Wang, J., Xing, Z. and Zhang, R., Humanities and Social Sciences Communications, 10 (356), 2023.

Employees are important stakeholders of firms, and employee responsibility is a crucial dimension of corporate social responsibility. This study employed a multivariable linear regression model to analyze the impact of AI technology on the variation in employee responsibility. We also utilized multiple methods, such as propensity score matching and alternative indicator analysis, to ensure the robustness of the research results. We theorized and found that the application of AI technology has a negative effect on employee responsibility, with supervision cost partially mediating the relationship between AI technology application and employee responsibility.

Yu, X., Xu, S. and Ashton, M., Information Technology & People, 36 (1), 2023.

The use of artificial intelligence (AI) in the workplace is on the rise. To help advance research in this area, the authors synthesise the academic research and develop research propositions on the antecedents and consequences of AI adoption and application in the workplace to guide future research. The authors also present AI research in the socio-technical system context to provide a springboard for new research to fill the knowledge gap of the adoption and application of AI in the workplace.

Walusiak-Skorupa, J., Kaczmarek, P. and Wiszniewska, M., Medycyna Pracy, 74 (3), 2023.

The purpose of this article is to identify, based on selected literature, possible applications of AI and the potential benefits and risks for humans. In the article, the authors emphasize the importance of relevant EU legislation that guarantees respect for the rights of the employed. The authors put forward the thesis that the new reality with the widespread use of AI, requires an analysis of its impact on the human psycho-social and health situation. Thus, a legal framework defining the scope of monitoring and collection of sensitive data is necessary.

Lu, C.-H., Macroeconomic Dynamics, 3 (4), 2023.

The development of artificial intelligence (AI) does influence human jobs but not necessarily in a negative way. Although labor force participation rates and firms’ job vacancies for human labor decline, the unemployment rate may be lower than that in an economy without AI. In an economy with heterogeneously skilled workers, the invention of AI usually has a negative effect on the skilled labor market but a positive effect on the unskilled labor market. The overall unemployment rate may decline as AI develops.

Selenko, E., Bankins, S., Shoss, M., et al., Current Directions in Psychological Science, 31 (3), 2022.

The authors argues that the conditions for AI to either enhance or threaten workers’ sense of identity derived from their work depends on how the technology is functionally deployed (by complementing tasks, replacing tasks, and/or generating new tasks) and how it affects the social fabric of work. Also, how AI is implemented and the broader social-validation context play a role. It concludes by outlining future research directions and potential application of the proposed framework to organizational practice.

Jetha, A., Bakhtari, H., Rosella, L.C. , et al., American Journal of Industrial Medicine, 66 (10), 2023.

In this article, we present an agenda to guide research examining the implications of AI on the intersection between work and health. To build the agenda, a full day meeting was organized and attended by 50 participants including researchers from diverse disciplines and applied stakeholders. Discussions were synthesized into four research agenda areas: (1) examining the impact of stronger AI on human workers; (2) advancing responsible and healthy AI; (3) informing AI policy for worker health, safety, well-being, and equitable employment; and (4) understanding and addressing worker and employer knowledge needs regarding AI applications.

Gutsu, S., Bublikov, A. and Inna, A., Lecture Notes in Networks and Systems, 657 (July), 2023.

Information technology today has a strong impact on many areas of life and business. AI, neurotechnologies and automation significantly affect the structure of the labor market, the content of the employee's labor function, and over time this influence will only increase. The article discusses the prerequisites for the transformation of labor relations in connection with the introduction of information technology. The purpose of the article is to determine the impact of artificial intelligence, automation and neurotechnologies in the world of work, possible areas of its application, to consider the main problems associated with the regulation of the labor market, as well as granting “smart” robots the status of a subject of law. The authors conclude that it is necessary to amend a number of legal institutions of labor law, as well as the introduction of new norms and tables of safety, labor protection and labor organization.

Jarota, M., Computer Law & Security Review, 49 (July), 2023.

Artificial intelligence (AI) finds increasingly growing applications in the working environment. Its importance has been recognised by the European Parliament and the European Commission, as reflected in the legislation prepared at the European Union level. As the use of AI creates new risks hitherto unknown from an Occupational Health and Safety (OHS) perspective, the question is whether the proposed EU regulations address these risks. The starting point for further consideration should be an analysis of the proposed changes to EU law in the context of the general principles of labour law. In addition to proposals to amend EU law on artificial intelligence, this article examines current occupational safety and health legislation. Issues related to occupational safety and health monitoring of employers using artificial intelligence were also the subject of the study.

Gallego, A. and Kurer, T., Annual Review of Political Science, 25 (May), 2022.

New technologies have been a key driver of labor market change in recent decades. There are renewed concerns that technological developments in areas such as robotics and artificial intelligence will destroy jobs and create political upheaval. This article reviews the vibrant debate about the economic consequences of recent technological change and then discusses research about how digitalization may affect political participation, vote choice, and policy preferences.

Fernández-Macías, E. and Bisello, M., Social Indicators Research, 159 (2), 2022.

In recent years, the increasing concern about the labour market implications of technological change has led economists to look in more detail at the structure of work content and job tasks. Incorporating insights from other traditions of task analysis, in particular from the labour process approach, as well as from recent research on skills, work organisation and occupational change, in this paper we propose a comprehensive and detailed taxonomy of tasks. Going beyond existing broad classifications, our taxonomy aims at connecting the substantive content of work with its organisational context by answering two key questions: what do people do at work and how do they do their work? For illustrative purposes, we show how our approach allows a better understanding of the impact of new technologies on work, by accounting for relevant ongoing transformations such as the diffusion of artificial intelligence and the unfolding of digital labour platforms.

Linnyk, O. and Teetz, I., IEEE Technology & Society Magazine, 42 (2), 2023.

There are three common beliefs about the labor market: first, that increased use of artificial intelligence (AI) is going to cause large-scale unemployment in the future; second, that the postpandemic revitalization of mobility and migration would resupply the markets affected currently by the workforce shortage; and third, that job postings, under existing employment laws, do not use biased language and offer equal opportunities to job seekers. All of them are wrong.

Li, C., Zhang, Y., Niu, X., et al., Systems, 11 (3), 2023.

This paper examines how AI at work impacts on-the-job learning, shedding light on workers’ reactions to the groundbreaking AI technology. Based on theoretical analysis, six hypotheses are proposed regarding three aspects of AI’s influence on on-the-job learning. Empirical results demonstrate that AI significantly inhibits people’s on-the-job learning and this conclusion holds true in a series of robustness and endogeneity checks. The impact mechanism is that AI makes workers more pessimistic about the future, leading to burnout and less motivation for on-the-job learning. In addition, AI’s replacement, mismatch, and deskilling effects decrease people’s income while extending working hours, reducing their available financial resources and disposable time for further learning.

Noy, S. and Zhang, W., Science, 381 (6654), 2023.

We examined the productivity effects of a generative artificial intelligence (AI) technology, the assistive chatbot ChatGPT, in the context of midlevel professional writing tasks. In a preregistered online experiment, we assigned occupation-specific, incentivized writing tasks to 453 college-educated professionals and randomly exposed half of them to ChatGPT. Our results show that ChatGPT substantially raised productivity: The average time taken decreased by 40% and output quality rose by 18%. Inequality between workers decreased, and concern and excitement about AI temporarily rose. Workers exposed to ChatGPT during the experiment were 2 times as likely to report using it in their real job 2 weeks after the experiment and 1.6 times as likely 2 months after the experiment.

Lukács, A. and Váradi, S., Computer Law & Security Review, 50 (September), 2023.

The paper provides a detailed overview on the European legal framework on the data protection aspects of AI-based automated decision-making in the employment context. It identifies the main challenges, such as the applicability of the existing legal framework to the current use-cases and the specific questions relating to the lawful bases in the world of work, and provides guidelines on how to address these challenges.

Malik, N., Tripathi, S.N., Kar, A.K., et al., International Journal of Manpower, 43 (2), 2022.

This study attempts to develop a practical understanding of the positive and negative employee experiences due to artificial intelligence (AI) adoption and the creation of technostress. It unravels the human resource development-related challenges with the onset of Industry 4.0. The findings establish prominent adverse impacts of the adoption of AI, namely, information security, data privacy, drastic changes resulting from digital transformations and job risk and insecurity brewing in the employee psyche. This is followed by a hierarchy of factors comprising the positive impacts, namely, work-related flexibility and autonomy, creativity and innovation and overall enhancement in job performance. Further factors contributing to technostress (among employees): work overload, job insecurity and complexity were identified.

Morandini, S., Fraboni, F., De Angelis, M., et al., Informing Science, 26, 2023.

This paper aims to investigate the recent developments in research and practice on the transformation of professional skills by artificial intelligence (AI) and to identify solutions to the challenges that arise. This work contributes to the body of knowledge by examining recent trends in research and practice on how AI will transform professional skills and workplaces, highlighting the crucial role played by transversal skills and identifying strategies that can support organisations and guide workers toward the upskilling and reskilling challenges.

Zhang, Z., Technological Forecasting and Social Change, 197 (December), 2023.

This study endeavors to examine the intricate impact of the industries related to artificial intelligence (AI) on both the quantity of labor employment in terms of quantity and the evolving structure of the job market. The study constructs a mechanism and theoretical model to elucidate labor employment dynamics and structural transformations within the AI industry. The research findings reveal discernible trend in China's labor force characterized by a heightened emphasis on education and increased employment opportunities. This study makes a substantial contribution to the field by constructing innovative mechanisms and theoretical frameworks that facilitate a profound comprehension of the intricacies surrounding labor employment and structural changes in the AI industry. This comprehension is grounded in an analysis of the prevailing employment quantity and structure.

Foster-McGregor, N., Nomaler, Ö. and Verspagen, B., Research Policy, 50 (7), 2021.

Recent studies report that technological developments in machine learning and artificial intelligence present a significant risk to jobs in advanced countries. We re-estimate automation risk at the job level, finding sectoral employment structure to be key in determining automation risk at the country level. At the country level, we find a negative relationship between automation risk and labour productivity. We then analyse the role of trade as a factor leading to structural changes and consider the relation between trade and aggregate automation risk by comparing automation risk between a hypothetical autarky and the actual situation.

Duch-Brown, N., Gomez-Herrera, E., Mueller-Langer, F., et al., Research Policy, 51 (3), 2022.

The study investigates three alternative but complementary indicators of market power on one of the largest online labour markets (OLMs) in Europe: (1) the elasticity of labour demand, (2) the elasticity of labour supply, and (3) the concentration of market shares. It explores how these indicators relate to an exogenous change in platform policy. In the middle of the observation period, the platform made it mandatory for employers to signal the rates they were willing to pay as given by the level of experience required to perform a project, i.e., entry, intermediate or expert level. A positive labour supply elasticity was found, ranging between 0.06 and 0.15, which is higher for expert-level projects.

Matthew C., Callum C., Funda U.S., et al., Frontiers in Artificial Intelligence, 15 (July), 2022.

One of the main hurdles to establishing “ethical AI” remains how to operationalize high-level principles such that they translate to technology design, development and use in the labor process. This is because organizations can end up interpreting ethics in an ad-hoc way with no oversight, treating ethics as simply another technological problem with technological solutions, and regulations have been largely detached from the issues AI presents for workers. Topics such as discrimination and bias in job allocation, surveillance and control in the labor process, and quantification of work have received significant attention, yet questions around AI and job quality and working conditions have not. This has left workers exposed to potential risks and harms of AI.

Jaiswal, A., Arun, C.J. and Varma, A., International Journal of Human Resource Management, 33 (6), 2022.

Proponents of artificial intelligence (AI) have envisaged a scenario wherein intelligent machines would execute routine tasks performed by humans, thus, relieving them to engage in creative pursuits. While there is widespread fear of corresponding job losses, organizational think tanks vouch for the synergistic culmination of human–machine competencies. Using the dynamic skill, neo-human capital and AI job replacement theories, we contend that the introduction and adoption of AI calls for employees to upskill themselves.

Pereira, V., Hadjielias, E., Christofi, M., et al., Human Resource Management Review, 33 (1), 2023.

Proponents of artificial intelligence (AI) have envisaged a scenario wherein intelligent machines would execute routine tasks performed by humans, thus, relieving them to engage in creative pursuits. While there is widespread fear of corresponding job losses, organizational think tanks vouch for the synergistic culmination of human–machine competencies. Using the dynamic skill, neo-human capital and AI job replacement theories, we contend that the introduction and adoption of AI calls for employees to upskill themselves.

Ooi, V. and Goh, G., eJournal of Tax Research, 19 (2), 2022.

Rapidly developing automation technology risks creating a mass displacement of human labour. An automation tax could slow the adoption of such technology in appropriate circumstances, giving workers time to adapt. Implementing the tax through changes to the existing schedular system of depreciation/capital allowances would reduce the uncertainty of application and costs, and be flexible enough to keep up with rapid technological developments. The mechanism would adjust: 1) accelerated depreciation, and 2) bonus depreciation. The tax provides a useful tool to counter sudden and massive labour displacement, but must be applied with care so as not to disincentivise efficiency gains.

La Torre, D., Colapinto, C., Durosini, I., et al., IEEE Transactions on Engineering Management, 70 (5), 2023.

The need for preparing for digital transformation is a recurrent theme in the recent public and academic debate. Artificial Intelligence (AI) has the potential to reduce operational costs, increase efficiency, and improve customer experience. Thus, it is crucial to forming project teams in an organization, in such a way that they will welcome AI in the decision-making process. The current technological revolution is demanding a rapid pace of change to companies and has increased the attention to the role of teams in fostering innovation adoption.

Gutsu, S. and Bublikov, A., Integrated Computer Technologies in Mechanical Engineering - 2021, 367, 2022.

The article is devoted to research on prospects artificial intelligence implementation in the field of labor relations. The tendencies inherent in digitalization processes influencing labor field are marked, and also the changes which will occur in the field of labor law are forecasted. It is determined that with development of artificial intelligence, the range of subjects of labor law will be expanded. With acquisition of the legal status of Electronic personhood in civil law, “smart” jobs will be able to obtain the status of a subject in the employment relationship.