Journal Article

Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when automating prediction leads to automating decisions versus enhancing decision-making by humans.

Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a small summer workshop at Dartmouth College in 1956. Since then, AI applications made possible by machine learning (ML), an AI subdiscipline, include Internet searches, e-commerce sites, goods and services recommender systems, image and speech recognition, sensor technologies, robotic devices, and cognitive decision support systems (DSSs). As more applications are integrated into everyday life, AI is predicted to have a globally transformative influence on economic and social structures similar to the effect that other general-purpose technologies, such as steam engines, railroads, electricity, electronics, and the Internet, have had. Novel AI applications in the workplace of the future raise important issues for occupational safety and health. This commentary reviews the origins of AI, use of ML methods, and emerging AI applications embedded in physical objects like sensor technologies, robotic devices, or operationalized in intelligent DSSs. Selected implications on the future of work arising from the use of AI applications, including job displacement from automation and management of human-machine interactions, are also reviewed. Engaging in strategic foresight about AI workplace applications will shift occupational research and practice from a reactive posture to a proactive one. Understanding the possibilities and challenges of AI for the future of work will help mitigate the unfavorable effects of AI on worker safety, health, and well-being.

Unemployment data and a fast-changing environment have elicited reflections about the skills and personal traits required to face the increasing complexity brought by the 'glocal, liquid and networked' world in which workers operate. Several definitions and categorisations of the 'soft skills' are present in the literature, but there is a lack of scientific research on the topic and very few studies have been able to contribute significantly to the discussion on the practitioners' side. A literature review addressing and structuring this issue is presented in this article and the authors propose a preliminary list of relevant soft skills to enter the job market in order to lay the foundations for a comprehensive conceptual study. As a first step, a pilot study was carried out to validate the list of 22 soft skills. It was ranked and validated by a panel of Italian HR managers. Results confirmed that the development of soft skills is a top priority on the agenda of Italian HR managers and, in particular, teamwork, communication, results orientation, and learning skills (9%) are felt to be primary skills when assessing young graduates.

The media and popular business press often invoke narratives that reflect widespread anxiety that robots may be rendering humans obsolete in the workplace. However, upon closer examination, many argue that automation, including robotics and artificial intelligence, is spreading unevenly throughout the labor market, such that middle-skill occupations that do not require a college degree are more likely to be affected adversely because they are easier to automate than high-skill occupations. In this article, the author examines the effect of industrial robots on occupations in the United States in 2010 and 2015. Results from regression models indicate that an increase in industrial robots is associated with increases in high-skill and some middle-skill occupations but not for other types of occupations. These findings may indicate the ushering in of a new era in which robots are more technologically advanced and able to collaborate better with human employees.

This article investigates how educational level, job-related skills and employers' support for competence development jointly determine Norwegian employees' expectations of maintaining employment and career advancement. The data were collected in 2010 and 2013, and they comprise a representative sample of Norwegian employees. In contrast to previous research on self-perceived employability, this study divides expectations of advancement and continued employment. The results show that these are different measures of labour market success. While education is significantly correlated with both measures, the employer's support for competence development is important for expectations of career advancement, especially among the highly educated, whereas the job-skills match is most relevant for the expectation of maintaining employment.

This paper examines the effectiveness of active labour market policies (ALMPs) in improving labour market outcomes, especially of low-skilled individuals, by means of a pooled cross-country and time series database for 31 advanced countries during the period 1985-2010. The analysis includes aspects of the delivery system to see how the performance of ALMPs is affected by different implementation characteristics. Among the notable results, the paper finds that ALMPs matter at the aggregate level, but mostly through an appropriate management and implementation. In this regard, sufficient allocation of resources to programme administration and policy continuity appear to be particularly important. Moreover, start-up incentives and measures aimed at vulnerable populations are more effective than other ALMPs in terms of reducing unemployment and increasing employment. Interestingly, the positive effects of these policies seem to be particularly beneficial for the low skilled., The ILO Research Department released a working paper by this author, 'Are active labour market policies effective in activating and integrating low-skilled individuals?: an international comparison', in 2015.

The paper evaluates the readiness of apprenticeship systems to cope with five major developments affecting the future of work. The institution of apprenticeship has evolved over time in all countries, gradually adapting to changes in industrial processes, the economy, the labour market and education systems. This paper suggests, however, that recent changes in the economy and the labour market, and their concomitant effects on the likely future of work, have the potential to disrupt apprenticeship systems quite radically worldwide, and/or to make them less relevant in the 21st century. The paper draws on data from recent Australian and international research projects undertaken by the author, as well as the author's engagement in Australian government exercises to discuss the future of apprenticeships. The research found that adaptations of systems and processes were being undertaken at company level and by stakeholders such as trade union or employer peak bodies. They were less frequently apparent, however, in government policy. The paper analyses the data to produce a framework of readiness for ‘future work', but also queries whether adaptation of apprenticeship systems is necessarily desirable in all instances. Although the presence of multiple stakeholders in the system has previously been viewed as a strength of the system, it can also make even minor changes difficult to implement. This could prove to be a major impediment to apprenticeship's future or could be a means of preserving its essential features.

A discourse of employability saturates the higher education sector in the UK. Government and employers call on universities to produce employable graduates who are attractive to the labour market and can sustain their future marketability by taking responsibility for protean self-development. While the neoliberal assumptions behind this call have attracted robust critique, the extent to which employers shape graduating students' subjectivities and sense of worth as (potentially employable) workers has escaped scrutiny. Inspired by Foucauldian analyses of human resource management (HRM) practices, this article examines employers' graduate careers websites and explores the discursive construction of the 'employable graduate'. The article contends that these websites function as a mechanism of anticipatory socialization through which HRM practices extend managerial control into the transitional space of pre-recruitment, with the aim of engaging students' consent to particular norms of employability.

Background: By applying the inventory theory to hiring skilled workers under uncertainty, the authors explain how firms decide on their optimum investment in an 'inventory of skills'. This paper investigates the conditions under which firms are willing to make investments in a skilled workforce themselves rather than relying on skills produced within the education system or by other companies. By applying inventory theory to investments into apprenticeship training, the authors explain how firms decide on producing an optimum 'inventory of skills' today to meet future demand. The authors derive hypotheses on how much firms are willing to invest in having a larger inventory of skilled workers depending on different types of inventory costs (overage costs, underage costs, demand structure). Methods: The authors use data from the BIBB Cost-Benefit-Survey 2012/2013, which comprises detailed information on different costs and benefits of training investments from the firm's perspective. The study applies a negative binomial estimation model., Results: Results are threefold: firms are willing to invest in a larger inventory of skilled workers, i.e., to train more apprentices, first, if the costs of producing and retaining an excessive number of skilled workers (overage costs) are lower, second, if the costs of being short of skilled workers (underage costs) are higher, and third, given an identical cost structure, if it is more likely that the demand for skilled workers may be high in the future. Even more important is the relationship of the three: the combination of a firm's critical ratio (underage costs in relation to overage costs) with its demand structure (industry volatility) is associated with a higher inventory of skills. Conclusion: The findings (particularly the relation of underage and overage costs, in combination with the demand structure) have important policy implications for firms' incentives to invest in apprenticeship training.