Applications and Societal Implications of Artificial Intelligence in
Manufacturing: A Systematic Review
- URL: http://arxiv.org/abs/2308.02025v1
- Date: Tue, 25 Jul 2023 07:17:37 GMT
- Title: Applications and Societal Implications of Artificial Intelligence in
Manufacturing: A Systematic Review
- Authors: John P. Nelson, Justin B. Biddle, Philip Shapira
- Abstract summary: The study finds that there is a predominantly optimistic outlook in prior literature regarding AI's impact on firms.
The paper draws analogies to historical cases and other examples to provide a contextual perspective on potential societal effects of industrial AI.
- Score: 0.3867363075280544
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: This paper undertakes a systematic review of relevant extant literature to
consider the potential societal implications of the growth of AI in
manufacturing. We analyze the extensive range of AI applications in this
domain, such as interfirm logistics coordination, firm procurement management,
predictive maintenance, and shop-floor monitoring and control of processes,
machinery, and workers. Additionally, we explore the uncertain societal
implications of industrial AI, including its impact on the workforce, job
upskilling and deskilling, cybersecurity vulnerability, and environmental
consequences. After building a typology of AI applications in manufacturing, we
highlight the diverse possibilities for AI's implementation at different scales
and application types. We discuss the importance of considering AI's
implications both for individual firms and for society at large, encompassing
economic prosperity, equity, environmental health, and community safety and
security. The study finds that there is a predominantly optimistic outlook in
prior literature regarding AI's impact on firms, but that there is substantial
debate and contention about adverse effects and the nature of AI's societal
implications. The paper draws analogies to historical cases and other examples
to provide a contextual perspective on potential societal effects of industrial
AI. Ultimately, beneficial integration of AI in manufacturing will depend on
the choices and priorities of various stakeholders, including firms and their
managers and owners, technology developers, civil society organizations, and
governments. A broad and balanced awareness of opportunities and risks among
stakeholders is vital not only for successful and safe technical implementation
but also to construct a socially beneficial and sustainable future for
manufacturing in the age of AI.
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