research laboratories, which cannot be created due to the attendant risks and unstable political and economic situations. However, these problems can be addressed by developing existing opportunities in three directions: the creation of affinity groups, the inclusion of residents in research, and programs to reduce the development gap (Chen et al., 2021). Without the introduction of such applications, the development of AI will remain non-inclusive.

This article was written by four authors, each of whom is from a different university. Each of them is a Ph.D. student whose research area includes various technical disciplines, including artificial intelligence. However, at the moment, they do not have enough background to assess their authority fully. Accordingly, it is advisable to approach the existing text with caution. Its content is intended for a broad audience and provides an overview and theoretical analysis of possible ways to resolve AI development inequalities. The text contains a small number of specific terms, making it easier for people from the topic under study to understand the material.

Reference

Chan, A., Okolo, C. T., Terner, Z., & Wang, A. (2021). The limits of global inclusion in AI development. arXiv preprint arXiv:2102.01265.

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StudyCorgi. (2022, December 12). The Limits of Global Inclusion in AI (Artificial Intelligence) Development. Retrieved from https://studycorgi.com/the-limits-of-global-inclusion-in-ai-artificial-intelligence-development/

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StudyCorgi. (2022, December 12). The Limits of Global Inclusion in AI (Artificial Intelligence) Development. https://studycorgi.com/the-limits-of-global-inclusion-in-ai-artificial-intelligence-development/

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StudyCorgi. "The Limits of Global Inclusion in AI (Artificial Intelligence) Development." December 12, 2022. https://studycorgi.com/the-limits-of-global-inclusion-in-ai-artificial-intelligence-development/.

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StudyCorgi. 2022. "The Limits of Global Inclusion in AI (Artificial Intelligence) Development." December 12, 2022. https://studycorgi.com/the-limits-of-global-inclusion-in-ai-artificial-intelligence-development/.

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StudyCorgi. (2022) 'The Limits of Global Inclusion in AI (Artificial Intelligence) Development'. 12 December.

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