Labor

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LaborEvidence-backed problem

Evidence of a social evaluation penalty for using AI

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further,…

Proceedings of the National Academy of Sciences

Evidence-backed gain

AI and employee wellbeing in the workplace: An empirical study

Evidence-backed gain

The impact of AI literacy on work–life balance and job satisfaction among university faculty: a self-determination theory perspective

Evidence-backed gain

GDPVAL: Evaluating AI Model Performance on Real-World Economically Valuable Tasks

Evidence-backed gain

The Health-Wealth Gradient in Labor Markets: Integrating Health, Insurance, and Social Metrics to Predict Employment Density

Labor market forecasting relies heavily on economic time-series data, often overlooking the “health–wealth” gradient that links population health to workforce participation. This study develops a machine learning framework integrating non-traditional health and social metrics to predict state-level employment density. Methods: We constructed a multi-source longitudinal dataset (2014–2024) by aggregating county-level Quarterly Census of Employment and Wages (QCEW) data with County Health Rankings to the state lev…

Evidence-backed gain

AI job worries grow. But some human skills can’t be replaced by machines | Gaynor Parkin and Dave Winsborough

Earlier this year Paul* discovered via a flurry of media stories that his business group had been targeted for job cuts, alongside a number of other public-sector agencies. For him, this was the second time, after his technical management role was restructured in 2024. While that process was difficult enough, the comms this time were highlighting the integration of AI as a cost-saving tool. “They say it’s not about firing people, but hey, my whole team will go.” For Paul, the timing could not have been worse. He…

Both readings

Navigating the Complexity of Generative AI Adoption in Software Engineering

This article explores the adoption of Generative Artificial Intelligence (AI) tools within the domain of software engineering, focusing on the influencing factors at the individual, technological, and social levels. We applied a convergent mixed-methods approach to offer a comprehensive understanding of AI adoption dynamics. We initially conducted a questionnaire survey with 100 software engineers, drawing upon the Technology Acceptance Model, the Diffusion of Innovation Theory, and the Social Cognitive Theory a…

Both readings

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…

Labor

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

Strategic Human Resource Management in the Digital Era: Technology, Transformation, and Sustainable Advantage

The rapid integration of emerging technologies into organizational processes has fundamentally redefined the role of strategic human resource management (SHRM). This paper explores how digital innovations—such as artificial intelligence (AI), robotic process automation (RPA), blockchain, and immersive technologies—are reshaping the workforce and transforming the way organizations attract, develop, and retain talent. In the context of the digital era, human capital is no longer a passive input but a strategic ena…

Labor

Fairness, AI & recruitment

The ever-increasing adoption of AI technologies in the hiring landscape to enhance human resources efficiency raises questions about algorithmic decision-making's implications in employment, especially for job applicants, including those at higher risk of social discrimination. Among other concepts, such as transparency and accountability, fairness has become crucial in AI recruitment debates due to the potential reproduction of bias and discrimination that can disproportionately affect certain vulnerable groups…

Labor

Generative-AI, the media industries, and the disappearance of human creative labour

This article addresses the transformative role of Generative-AI (Gen-AI) in the creative media and arts industries, focusing on concerns about the disappearance of human creative labour.It critically examines the discourse of the 2023 Writers' and Actors' strikes, which replicates prevailing assumptions of the superiority of human creativity over Gen-AI.This discourse emphasises a 'replacing tasks' model, anticipating a future where AI assists human creatives in a limited capacity.Against this background, the ar…

Labor

Problematizing the role of artificial intelligence in hiring and organizational inequalities: A multidisciplinary review

What are the implications of the growing use of artificial intelligence (AI) in recruitment and hiring for organizational inequalities? While advocates suggest that AI is a groundbreaking tool that can enhance hiring precision, efficiency, diversity and fit, critics raise serious concerns around bias, fairness, and privacy. This review article critically advances this debate by drawing on diverse scholarship across computing and data sciences; human resource, management, and organization studies; social sciences…

Labor

Artificial intelligence in industry – ethical challenges

Abstract Artificial intelligence is revolutionising industry, significantly improving work efficiency. However, the development of AI continues to generate new ethical challenges. An international legal framework has already been developed to ensure the ethical and safe development of AI. However, it seems that new threats and ethical dilemmas continue to arise as AI develops further. This study aims to explain some of the benefits and threats of using AI in industry and to encourage reflection on the need to in…

Labor

Garbage in, garbage out? How the monster of AI art reflects human fault, bias, and capitalism in contemporary culture

Abstract This paper examines the relationship between artificial intelligence, contemporary artistic production and content creation through an intersectional feminist framework, arguing that AI operates as a reflective system that reproduces and amplifies existing social, economic, and cultural biases. Beginning with examples of AI artistic collaborations such as 'What I Saw Before the Darkness', and 'Théâtre D'opéra Spatial' the research investigates how generative AI exposes underlying tensions surrounding cr…