Communicative Frontiers: The Role of Media and Communication Strategies in the Adoption of AI and Real-Time Data in Thrust Manufacturing
Keywords:
Artificial Intelligence In Manufacturing, Real-Time Data Analytics, Media And Communication Strategies, Public Perception Of Technology, Ethical Considerations In Digital Transformation.Abstract
This research paper delves into the transformative integration of Artificial Intelligence (AI) and real-time data analytics within thrust manufacturing, focusing on the consequential shifts in media and communication strategies. Amidst the rapid technological advancements in manufacturing sectors, especially those involving complex production processes like thrust manufacturing, this study aims to unravel how these innovations are communicated to and perceived by the public, stakeholders, and the media. Employing a mixed-methods approach that combines content analysis, stakeholder interviews, and public surveys, the paper investigates the evolution of communication channels, the effectiveness of current media strategies, and the public's understanding and reception of AI-driven manufacturing technologies. It further scrutinises the ethical dimensions relayed through media narratives, including concerns around data privacy, workforce displacement, and the reliability of automated systems. By identifying gaps in knowledge, misconceptions, and areas for communicative improvement, the research seeks to propose innovative approaches for fostering transparency, engagement, and informed public discourse. The findings are poised to offer actionable insights for manufacturers, policymakers, and media professionals, aiming to enhance the alignment between technological innovations and societal expectations. This paper contributes to the discourse on the critical role of media and communication in the era of industrial digital transformation, highlighting the interplay between technological advances and their societal implications.
References
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Brown, A., & Marsen, S. (2021). AI in industrial manufacturing: Opportunities, challenges, and applications. Journal of Manufacturing Systems, 58, 227-239.
Li, X., Yang, H., & Kankanhalli, A. (2020). Real-time data in manufacturing: A survey. Computers in Industry, 115, 103125.
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