Digitale Arbeitswelt – Chancen und Herausforderungen für Beschäftigte und Arbeitsmarkt
Der digitale Wandel der Arbeitswelt gilt als eine der großen Herausforderungen für Wirtschaft und Gesellschaft. Wie arbeiten wir in Zukunft? Welche Auswirkungen hat die Digitalisierung und die Nutzung Künstlicher Intelligenz auf Beschäftigung und Arbeitsmarkt? Welche Qualifikationen werden künftig benötigt? Wie verändern sich Tätigkeiten und Berufe? Welche arbeits- und sozialrechtlichen Konsequenzen ergeben sich daraus?
Dieses Themendossier dokumentiert Forschungsergebnisse zum Thema in den verschiedenen Wirtschaftsbereichen und Regionen.
Im Filter „Autorenschaft“ können Sie auf IAB-(Mit-)Autorenschaft eingrenzen.
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
- Qualifikationsanforderungen und Berufe
- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
- Arbeits- und sozialrechtliche Aspekte / digitale soziale Sicherung
- Deutschland
- Andere Länder/ internationaler Vergleich
- Besondere Personengruppen
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Literaturhinweis
Technologischer Wandel und Löhne: Die Anpassung der Berufe spielt eine entscheidende Rolle (2026)
Zitatform
Bachmann, Ronald, Gökay Demir, Colin Green & Arne Uhlendorff (2026): Technologischer Wandel und Löhne: Die Anpassung der Berufe spielt eine entscheidende Rolle. (IAB-Kurzbericht 01/2026), Nürnberg, 8 S. DOI:10.48720/IAB.KB.2601
Abstract
"Technischer Fortschritt verändert die Arbeitswelt - besonders in Berufen, in denen viele Tätigkeiten leicht automatisiert werden können. In den letzten Jahrzehnten ist der Anteil an Routinetätigkeiten in vielen Berufen deutlich zurückgegangen - häufig zugunsten nicht routinemäßiger kognitiver Tätigkeiten wie Analysieren, Planen oder Beraten. Dabei verzeichnen Berufe, deren Tätigkeiten sich im Laufe der Zeit stärker an den technologischen Wandel angepasst haben, steigende Löhne. Sie zeichnen sich zudem durch intensivere Weiterbildungsaktivitäten aus. In Berufen, deren Tätigkeitsprofil sich kaum verändert hat, stagnieren die Löhne dagegen häufiger." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
- Vollzeitbeschäftigte westdeutsche Männer in ursprünglich routinelastigen Berufen
- Veränderung von Tätigkeitsschwerpunkten durch technologischen Wandel
- Veränderung im Anteil der Routinetätigkeiten
- Veränderung im Anteil der Routinetätigkeiten im Vergleich zu nicht routinemäßigen (NR) kognitiven Tätigkeiten in exemplarisch ausgewählten, ursprünglich routinelastigen Berufsfeldern
- Anteil Beschäftigter in Weiterbildungskursen nach Tätigkeitsgruppen
- Relatives Lohnwachstum nach Tätigkeitsgruppen
- Vollzeitbeschäftigte westdeutsche Männer nach Tätigkeitsgruppen
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Literaturhinweis
Winners and losers when firms robotize: wage effects across occupations and education (2026)
Zitatform
Barth, Erling, Marianne Røed, Pål Schøne & Janis Umblijs (2026): Winners and losers when firms robotize: wage effects across occupations and education. In: The Scandinavian Journal of Economics, Jg. 128, H. 1, S. 3-32. DOI:10.1111/sjoe.12593
Abstract
"This paper analyses the impact of robots on workers' wages in the manufacturing sector, with a particular focus on relative wages for workers with different levels of education and in different occupations. Using high-quality matched employer–employee register data with firm-level information on the introduction of industrial robots, we identify the effects of robotization on relative wages within firms. Skilled blue-collar workers with a vocational degree experience a decline in wages when firms introduce robots, while there are only small effects for the other groups of workers. These results suggest that robots are substitutes for tasks undertaken by skilled blue-collar workers in manufacturing, and furthermore that the adoption of robots contributes to a polarization of the labor market and a hollowing out of the wage distribution, rather than to skill-biased technical change." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Investigating social protection amongst platform workers in Germany: forced individualisation, hybrid income generation and undesired regulation (2026)
Zitatform
Beckmann, Fabian, Sabrina Glanz, Fabian Hoose & Serkan Topal (2026): Investigating social protection amongst platform workers in Germany: forced individualisation, hybrid income generation and undesired regulation. In: Journal of Social Policy, Jg. 55, H. 1, S. 100-118. DOI:10.1017/s0047279424000217
Abstract
"The social protection of platform workers is considered one of the most precarious features and political challenges of this new form of employment. Still, there have only been a few empirical investigations on this issue to date. This article presents an explorative empirical analysis of the social protection of platform workers in Germany – a conservative welfare regime with a strong link between standard employment and institutionalized social protection. On the basis of an online survey amongst 719 self-employed platform workers, we examine how different employment patterns correspond to institutionalized protection against sickness and old age. We empirically explore different protection types and analyse how they differ regarding working conditions in platform work and individual social policy preferences. Findings reveal that conditions of platform work and social protection as well as demands and regulatory preferences vary notably across different clusters of platform workers. Still, the vast majority votes against obligatory social insurances for platform workers and favors self-employment over dependent employment. Against this background, we discuss challenges for future attempts aiming at improving social protection for platform workers. This study adds to the literature by empirically exploring platform workers’ social protection and social policy preferences, which have been overlooked to date." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation Experiments and Inequality (2026)
Zitatform
Benzell, Seth Gordon & Kyle R. Myers (2026): Automation Experiments and Inequality. (NBER working paper / National Bureau of Economic Research 34668), Cambridge, Mass, 26 S., App. DOI:10.3386/w34668
Abstract
"Many experiments study the productivity effects of automation technologies such as generative algorithms. A key test in these experiments relates to inequality: does the technology increase output more for high- or low-skill workers? However, the theoretical content of this empirical test has been unclear. Here, we formalize a theory that describes the experimental effect of automation technologies on worker-level output and, therefore, inequality. Worker-level output depends on a task-level production function, and workers are heterogeneous in their task-level skills. Workers perform a task themselves or delegate it to the automation technology. The inequality effect of improved automation depends on the interaction of two factors: (i) the correlation in task-level skills across workers, and (ii) workers' skills relative to the technology's effective skill. In many cases we study, the inequality effect is non-monotonic --- as technologies improve, inequality decreases then increases. The model and descriptive statistics of skill correlations generally suggest that the diversity of automation technologies will play an important role in the evolution of inequality." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digital divide and income inequality: causal evidence from Italian provinces (2026)
Zitatform
Bergantino, Angela Stefania, Giulio Fusco, Mario Intini & Gianluca Monturano (2026): Digital divide and income inequality: causal evidence from Italian provinces. In: The Annals of Regional Science, Jg. 75, H. 1. DOI:10.1007/s00168-025-01440-z
Abstract
"The digital economy can function either as a catalyst to stimulate economic growth or else as a driver of socioeconomic inequality when its benefits are unevenly distributed. This study investigates the effect of rural digital connectivity on income inequality in Italy. Utilizing NUTS 3 panel data spanning 2014–2022, we conduct a counterfactual Difference-in-Differences approach with continuous treatment intensity to estimate the impact of introducing rural broadband coverage at speeds of 30 and 100 Mbps on multiple measures of income distribution, including the Gini, Theil, and Atkinson indices. The empirical framework incorporates a comprehensive set of socioeconomic controls, as well as provincial and time fixed effects, to account for unobserved heterogeneity and regional path dependencies. Our findings indicate that broadband expansion is significantly associated with increasing inequality, suggesting that access alone does not guarantee inclusive outcomes, particularly in localities characterized by structural fragility and limited human capital. Additional heterogeneity and spatial analyses demonstrate that these inequality effects are more evident in southern provinces and localities with a higher concentration of inner areas, where the digital divide remains more pronounced. These findings accentuate the dual role of digitalization and highlight the necessity of coordinated policy interventions that combine infrastructure investment with digital skills development, institutional capacity-building, and spatially integrated governance strategies." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The EU compromise machine and the politicisation of social policy: Lessons from the regulation of platform work (2026)
Zitatform
Crespy, Amandine, Bastian Kenn, Matteo Marenco & Slavina Spasova (2026): The EU compromise machine and the politicisation of social policy: Lessons from the regulation of platform work. In: Journal of European Social Policy, Jg. 36, H. 1, S. 18-33. DOI:10.1177/09589287251345912
Abstract
"Over the past few years, the legal status and the working conditions of platform workers have been among the most debated manifestations of the digital transformation of work. Tense negotiations on the EU platform work directive (from 2021 to 2024) epitomize long-standing conflicts in EU social policymaking, namely the opposition between capital and labor, on the one hand, and resistance to EU involvement or impact on Member States’ social arrangements, on the other. This paper provides an in-depth inquiry of the policy process by focussing specifically on the presumption of employment in platform work, which was first proposed as an EU-wide provision and eventually nationalized with its definition left to national arrangements. Drawing on this case and mobilizing the literature on positive integration entrepreneurship, and politicization, we shed light on the ‘drivers’ and ‘inhibitors’ of EU social regulation. On the one hand, we provide evidence that joint entrepreneurship of the European Parliament (EP) and the European Commission is a primary driver and argue for acknowledging the role of the EP as a key entrepreneur of ‘Social Europe’. On the other hand, divisions in the Council, underpinned by domestic politics, hinder ambitious social policy regulation at EU level in several respects. Furthermore, we tease out the role of politicization and theorize its ambivalent role as both a driver and inhibitor, depending on contingent party political orientations, contextual factors, but also the role played by Council presidencies, so far overlooked in the literature. We conclude that the drivers and inhibitors we identify, and the resulting dynamics of compromise, are relevant beyond the case of platform work. While stressing the crucial, yet ambivalent, role of politicization, our findings cast a shadow on what has recently been described as a great come back of ‘Social Europe’ with the European Pillar of Social Rights." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digitalisierung der Arbeitswelt - Fluch und Segen zugleich (2026)
Franke, Andreas; Hildt, Elisabeth;Zitatform
Franke, Andreas & Elisabeth Hildt (2026): Digitalisierung der Arbeitswelt - Fluch und Segen zugleich. In: IAB-Forum H. 16.03.2026. DOI:10.48720/IAB.FOO.20260316.01
Abstract
"Die Arbeitswelt unterliegt seit einigen Jahren einer rasanten Digitalisierung. Damit sind sowohl Chancen als auch Risiken für die psychische Gesundheit der Beschäftigten verbunden. Zudem ergeben sich daraus handfeste ethische Implikationen. So droht nicht zuletzt ein Gerechtigkeitsproblem, weil bestimmte Gruppen von Beschäftigten eher Gefahr laufen als andere, durch die Digitalisierung Nachteile zu erfahren und mit der digitalen Entwicklung nicht mehr Schritt halten zu können." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Retirement decisions in the age of COVID-19 pandemic: are older employees in digital occupations working longer? (2026)
Zitatform
Gallo, Giovanni & Amparo Nagore García (2026): Retirement decisions in the age of COVID-19 pandemic: are older employees in digital occupations working longer? In: Review of Economics of the Household, S. 1-34. DOI:10.1007/s11150-025-09827-9
Abstract
"This paper investigates the retirement response to the pandemic and to the resulting acceleration in the adoption of new technologies. Using the European Union Statistics of Income and Living Conditions datasets and leveraging the natural experiment of many workers being forced to work from home in Europe during the lockdown, we compare the retirement response of older workers in digital occupations (i.e. more exposed to the accelerated adoption of new technologies) versus non-digital occupations to detect any differences in retirement behaviour, which we interpret as digitalization effects. In addition, we analyze changes in retirement decisions by gender and geographic area. We find that retirement rates increased during COVID-19 in Europe, especially in Mediterranean countries and among women. This trend may be linked to gender occupational segregation. In Mediterranean countries, digitalization increases female retirement, likely due to challenges in balancing digital work and family responsibilities while working from home. In Eastern countries, and to a lesser extent in Northern countries, digitalization leads to postponing retirement among women, likely due to greater gender equality in unpaid work. In contrast, the retirement age for men is less affected by the pandemic with no significant differences between digital and non-digital occupations. This may exacerbate the existing gender gap in labor force participation and pension outcomes." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
Labour productivity gains or offshoring? Implications for post-growth proposals on the future of work (2026)
Zitatform
Godé, Lukas, Simon Mair & Erik Gómez-Baggethun (2026): Labour productivity gains or offshoring? Implications for post-growth proposals on the future of work. In: Ecological economics, Jg. 239. DOI:10.1016/j.ecolecon.2025.108778
Abstract
"Two visions prevail about the future of work in sustainable post-growth economies. According to the first, labour productivity gains resulting from technological development will enable to work less. The second contends instead that such gains are not always desirable and could be constrained by a shift towards less polluting production, potentially resulting in more work. Yet, conventional measures of labour productivity on which these proposals are based can conceal a displacement of labour requirements abroad. In this paper, we conduct a case study on Germany in 1995 –2020 to assess whether and to which extent labour productivity gainsresult from offshoring, and implications for post-growth proposals on the future of work. We first retrieve global labour requirements of German production across upstream supply chains. We then decompose conventional labour productivity gains to evaluate whether they result from a reduction in global labour requirements or of their increased displacement towards upstream sectors. Finally, we examine possible impacts on labour offshoring of shifting production to sectors with low productivity gains. We use a socially extended Multi-Regional Input-Output model based on OECD data. Our results show that a quarter of the global labour requirements for German production is provided abroad. This share increased until 2007 before it stabilized or decreased. We identify some potential for working time reduction without increases in labour offshoring. Shifting to service sectors could furthermore reduce labour offshoring relative to production. Yet critically, German production may cover only a fraction of domestic consumption. Related implications for post-growth proposals require further attention." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Generative AI and Career Choices (2026)
Zitatform
Gschwendt, Christian, Martina Viarengo & Thea S. Zoellner (2026): Generative AI and Career Choices. (Working paper / Swiss Leading House 251), Zürich, 52 S.
Abstract
"The economic impact of technological change will critically depend on how future workers invest in their human capital. Yet, little is known about how future workers themselves evaluate and choose their educational and occupational paths in light of emerging technologies. This paper examines how adolescents currently at the school-to-work transition stage value working with generative artificial intelligence (GenAI) in their future occupations, and how automation risk and opportunities for continuing education shape these preferences. We field a discrete-choice experiment among a nationally representative sample of over 7,000 Swiss adolescents aged around 15. We find that adolescents generally exhibit an aversion to collaborating with GenAI at work, with females consistently more averse than males. However, preferences are nuanced: adolescents welcome greater GenAI collaboration, provided that GenAI usage levels remain moderate and that it is not accompanied by increases in job-automation risk. Finally, continuing education opportunities in occupations improve attitudes towards working with GenAI across genders. Our results challenge simple narratives of technology acceptance or rejection, revealing that adolescents' willingness to work with GenAI depends on how it is implemented — its intensity, associated displacement risks, and accompanying skill development - rather than the technology itself. Our findings suggest that the way future workers value GenAI collaboration in their career choices critically depends on its intensity and on the interplay with automation risk and AI-related educational opportunities." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The impact of AI on global knowledge work (2026)
Ide, Enrique; Talamas, Eduard;Zitatform
Ide, Enrique & Eduard Talamas (2026): The impact of AI on global knowledge work. In: Journal of monetary economics, Jg. 157. DOI:10.1016/j.jmoneco.2025.103876
Abstract
"We analyze how Artificial Intelligence (AI) reshapes global knowledge work in a two-region world where firms organize production hierarchically to use knowledge efficiently: the most knowledgeable individuals specialize in problem-solving, while others perform routine work. Before AI, the Advanced Economy specializes in problem-solving services, whereas the Emerging Economy focuses on routine work. AI converts compute — which is located in the Advanced Economy — into autonomous “AI agents” that perfectly substitute for humans with a given level of knowledge. Basic AI reduces the Advanced Economy ’s net exports of problem-solving services, potentially reversing pre-AI trade patterns. In contrast, sophisticated AI expands these exports, reinforcing existing trade patterns. Finally, we show that a global ban on AI autonomy redistributes AI’s gains toward lower-skilled workers, while a regional ban — such as prohibiting autonomy only in the Emerging Economy — offers little benefit to lower-skilled workers and harms the most knowledgeable individuals in that region." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Online platforms' organizational resources and gig workers' self-leadership (2026)
Ihl, Andreas; Mayer, Anne-Sophie;Zitatform
Ihl, Andreas & Anne-Sophie Mayer (2026): Online platforms' organizational resources and gig workers' self-leadership. In: Journal of vocational behavior, Jg. 166. DOI:10.1016/j.jvb.2026.104214
Abstract
"An increasing number of gig workers turn to online gig work platforms to pursue potentially boundaryless and protean careers outside traditional organizational settings. Proactive career self-management and related self-leadership are essential to succeed in such careers. However, while traditional organizations facilitate self-leadership by providing traditional organizational resources, such as supportive human resource practices, gig work lacks these important resources. As a result, cultivating self-leadership among gig workers remains a considerable challenge. This study addresses this challenge by investigating how online platforms that centrally shape work environments may provide a resource-related context that facilitates gig workers' self-leadership strategies. Using a contextual and systemic approach to career self-management and inspired by the conservation of resources theory, we draw on insights from a 14-month field study of an online gig work platform, involving data collected from multiple sources. The findings show how platforms offer various types of platform-embedded resources and how workers utilize these resources to engage in behavior- and cognitive-focused self-leadership strategies. This study thereby contributes to the literature on careers in gig work by theorizing the role of online platforms in shaping gig workers' careers from a proactive and agentic perspective." (Author's abstract, IAB-Doku, © 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.) ((en))
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Literaturhinweis
Automation and the risk of labor market exclusion across Europe (2026)
Zitatform
Lamperti, Fabio & Davide Castellani (2026): Automation and the risk of labor market exclusion across Europe. In: Structural Change and Economic Dynamics, Jg. 77, S. 62-76. DOI:10.1016/j.strueco.2025.12.014
Abstract
"Labor market exclusion represents a major concern in several European economies, particularly affecting highly exposed demographic groups. This paper examines the potential effect of automation technologies on the risk of being locked into protracted unemployment or inactivity, using Labour Force Survey data for the European Union 27 countries and the United Kingdom, between 2009 and 2019. Our study employs repeated cross-sections of individual-level data to compute probabilities of exclusion outcomes due to automation adoption, controlling for several individual, macroeconomic, and region-specific characteristics, and for potential selection mechanisms. Findings highlight that, on average, the adoption of new automation technologies is associated with a higher probability of being inactive. This is consistent with the view that automation may exacerbate job insecurity, psychological discouragement, and detachment from job-seeking. This relationship is heterogeneous across demographic groups, with younger individuals being relatively more affected." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Good Jobs or Bad Jobs? Immigrant Workers in the Gig Economy (2026)
Zitatform
Liu, Cathy Yang & Rory Renzy (2026): Good Jobs or Bad Jobs? Immigrant Workers in the Gig Economy. In: International migration review, Jg. 60, H. 1, S. 114-138. DOI:10.1177/01979183241309585
Abstract
"New work arrangements enabled by online platforms, or gig work, saw substantive growth during the COVID-19 pandemic. Various estimates have suggested the wide participation of workers in the gig economy, with minority and immigrant workers well represented. The quality of work is a multi-dimensional concept that goes beyond earnings. One framework of good jobs and bad jobs centers on control over work schedule, content and duration, stability, safety, benefits and insurance, as well as career advancement opportunities. Using a newly released national survey focused on entrepreneurs and workers in the United States, we find that about 18.5 percent immigrant workers and 21.1 percent native-born workers participated in the gig economy as their primary or secondary job. In terms of job quality, immigrant gig workers work shorter hours and have significantly less fringe benefits than non-gig workers as well as U.S.-born gig workers, reflecting a double disadvantage. However, they tend to have higher entrepreneurial aspirations, suggesting the transient nature of gig arrangements and potential for career advancements. This paper provides a comprehensive analysis of the characteristics and implication of immigrants’ engagement with the gig economy and offers policy and theoretical discussions." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The Enshittification of Work: Platform Decay and Labour Conditions in the Gig Economy (2026)
Zitatform
Maffie, Michael David & Hector Hurtado (2026): The Enshittification of Work: Platform Decay and Labour Conditions in the Gig Economy. In: BJIR, Jg. 64, H. 1, S. 5-20. DOI:10.1111/bjir.70004
Abstract
"This study investigates the mechanisms by which gig platforms degrade labor conditions over time, building on the concept of platform decay, or ‘enshittification’, initially developed in the context of social media platforms. In this article, we draw on 30 interviews with long-term gig workers in the ride-hail and grocery delivery sectors, offering insights into how these companies shift from offering attractive working conditions to exploiting labor as these services develop market power via network effects. We identify three mechanisms through which gig companies claw back value from workers over time: burden shifting (transferring operational costs to workers), feature addition and alteration (increasing the demands on workers), and market manipulation (reducing worker bargaining power). We then explore how workers respond to platform decay, finding that workers adopt three responses: effort recalibration , multi-homing and navigating the changing conditions through what we term toxic resilience . This study contributes to the gig work literature by developing a framework to explain how working conditions in the gig economy improve or degrade over time. In doing so, this article provides a framework for organizing the growing constellation of labour research on gig workers." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))
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Literaturhinweis
Improving the effects of industrial robot adoption on employment, total factor productivity, and real wages in 52 world economies and OECD members (2026)
Zitatform
Matsuki, Takashi (2026): Improving the effects of industrial robot adoption on employment, total factor productivity, and real wages in 52 world economies and OECD members. In: Review of world economics, S. 1-32. DOI:10.1007/s10290-025-00626-z
Abstract
"This study investigates the effects of industrial robot adoption in the production process on unemployment rate, employment ratio in manufacturing, and total factor productivity (TFP) growth in 52 countries, and real wage growth in 31 and 20 OECD member countries for 2007–2019. The operating stock of robots per employee significantly impacts these variables; robot adoption lowers the unemployment rate and raises TFP and real wage growth. However, it reduces the employment ratio in manufacturing. In addition, the slight but significant positive contribution of robot adoption is observed only in the 90-percentile (top 10-percentile) of the real wage distribution. Interestingly, workers in the bottom and top tails (10- and 90-percentiles) of the wage distribution asymmetrically benefit from robotization. The industry ratio of value-added improves the labor market by reducing the unemployment rate and raising the employment ratio in manufacturing, TFP growth, and real wage growth. The information and communication technology (ICT) development also positively contributes to the employment ratio in Asia’s manufacturing, TFP growth, and real wage growth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Gender bias in machine learning: insights from official labour statistics and textual analysis (2026)
Menis–Mastromichalakis, Orfeas ; Filandrianos, George; Stamou, Giorgos ; Parsanoglou, Dimitris ; Symeonaki, Maria ; Stamatopoulou, Glykeria ;Zitatform
Menis–Mastromichalakis, Orfeas, George Filandrianos, Maria Symeonaki, Glykeria Stamatopoulou, Dimitris Parsanoglou & Giorgos Stamou (2026): Gender bias in machine learning: insights from official labour statistics and textual analysis. In: Quality & quantity, Jg. 60, H. 1, S. 619-653. DOI:10.1007/s11135-025-02261-0
Abstract
"The interplay between technology and societal norms often reveals a troubling reality: machine learning systems not only reflect existing gender stereotypes but can also amplify and entrench them, making these biases harder to detect and address. This paper adopts an interdisciplinary approach, combining quantitative and qualitative methods with recent technological advancements, such as machine learning techniques for textual analysis and computational linguistics, to offer a new framework for understanding occupational gender bias in machine learning. The study is motivated by persistent gender inequalities in the labor market and rising concerns about gendered algorithmic bias, as outlined in the European Commission’s Gender Equality Strategy 2020–2025. Focusing on language translation technologies, the research explores how machine learning may perpetuate or amplify gender stereotypes, aiming to foster more inclusive digital systems aligned with EU strategic goals. More specifically, it investigates occupational gender segregation and its manifestations in various forms of gender bias in machine learning across English, French, and Greek. The study introduces a classification of gender biases in machine learning, providing insights into professional areas needing intervention to address gender imbalances and identifying enduring stereotypical representations in textual data. To support this, statistical analysis is conducted to explore gender variations in occupations over the past thirteen years, using official data and international classifications such as the International Standard Classification of Occupations (ISCO-08). Moreover, gendered occupational distributions are extracted from 200,920 text instances in the three languages, revealing significant discrepancies between official labour statistics and the training data." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial Intelligence and Productivity in Europe (2026)
Misch, Florian; Park, Ben; Sher, Galen; Pizzinelli, Carlo;Zitatform
Misch, Florian, Ben Park, Carlo Pizzinelli & Galen Sher (2026): Artificial Intelligence and Productivity in Europe. (CESifo working paper 12401), München, 37 S.
Abstract
"The discussion on Artificial Intelligence (AI) often centers around its impact on productivity, but macroeconomic evidence for Europe remains scarce. Using the Acemoglu (2024) approach we simulate the medium-term impact of AI adoption on total factor productivity for 31 European countries. We compile many scenarios by pooling evidence on which tasks will be automatable in the near term, using reduced-form regressions to predict AI adoption across Europe, and considering relevant regulation that restricts AI use heterogeneously across tasks, occupations and sectors. We find that the medium-term productivity gains for Europe as a whole are likely to be modest, at around 1 percent cumulatively over five years. While economically still moderate, these gains are still larger than estimates by Acemoglu (2024) for the US. They vary widely across scenarios and countries and are substantially larger in countries with higher incomes. Furthermore, we show that national and EU regulations around occupation-level requirements, AI safety, and data privacy combined could reduce Europe's productivity gains by over 30 percent if AI exposure were 50 percent lower in tasks, occupations and sectors affected by regulation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Machine learning for labor market matching (2026)
Zitatform
Mühlbauer, Sabrina & Enzo Weber (2026): Machine learning for labor market matching. In: Machine learning with applications, Jg. 23, 2026-02-03. DOI:10.1016/j.mlwa.2026.100861
Abstract
"This paper develops a large-scale machine learning framework to improve labor market matching using rich administrative data. Matching is defined as a job seeker entering employment in a specific occupational field. We exploit comprehensive employment biographies from Germany, covering individual characteristics and job-related information, to estimate employment probabilities across occupations and generate personalized job recommendations. The contribution lies in demonstrating why machine learning methods are particularly well suited for administrative labor market data and outperform traditional statistical approaches. We compare logit, ordinary least squares (OLS), k-nearest neighbors, and random forest (RF). RF consistently achieves the highest predictive performance. Its advantage is rooted in key methodological properties: RF builds an ensemble of decision trees trained on bootstrap samples, introduces random feature selection at each split, and aggregates predictions through majority voting. This enables RF to capture nonlinear relationships and complex interactions, remain robust in high-dimensional settings, and reduce overfitting — features that are particularly relevant for heterogeneous and imbalanced administrative data. Compared to conventional models, RF better exploits the full informational content of employment histories, especially when estimating on all employment spells rather than restricting the sample to unemployment-to-employment transitions. The sample comprises approximately 55 million spells, representing about 6 percent of the German workforce from 2012 to 2018. Our results suggest that ML-based matching, relative to standard statistical approaches, could hypothetically reduce the unemployment rate by up to 0.3 percentage points, highlighting the practical relevance of RF-based decision support for labor market policy." (Author's abstract, IAB-Doku, © Elsevier) ((en))
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Literaturhinweis
How local labour market skill relatedness and size moderate the impacts of automation (2026)
Zitatform
Njekwa Ryberg, Peter (2026): How local labour market skill relatedness and size moderate the impacts of automation. In: Regional Studies, Jg. 60, H. 1. DOI:10.1080/00343404.2025.2598031
Abstract
"This paper examines how local labour market skill relatedness and size moderate the impacts of automation on occupations across Swedish local labour markets. Using administrative data and a spatially explicit risk of automation measure that accounts for regional differences in occupational task contents, it finds a negative association between automation and employment growth and wage income growth for non-metropolitan occupations between 2011 and 2021. Skill relatedness and labour market size mitigate these negative relationships. In contrast, no negative associations are found for metropolitan occupations. Due to their higher shares of non-automatable tasks, they are more resilient to adverse automation effects." (Author's abstract, IAB-Doku) ((en))
Aspekt auswählen:
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
- Qualifikationsanforderungen und Berufe
- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
- Arbeits- und sozialrechtliche Aspekte / digitale soziale Sicherung
- Deutschland
- Andere Länder/ internationaler Vergleich
- Besondere Personengruppen