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Article summary:
1. This article reviews recent literature on the likely impacts of artificial intelligence (AI) in the world of work, bringing together disparate scholarship on AI in the world of work and critically evaluating problematic assumptions driving leading interpretations and predictions regarding the future of work.
2. The article defines "work" as activities individuals engage in as part of the production of goods and services, for a profit if they are business owners, for a wage if they are employees, in the commercial, public or third sector. It also highlights the capitalist imperative and nationalistic pressures that influence AI innovation and deployment.
3. The article focuses on issues such as technological unemployment, algorithmic management, platform work, and the political dimensions of AI's impact on work. It suggests that it is necessary to be reflective of the context in which AI is deployed, as powerful background imperatives influence its development and deployment.
Article analysis:
The article "Artificial intelligence and work: a critical review of recent research from the social sciences" provides a comprehensive overview of the literature on the impact of AI on work. The authors take a non-specialized approach, covering a broad range of issues related to AI's impact on economies, social structures, and working people. However, this approach also has its drawbacks, as it may miss important details and references in each disciplinary field.
The authors define their critical approach as one that considers the historical context in which scientific inquiries occur. They argue that knowledge claims reflect social and political fault lines. In studying the impact of AI on work, it is crucial to keep in mind what kinds of imperatives and pressures AI innovation and deployment are under. These include the capitalistic imperative and nationalistic pressures.
The article provides an insightful analysis of these two features' influence on AI's development and deployment. The capitalist imperative drives firms to invest in AI to cut costs, increase outputs through rationalization of production processes, raise productivity, manage the workforce more efficiently (including through increased surveillance), refine customer knowledge, and establish monopoly positions. Meanwhile, nationalistic pressures drive countries to invest significantly in AI research for military purposes or economic competition.
However, while the article provides a thorough analysis of these factors' influence on AI's development and deployment, it does not explore counterarguments or potential risks associated with these imperatives. For example, while increasing productivity may benefit firms' profits in the short term by reducing labor costs, it may also lead to job losses and exacerbate income inequality in the long run.
Moreover, while the article acknowledges that work covers activities beyond formal economic activity (such as social reproduction), it restricts its focus to formal economic activity for practical reasons. This narrow focus may overlook important aspects of how AI impacts work beyond formal economic activity.
Overall, "Artificial intelligence and work: a critical review of recent research from the social sciences" provides valuable insights into how historical context shapes knowledge claims about AI's impact on work. However, its non-specialized approach may miss important details in each disciplinary field. Additionally, while it acknowledges some potential risks associated with capitalistic imperatives driving AI development and deployment, it does not explore counterarguments or other potential risks associated with these imperatives fully.