Examining the Social Consequences of Automation and Artificial Intelligence in Industrial Management

Abstract

This article examines the social consequences of automation and artificial intelligence (AI) in industrial management, drawing on the findings of Damioli, Van Rooy, and Vertsy’s (2021) study on the impact of AI on labor productivity. The integration of AI technologies in industrial settings has led to significant improvements in efficiency and productivity. However, these advancements come with substantial social implications that affect both the workforce and broader societal structures. Internally, automation and AI have shifted the demand from low-skilled to high-skilled labor, necessitating ongoing education and skill development for employees. Additionally, the reliance on AI for managerial decisions raises ethical concerns regarding algorithmic biases and the potential erosion of human judgment.

Externally, the broader societal impact includes economic disparities, as regions with a high concentration of low-skilled jobs experience greater unemployment and underemployment. The displacement of workers due to automation presents challenges such as increased socio-economic divides and disruptions to community stability. Ethical considerations, including data privacy and security, are crucial to ensuring fair and responsible AI deployment. This article underscores the need for strategic collaboration between industry leaders, policymakers, and educational institutions to address these social consequences. By fostering an inclusive approach to technological advancement, it is possible to balance the productivity benefits of AI with the imperative to mitigate its adverse social impacts.