Labor · Job Displacement

All Job Displacement Hiring & Screening New Roles & Skills Workplace Monitoring

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From automation technology to generative AI: skill heterogeneity in technology’s impact on laborers

Abstract This is a study of skill heterogeneity in technology’s impact on laborers transitioning from physical automation to cognitive automation. The findings indicate that cognitive skills are a crucial determinant of the extent of technological influence. Considering both technological substitution and technological control, high-skilled and low-skilled workers experience limited technological substitution. However, high-skilled workers are not significantly affected by technological control, whereas low-skil…

The Journal of Chinese Sociology · Labor

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Technology-Driven Change in Human Resource Management: Reshaping Talent Management and Organizational Design

The digital transformation of human resource management is fundamentally reshaping how organizations manage talent and design their structures. However, a comprehensive understanding of the drivers, impacts, and implementation challenges of this shift is critically needed. The purpose of this review is to consolidate recent literature to provide a holistic overview of this technology-driven evolution. It examines key technological drivers—such as artificial intelligence, automation, and data analytics—and their…

Labor

Both readings

A Framework for Future Human Resource Management Individual Competencies: An Integrative Review

The advent of automation, artificial intelligence and disruptive technologies has affected the role of the Human Resource Management (HRM) professionals and taken over some HRM functions thereby imposing new sets of competencies for HRM professionals. Yet, there is limited research on the full spectrum of competencies needed to execute the HRM function successfully in an increasingly technologically dynamic environment. Hence, the purpose of this research was to develop a framework for future HRM individual comp…

Labor

Evidence-backed problem

Skill-biased technological change in the age of AI: a theoretical analysis of automation and inequality

This paper develops a general equilibrium model to analyze how artificial intelligence (AI)–driven automation reshapes productivity, labor markets, and income distribution. The model features heterogeneous workers, endogenous automation decisions, and irreversible skill investment choices, allowing a unified examination of displacement, complementarity, and skill-supply responses. Automation substitutes for labor in routine tasks, reducing demand and wages for low-skilled workers, while simultaneously enhancing…

Labor

Evidence-backed problem

AI job layoffs are here: it’s time to revive the push for shorter working hours | John Quiggin

The announcement that Australian software giant Atlassian will lay off 10% of staff has brought the debate over artificial intelligence (AI) and jobs closer to home. While a broader question about the usefulness of AI remains unresolved, there can be no remaining doubt that it has transformed the software industry, with developers reporting massive increases in productivity from the use of Anthropic’s AI-powered coding tool Claude. The spectre of AI-driven job losses has been the subject of much debate. But missing

Labor

Evidence-backed problem

Third of university students in Great Britain think AI job losses will cause social unrest, poll finds

One in three university students think AI will wipe out jobs so rapidly it will trigger civil unrest, according to a survey by King’s College London (KCL). Students are among the heaviest users of AI, the poll found, with 77% using it at least a few times a month – compared with 46% of workers – and 27% using it daily or almost daily. They are also among the most pessimistic about AI’s economic impact. More than half said they were convinced job losses would be worse than in a normal recession. The findings are the

Labor

Evidence-backed problem

US companies accused of ‘AI washing’ in citing artificial intelligence for job losses

Over the last year, US corporate leaders have often explained layoffs by saying the positions were no longer needed because artificial intelligence had made their companies more efficient, replacing humans with computers. But some economists and technology analysts have expressed skepticism about such justifications and instead think that such workforce cuts are driven by factors like the impact of tariffs, overhiring during the Covid-19 pandemic and perhaps simple maximising of profits. In short, the CEOs are alle

Labor

No shared standard for reporting AI job displacement by region

Current estimates vary 5x depending on methodology.

Labor

No shared standard for reporting AI job displacement by region