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Autor, David & Neil Thompson (2025): Expertise. In: Journal of the European Economic Association, Jg. 23, H. 4, S. 1203-1271. DOI:10.1093/jeea/jvaf023

Abstract

"When job tasks are automated, does this augment or diminish the value of labor in the tasks that remain? We argue the answer depends on whether removing tasks raises or reduces the expertise required for remaining non-automated tasks. Since the same task may be relatively expert in one occupation and inexpert in another, automation can simultaneously replace experts in some occupations while augmenting expertise in others. We propose a conceptual model of occupational task bundling that predicts that changing occupational expertise requirements have countervailing wage and employment effects: automation that decreases expertise requirements reduces wages but permits the entry of less expert workers; automation that raises requirements raises wages but reduces the set of qualified workers. We develop a novel, content-agnostic method for measuring job task expertise, and we use it to quantify changes in occupational expertise demands over four decades attributable to job task removal and addition. We document that automation has raised wages and reduced employment in occupations where it eliminated inexpert tasks, but lowered wages and increased employment in occupations where it eliminated expert tasks. These effects are distinct from—and in the case of employment,opposite to—the effects of changing task quantities. The expertise framework resolves the puzzle of why routine task automation has lowered employment but often raised wages in routine task-intensive occupations. It provides a general tool for analyzing how task automation and new task creation reshape the scarcity value of human expertise within and across occupations." (Author's abstract, IAB-Doku) ((en))

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Battisti, Michele, Massimo Del Gatto, Antonio Francesco Gravina & Christopher F. Parmeter (2025): Robotic capital - skill complementarity. In: Macroeconomic Dynamics, Jg. 29, S. e54. DOI:10.1017/s1365100524000567

Abstract

"Relying upon an original (country-sector-year) measure of robotic capital (RK), we investigate the degree of complementarity/substitutability between robots and workers at different skill levels. We employ nonparametric methods to estimate elasticity of substitution patterns between RK and skilled/unskilled labor over the period 1995–2009. We show that: i) on average, RK exhibits less substitutability with skilled workers compared to unskilled workers, indicating a phenomenon of “RK-Skill complementarity”. This pattern holds in a global context characterized by significant heterogeneity; ii) the dynamic of “RK-Skill complementarity” has increased since the early 2000s; iii) the observed strengthening is more prominent in OECD countries, as opposed to non-OECD countries, and in the Manufacturing sector, compared to non-Manufacturing industries." (Author's abstract, IAB-Doku) ((en))

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Buzzelli, Gregorio (2025): Automation and segmentation: Downgrading employment quality among the former “insiders” of Western European labour markets. In: International Journal of Social Welfare, Jg. 34, H. 2. DOI:10.1111/ijsw.70011

Abstract

"The literature on labor market segmentation traditionally looks at servitisation as the main structural driver behind the rise of employment precariousness, overlooking another crucial engine of the knowledge-economy transition: the Information and Communication Technologies (ICT) revolution. This paper proposes a task-based approach to complement the skill-biased framework usually applied to labor market segmentation, investigating the correlation between occupational exposure to the risk of automation and low-quality employment. The empirical analysis, based on 14 countries sampled from ESS (2002–2018), shows a strong correlation between technological replaceability and low income across all of Western Europe, especially after the Great Recession, while its association with atypical employment is mainly driven by fixed-term contracts in Central and Southern Europe and by part-time arrangements in Anglo-Saxon and Scandinavian countries. Overall, a “recalibrated” dualisation emerges in Western European labor markets, characterized by the diffusion of low labor earnings and atypical contracts among mid-skill routine workers, besides the low-skill service precariat." (Author's abstract, IAB-Doku) ((en))

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Giebel, Marek & Alexander Lammers (2025): The Impact of a New Workplace Technology on Employees. In: Oxford Bulletin of Economics and Statistics, Jg. 87, H. 5, S. 1003-1024. DOI:10.1111/obes.12674

Abstract

"How does the implementation of a new technology affect workers? Using detailed worker-level data for Germany, we analyse the impact of new technologies on non-monetary working conditions such as overtime, training and perceived labor intensity. We show that the strongest effects arise in the first year of their implementation. These effects diminish after the introduction period. We further provide evidence that the impact of technology adoption varies across diverse occupational and industrial contexts. Workers in occupations with a higher task substitution potential show stronger increases in overtime, training measures and labor intensity. Analyzing industry characteristics, we find that employees exposed to a new technology react more strongly in industries with higher business dynamics in terms of organisational capital and R&D investment. Extending these considerations to information and communication technology (ICT) usage, we show that new technologies exert stronger effects in industries with high investment in ICT equipment or low investment in software." (Author's abstract, IAB-Doku) ((en))

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Guarascio, Dario, Alessandro Piccirillo & Jelena Reljic (2025): Robots vs. Workers: Evidence From a Meta‐Analysis. In: Journal of Economic Surveys, Jg. 39, H. 5, S. 2254-2271. DOI:10.1111/joes.12699

Abstract

"This study conducts a meta-analysis to assess the effects of robotization on employment and wages, synthesizing the evidence from 33 studies (644 estimates) on employment and a subset of 19 studies (195 estimates) on wages. The results challenge the alarmist narrative about the risk of widespread technological unemployment, suggesting that the overall relationship between robotization and employment or wages is minimal. However, the effects are far from uniform, with adverse outcomes observed in specific contexts, such as the United States, manufacturing sectors, and middle-skilled occupations. The analysis also identifies a publication bias favoring negative wage effects, though correcting for this bias confirms the negligible impact of robotization." (Author's abstract, IAB-Doku) ((en))

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Kuhn, Sarah & Holger Seibert (2025): Digitalisierung der Arbeitswelt: Durch künstliche Intelligenz sind inzwischen auch viele Expertentätigkeiten ersetzbar. (IAB-Regional. Berichte und Analysen aus dem Regionalen Forschungsnetz. IAB Berlin-Brandenburg 01/2025), 34 S. DOI:10.48720/IAB.REBB.2501

Abstract

"Durch neue digitale Technologien verändert sich der deutsche Arbeitsmarkt. Dies gilt besonders für das Ausmaß, in dem Berufe aktuell potenziell durch den Einsatz von Computern oder computergesteuerten Maschinen ersetzbar sind, dem so genannten Substituierbarkeitspotenzial. Es beschreibt, welcher Anteil an Tätigkeiten in einem Beruf schon heute durch den Einsatz moderner Technologien ersetzt werden könnte. Nach wie vor ist zwar das Substituierbarkeitspotenzial bei den Helfer*innen- und Fachkraftberufen am höchsten. Am stärksten gestiegen ist das Potenzial jedoch bei den Expert*innenberufen (u. a. durch generative Künstliche Intelligenz). Besonders bei den IT- und naturwissenschaftlichen Dienstleistungsberufen sind hohe Zuwachsraten zwischen 2019 und 2022 zu verzeichnen. Der vorliegende Beitrag fokussiert sich auf den Arbeitsmarkt in Brandenburg und Berlin. Wichtig zu betonen ist, dass es hier um Potenziale technischer Ersetzbarkeit geht. Ob und inwiefern die technischen Möglichkeiten auch tatsächlich umgesetzt werden, steht nicht fest. Es kann Gründe geben, die gegen eine tatsächliche Substituierung sprechen, beispielsweise weil eine Umstellung zu komplex wäre oder ethische Bedenken dem entgegenstehen. Unstrittig ist jedoch, dass auf der einen Seite einige Tätigkeiten durch die Digitalisierung wegfallen bzw. automatisiert werden, andererseits aber auch neue Tätigkeiten und Berufe entstehen. Daher kann ein hohes Substituierungspotenzial als Indikator für einen Wandel der Arbeitswelt gesehen werden." (Autorenreferat, IAB-Doku)

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Lábaj, Martin, Tomáš Oleš & Gabriel Procházka (2025): Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK. In: Eurasian business review, S. 1-49. DOI:10.1007/s40821-025-00314-w

Abstract

"Over the past four decades, automation technologies have replaced routine tasks performed by medium-skilled workers, and contributed to increased labor market polarization. With the advent of artificial intelligence, this dynamic may have shifted, extending task substitution to non-routine tasks performed by high-skilled workers. Using textual analysis and descriptions of technology found in patent texts, we construct novel occupational exposures to robot and artificial intelligence technologies. These occupational exposures are then used to analyze changes in labor and skill demand over the last decade in the United Kingdom. We find that the middle part of the income distribution is primarily exposed to robot technology, while exposure to artificial intelligence increases monotonically across income percentiles. Second, we find that exposure to robots is strongest among high school dropouts and declines monotonically with education, while artificial intelligence automation has a limited impact on the same workers, with a pronounced exposure among college graduates. Third, our findings suggest asymmetric effects of automation technologies across skill groups. Robot automation reduces demand for low-skilled workers, while AI technology shifts demand away from high-skilled workers, with the direct effects consistently negative despite the presence of several compensating mechanisms. Fourth, despite significant effects on wage bill, we find no robust relationship between automation exposure and changes in the employment-to-population ratio. Finally, a joint estimation of the effects of robot and AI automation shows that robot automation is positively associated with an increase in demand for skilled workers, while AI automation is weakly associated with a decrease in demand for skilled workers." (Author's abstract, IAB-Doku) ((en))

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Müller, Steffen & Verena Plümpe (2025): Wie Roboter die betriebliche Beschäftigungsstruktur verändern. In: Wirtschaft im Wandel, Jg. 31, H. 1, S. 10-13. DOI:10.18717/wwfyns-ep75

Abstract

"Der Einsatz von Robotern verändert die Arbeitswelt grundlegend – doch welche spezifischen Effekte hat dies auf die Beschäftigungsstruktur? Unsere Analyse untersucht die Folgen des Robotereinsatzes anhand neuartiger Mikrodaten aus deutschen Industriebetrieben. Diese Daten verknüpfen Informationen zum Robotereinsatz mit Sozialversicherungsdaten und detaillierten Angaben zu Arbeitsaufgaben. Auf Basis eines theoretischen Modells leiten wir insbesondere positive Beschäftigungseffekte für Berufe mit wenig repetitiven, programmierbaren Aufgaben ab, sowie für jüngere Arbeitskräfte, weil diese sich besser an technologische Veränderungen anpassen können. Die empirische, mikroökonomische Analyse des Robotereinsatzes auf Betriebsebene bestätigt diese Vorhersagen: Die Beschäftigung steigt für Techniker, Ingenieure und Manager und junge Beschäftigte, während sie bei geringqualifizierten Routineberufen sowie bei Älteren stagniert. Zudem steigt die Fluktuation bei geringqualifizierten Arbeitskräften signifikant an. Unsere Ergebnisse verdeutlichen, dass der Verdrängungseffekt von Robotern berufsabhängig ist, während junge Arbeitskräfte neue Tätigkeiten übernehmen." (Autorenreferat, IAB-Doku)

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Otoiu, Adrian, Emilia Titan, Dorel Paraschiv & Daniela-Ioana Manea (2025): Job polarisation OR AND upgrading! Recent evidence from Europe. In: The Economic and Labour Relations Review, Jg. 36, H. 1, S. 257-270. DOI:10.1017/elr.2025.12

Abstract

"Based on recent evidence from Europe, the paper shows that polarization and upgrading are not mutually exclusive trends, but rather, simultaneously defined recent structural changes in employment. The results show that (a) the occupational structure shows a general shift towards high-skill jobs, (b) the prevailing upgrading patterns are often accompanied by job polarization, as the share of middle-skill jobs declines in most cases, and (c) while low-skill employment often outperforms middle-skill jobs, it has tended to decline. In addition to analysing trends for EU-27 countries with different levels of development for the latest available time periods, the article also shows that occupational upgrading patterns are rather intertwined with job polarisation and are compatible with both the Skill-Biased Technical Change (SBTC) and Routine-Biaszd Technical Change (RBTC) hypotheses. The employment dynamics of low-skill workers are uncertain, as they are not fully compatible with any theoretical model, thus pointing to the need for a finer understanding of changes in occupational structure, and the extent to which both polarization and upgrading are shaping the evolution of the labor force structure under the impact of (ongoing) technological change." (Author's abstract, IAB-Doku) ((en))

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Riccio, Federico, Jacopo Staccioli & Maria Enrica Virgillito (2025): European regional employment and exposure to labour-saving technical change: results from a direct text similarity measure. (LEM working paper series / Laboratory of Economics and Management 2025/19), Pisa, 34 S. DOI:10.57838/sssa/02jp-b197

Abstract

"Does labor-saving technological change pose a threat to European employment, and if so, to what extent? This study investigates the degree of employment exposure to labor-saving technological change across NUTS-2 regions in Europe. We construct a cross-walked metric between the SOC and ISCO classification systems to adapt the direct measure of occupational exposure developed by Montobbio et al. (2024) for the US economy and apply it to the European context. This methodology enables us to generate detailed insights into the exposure of European occupations by leveraging the similarity rankings between technological classifications in the USPTO (CPCs) and task descriptions. To evaluate the transmission from occupational exposure to employment outcomes, we utilise data from the European Structure of Earnings Survey (EU-SES), thereby constructing exposure indices at both sectoral and regional levels. Finally, we examine the industrial and geographical diffusion of labor-saving technological change in recent years and provide robust econometric evidence indicating that low-wage regions, as well as deindustrialising areas heavily integrated into global value chains, are disproportionately vulnerable to the threat of substitution." (Author's abstract, IAB-Doku) ((en))

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Vodă, Adina-Maria, Mihai Ciobotea, Doina Badea, Monica Roman & Marian Stan (2025): The Interactions Between Digitalization, Innovation and Employment in European Companies: Insights from a Latent Class Analysis. In: Economies, Jg. 13, H. 4. DOI:10.3390/economies13040104

Abstract

"There is increasing concern regarding the association between technological change and jobs. This study explores how different patterns of digitalization and innovation relate to job creation in European companies. We use data from the European Company Survey 2019 collected by Eurofound and Cedefop. We apply Latent Class Analysis (LCA) to identify the typologies of companies, mainly based on their level of technology adoption, innovation practices and employment patterns. We showcase four distinct classes of companies: moderate adoption of digital technology and strong international orientation, traditional and local, medium digitalization, process innovative with local focus and digital leaders and innovators, with specific patterns regarding digitalization, innovation and job creation. The digital leaders and innovators class revealed a high level of digitalization and innovation and maintained stable employment levels, with increased investments in staff training and tendency towards automation. Conversely, less-digitalized traditional companies are more susceptible to stagnation or employment decline. In general, the employment outlook is stable, without significant employment growth, signaling the need for balanced investments in innovation and digitalization that stimulate more and better jobs. This is the first study to apply LCA to explore complex relationships between digitalization, innovation, foreign trade, training investments and employment trends and offers fresh insights into company views towards employment in the digital era." (Author's abstract, IAB-Doku) ((en))

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Wang, Ping & Tsz-Nga Wong (2025): Artificial Intelligence and Technological Unemployment. (NBER working paper / National Bureau of Economic Research 33867), Cambridge, Mass, 53 S.

Abstract

"How large is the impact of artificial intelligence (AI) on labor productivity and unemployment? This paper introduces a labor-search model of technological unemployment, conceptualizing the generative aspect of AI as a learning-by-using technology. AI capability improves through machine learning from workers and in turn enhances their labor productivity, but eventually displaces workers if wage renegotiation fails. Three distinct equilibria emerge: no AI, some AI with higher unemployment, or unbounded AI with sustained endogenous growth and little impact on employment. By calibrating to the U.S. data, our model predicts more than threefold improvements in productivity in some-AI steady state, alongside a long-run employment loss of 23%, with half this loss occurring over the initial five-year transition. Plausible change in parameter values could lead to global and local indeterminacy. The mechanism highlights the considerable uncertainty of AI's impacts in the presence of labor-market frictions. In the unbounded-AI equilibrium, technological unemployment would not occur. We further show that equilibria are inefficient despite adherence to the Hosios condition. By improving job-finding rate and labor productivity, the optimal subsidy to jobs facing the replacement risk of AI can generate a welfare gain from 26.6% in the short run to over 50% in the long run." (Author's abstract, IAB-Doku) ((en))

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Yuan, Bocong, Jiannan Li & Hairong Zhao (2025): Education pathways to mitigate automation anxiety: skill development as key for job satisfaction in the age of machines replacing human. In: International Journal of Manpower, Jg. 46, H. 9, S. 1676-1698. DOI:10.1108/ijm-02-2024-0093

Abstract

"Purpose: The application of intelligent machine in the workplace has led to increasing concern about technically induced unemployment. This study is to investigate the mechanism of how such risk affects the job satisfaction. Design/methodology/approach: We use the secondary data from SHARE (wave 8) and a longitudinal survey to examine the influence mechanism of how intelligent machine job substitution risk affects job satisfaction. Findings: Results show that intelligent machine job substitution risk has a negative impact on job satisfaction. Besides, skill development opportunity mediates the negative relation between intelligent machine job substitution risk and job satisfaction. Further, work support buffers the negative relation between intelligent machine job substitution risk and skill development opportunity, while enhancing the positive relation between skill development opportunity and job satisfaction. Originality/value: This study is the first to examine the mediation role of skill development opportunity in the relation between the intelligent machine job substitution risk and job satisfaction. Also, this study is the first to explore the role of work support in the above relation. This study enriches relevant research regarding the intelligent machine application in workplace and provides important insights for organization management." (Author's abstract, IAB-Doku, © Emerald Group) ((en))

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Zou, Wei, Liming Zheng & Ruiqi Ma (2025): Can inequality and intergenerational upward mobility coexist: the impact of skill-biased technological change. In: Applied Economics Letters, S. 1-8. DOI:10.1080/13504851.2025.2550571

Abstract

"We extend the Maoz and Moav (1999) model by introducing a CES production function to examine the impact of skill-biased technological change (SBTC) on inequality and intergenerational upward mobility. Our study shows that (1) when the production function shifts from a Cobb-Douglas form to a CES form, high-skilled workers rapidly converge to a unique steady state; (2) while SBTC exacerbates inequality, it raises the steady-state number of high-skilled workers, establishing a positive correlation between inequality and intergenerational upward mobility." (Author's abstract, IAB-Doku) ((en))

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ten Berge, Jannes & Fabian Dekker (2025): New technology and workers’ perceived impact on job quality: Does labor organization matter? In: Economic and Industrial Democracy, Jg. 46, H. 2, S. 619-654. DOI:10.1177/0143831x241265911

Abstract

"There is an emerging literature focusing on the impact of technological change on work quality. This study contributes to the literature by examining (1) workers’ expectations regarding the effect of technological change on perceived job insecurity, as well as physical and psychological job demands, and (2) how these expectations are shaped by the degree of labor organization within countries. The article uses cross-national data for 25 OECD countries. It is found that labor organization decreases perceived levels of job insecurity related to technological change, but also lowers workers’ expectations of technology improving the quality of their work. These findings may indicate that in environments where technological change is less strongly moderated by organized labor, workers put greater emphasis on technology as a driver of (short-term) work changes. Alternatively, these findings may signal a lack of ‘worker power’ of organized labor to enforce technologies that improve the quality of employment." (Author's abstract, IAB-Doku) ((en))

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Benítez, Miguel & Eric Parrado (2024): Mirror, Mirror on the Wall: Which Jobs Will AI Replace After All?: A New Index of Occupational Exposure. (Working papers / Inter-American Development Bank 13696), Washington, DC, 33 S. DOI:10.1823

Abstract

"This paper introduces the AI Generated Index of Occupational Exposure (GENOE), a novel measure quantifying the potential impact of artificial intelligence on occupations and their associated tasks. Our methodology employs synthetic AI surveys, leveraging large language models to conduct expert-like assessments. This approach allows for a more comprehensive evaluation of job replacement likelihood, minimizing human bias and reducing assumptions about the mechanisms through which AI innovations could replace job tasks and skills. The index not only considers task automation, but also contextual factors such as social and ethical considerations and regulatory constraints that may affect the likelihood of replacement. Our findings indicate that the average likelihood of job replacement is estimated at 0.28 in the next year, increasing to 0.38 and 0.44 over the next five and ten years, respectively. To validate our methodology, we successfully replicate other measures of occupational exposure that rely on human expert assessments, substituting these with AI-based evaluations. The GENOE index provides valuable insights for policymakers, employers, and workers, offering a data-driven foundation for strategic workforce planning and adaptation in the face of rapid technological change." (Author's abstract, IAB-Doku) ((en))

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Bockelmann, Carsten, Damian Dudek, Andreas Haja, Alexander Hanuschkin, Cosima Klischat, Sebastian Lehnhoff, Mathias Magdowski, Britta Matthes, Gerhard Rigoll, Michael Schanz, Hoai My Van, Dirk Wübben & Niclas Zeller (2024): Rolle der Künstlichen Intelligenz in der Elektro- und Informationstechnik. VDE „Studium, Beruf und Gesellschaft“. 43 S.

Abstract

"Dieses Papier zeigt, wo bereits heute in den verschiedenen Fachgebieten der Elektro- und Informationstechnik die Künstliche Intelligenz eine wichtige und insbesondere selbstverständliche Rolle spielt. Dabei besteht eine wechselseitige Beziehung: KI ist nicht nur Mittel zum Zweck – mächtiges Werkzeug zum Lösen elektrotechnischer Aufgabenstellungen sowie Helferlein im Arbeitsalltag – sondern auch Gegenstand der elektrotechnischen Forschung bzw. wird durch elektrotechnische Verfahren z.B. in der Nachrichtentechnik unterstützt. An vielen Stellen kommt die KI (noch) an ihre Grenzen. Wir zeigen, wo diese liegen und geben Ausblicke. Einen weiteren Schwerpunkt bildet die Auseinandersetzung mit dem Thema „KI in der elektrotechnischen Lehre“ sowie die Nutzung von Large Language Models im Studium und beim wissenschaftlichen Arbeiten. Wir lernen außerdem den Unterschied zwischen Data Scientist und Elektroingenieur in der Nachrichtentechnik kennen. Auch die Frage „Wird die KI Elektroingenieurinnen und Elektroingenieure ersetzen?“ klären wir hier mit Hilfe einer einschlägigen Berufsforscherin auf." (Autorenreferat, IAB-Doku)

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Bonfiglioli, Alessandra, Rosario Crinò, Harald Fadinger & Gino Gancia (2024): Robot Imports and Firm-Level Outcomes. In: The Economic Journal, Jg. 134, H. 664, S. 3428-3444. DOI:10.1093/ej/ueae055

Abstract

"We use French data over the 1994-2013 period to study how imports of industrial robots affect firm-level outcomes. Guided by a simple model, we develop a novel empirical strategy to identify the causal effects of robot adoption. Our results suggest that, while demand shocks generate a positive correlation between robot imports and employment at the firm level, exogenous exposure to automation leads to job losses. We also find that robot exposure increases labor productivity and some evidence that it may raise the relative demand for high-skill professions." (Author's abstract, IAB-Doku) ((en))

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Burkert, Carola, Annette Röhrig & Daniel Jahn (2024): Digitalisierung der Arbeitswelt: Mögliche Auswirkungen auf den Arbeitsmarkt in Hessen – Aktualisierung 2022. (IAB-Regional. Berichte und Analysen aus dem Regionalen Forschungsnetz. IAB Hessen 02/2024), Nürnberg, 26 S. DOI:10.48720/IAB.REH.2402

Abstract

"Der Einsatz von neuen digitalen Technologien wird die Arbeitswelt verändern, und auch – oder gerade – Hochqualifizierte werden betroffen sein. Das Substituierbarkeitspotenzial gibt an, in welchem Ausmaß Berufe gegenwärtig potenziell durch den Einsatz von Computern oder computergesteuerten Maschinen ersetzbar sind. Es entspricht dem Anteil an Tätigkeiten in einem Beruf, die schon heute durch den Einsatz moderner Technologien ersetzt werden könnten. Die vorliegende Studie zeigt, wie sehr sich die Arbeitswelt bereits verändert hat. Allerdings ist zu betonen, dass die Studie das technisch Mögliche der Ersetzbarkeit des Menschen durch die Maschine untersucht. Ob dies am Ende wirklich so eintrifft, steht nicht fest. Sicher ist aber: Für Unternehmen und Beschäftigte wird vor allem die permanente Weiterqualifizierung bzw. lebenslanges Lernen noch mehr an Gewicht gewinnen. In diesem IAB-Regional präsentieren wir die neuen Werte des Substituierbarkeitspotenzials 2022 für Hessen anhand der Anforderungsniveaus und der Berufssegmente und stellen teilweise auch die Entwicklung von 2013 bis 2022 dar. Weiterhin betrachten wir die Betroffenheit von Auswirkungen des Einsatzes neuer Technologien in Hessen, indem wir die Anteile sozialversicherungspflichtig Beschäftigter in Berufen mit niedrigem, mittlerem und hohem Substituierbarkeitspotenzial analysieren und untersuchen den Zusammenhang zwischen Substituierbarkeitspotenzialen und Beschäftigungsentwicklung." (Autorenreferat, IAB-Doku)

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Burzyński, Michał (2024): Spatial and Occupational Mobility of Workers Due to Automation. (LISER working papers), Esch-sur-Alzette, 52 S.

Abstract

"Automation of labor tasks is one of the most dynamic aspects of recent technological progress. This paper aims at improving our understanding of the way that automation affects labor markets, analyzing the example of European countries. The quantitative theoretical methodology proposed in this paper allows to focus on automation-induced migration of workers, occupation switching and income inequality. The key findings include that automation in the first two decades of the 21st century had a significant impact on job upgrading of native workers and generated gains in many local labor markets. Even though net migration of workers was attenuated due to convergence in incomes across European regions, mobility at occupation levels had a sizeable impact on transmitting welfare effects of automation." (Author's abstract, IAB-Doku) ((en))

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Casey, Gregory (2024): Unemployment and the direction of technical change. In: European Economic Review, Jg. 168. DOI:10.1016/j.euroecorev.2024.104802

Abstract

"I construct and analyze a growth model in which technical change can increase unemployment. I first analyze the forces that deliver a constant steady state unemployment rate in this setting. Labor-saving technical change increases unemployment, which lowers wages and creates incentives for future investment in labor-using technologies. In the long run, this interaction generates a balanced growth path that is observationally equivalent to that of the standard neoclassical growth model, except that it also incorporates a positive steady state level of unemployment and a falling relative price of investment. I also study the effects of a permanent increase in the ability of R&D to improve labor-saving technologies. In the long run, this change leads to faster growth in output per worker and wages, but it also yields higher unemployment and a lower labor share of income. In the short run, this change exacerbates existing inefficiencies and slows economic growth." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Cattaneo, Maria Alejandra, Christian Gschwendt & Stefan C. Wolter (2024): How Scary Is the Risk of Automation? Evidence from a Large Scale Survey Experiment. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 17097), Bonn, 36 S.

Abstract

"Advances in technology have always reshaped labor markets. Automating human labor has lead to job losses and creation but most of all, for an increasing demand for highly skilled workers. However, emerging AI innovations like ChatGPT may reduce labor demand in high skilled occupations previously considered "safe" from automation. While initial studies suggest that individuals adjust their educational and career choices to mitigate automation risk, it is unknown what people would be willing to pay for a reduced automation risk. This study quantifies this value by assessing individuals' preferences for occupations in a discrete-choice experiment with almost 6'000 participants. The results show that survey respondents are willing to accept a salary reduction equivalent to almost 20 percent of the median annual gross wage to work in an occupation with a 10 percentage point lower risk of automation. Although the preferences are quite homogeneous, there are still some significant differences in willingness to pay between groups, with men, younger people, those with higher levels of education, and those with a higher risk tolerance showing a lower willingness to pay for lower automation risk." (Author's abstract, IAB-Doku) ((en))

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Chen, Xi, Xiang Wen Cai, Xu Ding, Le Song & Cheng Chen (2024): Intellectualization and substitution elasticity of capital on the labour force in logistics enterprises: evidence from China and the United States. In: Applied Economics Letters, Jg. 31, H. 5, S. 395-400. DOI:10.1080/13504851.2022.2136615

Abstract

"This paper addresses the substitution elasticity of capital on the labor force in the context of the development of intellectualization. Given the substitution of capital for labor, China's benchmark listed logistics companies are compared with an American company to discuss the evolution of capital - labor substitution. A large-scale intellectualization process began in 2017, and based on a variable elasticity of substitution, this paper creates an econometric model of substitution elasticity between capital and labor and its evolution between 2017 and 2021. The American logistics company UPS maintains a relatively high level of substitution elasticity, and Chinese logistics companies are quickly catching up. The substitution elasticity of capital on labor in Chinese enterprises trends upward year after year. In 2021, the capital - labor substitution elasticity of logistics enterprises in both countries showed considerable growth. The calculation model of substitution elasticity presented in this paper can be extended to different regions and industries to measure intelligent development levels and the relationship between capital and the labor force." (Author's abstract, IAB-Doku) ((en))

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Damelang, Andreas & Michael Otto (2024): Who is Replaced by Robots? Robotization and the Risk of Unemployment for Different Types of Workers. In: Work and occupations, Jg. 51, H. 2, S. 181-206. DOI:10.1177/07308884231162953

Abstract

"We study the effects of robotization on unemployment risk for different types of workers. We examine the extent to which robotization increases inequality at the skill level and at the occupational level using two theoretical frameworks: skill-biased technological change and task-biased technological change. Empirically, we combine worker-level data with information on actual investments in industrial robots. Zooming in on the German manufacturing industry, our multivariate results show that robotization affects different types of workers differently. We do not observe an increase in unemployment risk for low- and medium-skilled, but we find a considerably lower unemployment risk among high-skilled workers. Moreover, the unemployment risk is significantly higher in occupations with highly substitutable tasks, but only in industries that invest largely in robots." (Author's abstract, IAB-Doku, © SAGE) ((en))

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Danzer, Alexander M., Carsten Feuerbaum & Fabian Gaessler (2024): Labor supply and automation innovation: Evidence from an allocation policy. In: Journal of Public Economics, Jg. 235. DOI:10.1016/j.jpubeco.2024.105136

Abstract

"Despite a longstanding interest in the potential substitution of labor and capital, limited empirical evidence exists regarding the causal relationship between labor supply and the development of labor-saving technologies. This study examines the impact of exogenous changes in regional labor supply on automation innovation by leveraging a German immigrant allocation policy during the 1990s and 2000s. The findings reveal that an increase in the low-skilled workforce reduces automation innovation, as measured by patents. This reduction is most pronounced for large firms within the manufacturing sector and primarily concerns process-related automation innovations. This suggests that the effect is channeled through changes in internal demand for automation innovation. Consistent with a labor scarcity mechanism, the effect is confined to tight labor markets." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Dauth, Wolfgang & Michael Moritz; Katharina Grienberger, Florian Lehmer, Steffen Müller, Bernd Fitzenberger, Verena Plümpe, Oliver Falck, Anja Bauer, Anja Sonnenburg, Markus Janser, Christian Schneemann, André Diegmann, Britta Matthes & Anna Solms (sonst. bet. Pers.) (2024): Wie bewältigen Regionen die digitale und ökologische Transformation von Wirtschaft und Arbeitsmarkt? (Podium). In: IAB-Forum H. 06.05.2024. DOI:10.48720/IAB.FOO.20240506.01

Abstract

"Was bedeuten die absehbaren Transformationsprozesse der kommenden Jahrzehnte auf regionaler Ebene und wie können sie gemeistert werden? Antworten auf diese Fragen gab der IWH/IAB-Workshop zur Arbeitsmarktpolitik, der in diesem Jahr erstmals am IAB in Nürnberg stattfand." (Autorenreferat, IAB-Doku)

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Demirci, Ozge, Jonas Hannane & Xinrong Zhu (2024): Who Is AI Replacing? The Impact of Generative AI on Online Freelancing Platforms. (CESifo working paper 11276), München, 22 S.

Abstract

"This paper studies the impact of Generative AI technologies on the demand for online freelancers using a large dataset from a leading global freelancing platform. We identify the types of jobs that are more affected by Generative AI and quantify the magnitude of the heterogeneous impact. Our findings indicate a 21% decrease in the number of job posts for automation-prone jobs related to writing and coding, compared to jobs requiring manual-intensive skills, within eight months after the introduction of ChatGPT. We show that the reduction in the number of job posts increases competition among freelancers while the remaining automation-prone jobs are of greater complexity and offer higher pay. We also find that the introduction of Image-generating AI technologies led to a 17% decrease in the number of job posts related to image creation. We use Google Trends to show that the more pronounced decline in the demand for freelancers within automation-prone jobs correlates with their higher public awareness of ChatGPT’s substitutability." (Author's abstract, IAB-Doku) ((en))

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Falck, Oliver, Yuchen Guo, Christina Langer, Valentin Lindlacher & Simon Wiederhold (2024): Training, Automation, and Wages: International Worker-Level Evidence. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 17503), Bonn, 72 S.

Abstract

"Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether job training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without job training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that job training reduces workers' automation risk by 4.7 percentage points, equivalent to 10 percent of the average automation risk. The training-induced reduction in automation risk accounts for one-fifth of the wage returns to job training. Job training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Women tend to benefit more from training than men, with the advantage becoming particularly pronounced at older ages." (Author's abstract, IAB-Doku) ((en))

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Fregin, Marie-Christine, Theresa Koch, Verena Malfertheiner, Pelin Özgül & Michael Stops (2024): On the Automation of Job Tasks: Occupational exposure to Artificial Intelligence and Software. (ROA external reports / Researchcentrum voor Onderwijs en Arbeidsmarkt (Maastricht) 4 ai:conomics policybrief), Maastricht, 10 S.

Abstract

"While rapid advances in digital technologies transformed the occupational structures and workers‘ skill and task composition over the past decades, much less is known about how Artificial Intelligence technologies (AI) will shape future labour markets. As part of the “ai:conomics” project, we analyze the extent to which employees subject to social security contributions in Germany are potentially exposed to AI and software technology. Our results show that highly educated, high-income workers are most exposed to AI, while their exposure is lower to software. Overall, the findings suggest that given AI’s far-reaching potential to carry out different sets of tasks, these technologies are expected to impact workers across a wider skill and wage spectrum, which previous automation technologies had limited impact on." (Author's abstract, IAB-Doku) ((en))

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Freundl, Vera, Philipp Lergetporer, Katharina Wedel & Katharina Werner (2024): Informationsbereitstellung zur Automatisierbarkeit von Berufen erhöht Weiterbildungsbereitschaft. In: Ifo-Schnelldienst, Jg. 77, H. 3, S. 39-43.

Abstract

"Beschäftige in Deutschland unterschätzen die Automatisierbarkeit ihres Berufs. Dies gilt vor allem für Beschäftigte in Berufen mit hoher Automatisierbarkeit, wie eine neue Studie von Lergetporer et al. (2023) zeigt. Die randomisierte Bereitstellung von Informationen über die tatsächliche Automatisierbarkeit ihrer Berufe erhöht die Arbeitsmarktsorgen und die Einschätzung über Veränderungen des Arbeitsumfelds. Außerdem wird die Teilnahmebereitschaft an Weiterbildungs und Umschulungsmaßnahmen erhöht, insbesondere bei Befragten in Berufen mit hoher Automatisierbarkeit. Dadurch verringert sich der Unterschied in der Weiterbildungsbereitschaft zwischen Beschäftigten in Berufen mit hoher und niedriger Automatisierbarkeit um 95,5 %, die Lücke in der Umschulungsbereitschaft wird sogar vollständig geschlossen." (Textauszug, IAB-Doku)

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Gabriel, Stefan, Tommy Falkowski, Jannis Graunke, Roman Dumitrescu, Anike Murrenhoff, Veronika Kretzschmer & Michael ten Hompel (2024): Künstliche Intelligenz und industrielle Arbeit – Perspektiven und Gestaltungsoptionen. Expertise des Forschungsbeirats Industrie 4.0. München, 46 S. DOI:10.48669/fb40_2024-1

Abstract

"In der neuen Expertise „Künstliche Intelligenz und industrielle Arbeit“ des Forschungsbeirats Industrie 4.0 zeigen das Fraunhofer IEM und das Fraunhofer IML Gestaltungsoptionen und Handlungsfelder auf, wie KI in der deutschen Industrie erfolgreich eingesetzt werden kann. Ziel ist sowohl eine Steigerung der Wettbewerbsfähigkeit als auch eine Aufwertung von Arbeitsplätzen. Der KI-Einsatz beinhaltet Produktionsabläufe planen, Montagetätigkeiten übernehmen, Steuerungen programmieren oder Lager organisieren." (Autorenreferat, IAB-Doku)

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Gathmann, Christina, Felix Grimm & Erwin Winkler (2024): AI, Task Changes in Jobs, and Worker Reallocation. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 17554), Bonn, 50 S.

Abstract

"How does Artificial Intelligence (AI) affect the task content of work, and how do workers adjust to the diffusion of AI in the economy? To answer these important questions, we combine novel patent-based measures of AI and robot exposure with individual survey data on tasks performed on the job and administrative data on worker careers. Like prior studies, we find that robots have reduced routine tasks. In sharp contrast, AI has reduced non-routine abstract tasks like information gathering and increased the demand for 'high-level' routine tasks like monitoring processes. These task shifts mainly occur within detailed occupations and become stronger over time. While displacement effects are small, workers have responded by switching jobs, often to less exposed industries. We also document that low-skilled workers suffer some wage losses, while high-skilled incumbent workers experience wage gains." (Author's abstract, IAB-Doku) ((en))

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Grienberger, Katharina, Britta Matthes & Wiebke Paulus (2024): Folgen des technologischen Wandels für den Arbeitsmarkt: Vor allem Hochqualifizierte bekommen die Digitalisierung verstärkt zu spüren. (IAB-Kurzbericht 05/2024), Nürnberg, 8 S. DOI:10.48720/IAB.KB.2405

Abstract

"Die Potenziale, dass berufliche Tätigkeiten durch Computer oder computergesteuerte Maschinen vollautomatisch erledigt werden könnten, ändern sich, wenn neue Technologien auf dem Markt verfügbar werden. Bei der Neuberechnung solcher Substituierbarkeitspotenziale wird neben dieser Entwicklung auch berücksichtigt, dass sich die Tätigkeitsprofile in den Berufen verändern, neue Berufe und Tätigkeiten entstehen und Beschäftigte ihren Beruf wechseln. Die Autorinnen zeigen für die technologischen Möglichkeiten im Jahr 2022, wie hoch das Substituierbarkeitspotenzial derzeit ist und wie es sich seit 2013 verändert hat." (Autorenreferat, IAB-Doku)

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Guarascio, Dario, Alessandro Piccirillo & Jelena Reljic (2024): Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis. (GLO discussion paper / Global Labor Organization 1395), Essen, 31 S.

Abstract

"This study conducts a meta-analysis to assess the effects of robotization on employment and wages, compiling data from 33 studies with 644 estimates on employment and a subset of 19 studies with 195 estimates on wages. We identify a publication bias towards negative outcomes, especially concerning wages. After correcting for this bias, the actual impact appears minimal. Thus, concerns about the disruptive effects of robots on employment and the risk of widespread technological unemployment may be exaggerated or not yet empirically supported. While this does not preclude that robots will be capable of gaining greater disruptive potential in the future or that they are not already disruptive in specific contexts, the evidence to date suggests their aggregate effect is negligible." (Author's abstract, IAB-Doku) ((en))

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Guarascio, Dario, Alessandro Piccirillo & Jelena Reljic (2024): Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis. (LEM working paper series / Laboratory of Economics and Management 2024,03), Pisa, 31 S.

Abstract

"This study conducts a meta-analysis to assess the effects of robotization on employment and wages, compiling data from 33 studies with 644 estimates on employment and a subset of 19 studies with 195 estimates on wages. We identify a publication bias towards negative outcomes, especially concerning wages. After correcting for this bias, the actual impact appears minimal. Thus, concerns about the disruptive effects of robots on employment and the risk of widespread technological unemployment may be exaggerated or not yet empirically supported. While this does not preclude that robots will be capable of gaining greater disruptive potential in the future or that they are not already disruptive in specific contexts, the evidence to date suggests their aggregate effect is negligible." (Author's abstract, IAB-Doku) ((en))

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Güven, Barış (2024): Has labor-saving technology accelerated? Evidence from industry-level data. In: Structural Change and Economic Dynamics, Jg. 70, S. 442-456. DOI:10.1016/j.strueco.2024.05.008

Abstract

"What role has labor-saving technological change played in the recent past in charting out the trajectory of employment? Have we already transitioned into a new technological regime where production technologies are more invasive upon labor’s terrain? In this study, I provide empirical evidence to answer these questions. Using industry-level data from 12 advanced economies for 1970–2007, I show that capital goods did not become more effective in labor-saving after 1980 or 1990. Similarly, the strength of the relationship between employment and output did not decline after 1980 or 1990. While many recent econometric studies have estimated the number of workers displaced due to industrial robots with which the media and public are highly preoccupied, there is nothing new in the fact that production technologies are labor-saving and displace workers. The importance of demand side factors and structural change (mainly deindustrialization) in determining employment patterns is often neglected, leading to a misleading assessment of the impact of labor-saving technologies on employment." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Heluo, Yuxi & Oliver Fabel (2024): Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan. In: Technological forecasting & social change, Jg. 209. DOI:10.1016/j.techfore.2024.123772

Abstract

"This study adds to the growing literature on wage and employment responses to the risk of job computerization. Specifically, it revisits the original occupational perspective and inquires into the nature of the adjustments of occupational wages and employment, i.e., the potential benefits and costs associated with professional careers in such occupations. The investigation further aims at identifying whether these adjustment processes are universal - as suggested by the global availability of the respective technology - or reflect country-specific peculiarities. To this end, it conducts a comparative analysis with data from the United States, Germany, and Japan, three G7 lead countries which share the commitment to fostering technological progress, but which are also characterized by distinctly different labor market institutions and approaches to industrial policies. Generally consistent with the country-specific employment institutions and common corporate strategies, transmission channels - as reflected by the relationship between adjustments of occupational employment and wages - differ between countries. In all three countries, though, higher risks of computerization are associated with relative wage losses in occupations which require low levels of formal education or training." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Hu, Shengming, Kai Lin, Bei Liu & Hui Wang (2024): Does robotization improve the skill structure? The role of job displacement and structural transformation. In: Applied Economics, Jg. 56, H. 28, S. 3415-3430. DOI:10.1080/00036846.2023.2206623

Abstract

"The literature generally focuses on the impact of robots or artificial intelligence on the employment and wages, but ignores the effect of robotization on the skill structure and its underlying mechanisms and lacks empirical evidence from developing countries. We theoretically develop a task model by introducing the skill structure and empirically investigate the effect of robotization on the skill structure based on Chinese provincial panel data from 2006 to 2018. Results show that: (1) the development of robotization in China is conducive to improving the skill structure, and the baseline conclusion still holds even though adopting multiple indexes of skill structure and controlling the endogeneity bias. (2) Robotization generates not only job displacement effect by displacing unskilled workers with robots but also structural transformation effect by increasing the proportion of technology-intensive industries, which can improve the skill structure. (3) In coastal provinces with strong Internet foundation, information transmission capacity and labour protection intensity, high labour cost and ageing rate, robotization plays a stronger role in improving the skill structure. Moreover, robotization can induce the employment polarization. These conclusions can help avoid technical unemployment and promote the upgrading of the skill structure in China." (Author's abstract, IAB-Doku) ((en))

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Jacobs, Arthur & Freddy Heylen (2024): Demographic change, secular stagnation, and inequality: automation as a blessing? In: Journal of demographic economics, S. 1-41. DOI:10.1017/dem.2024.10

Abstract

"We study whether the increased adoption of available automation technologies allows economies to avoid the negative effect of aging on per capita output. We develop a quantitative theory in which firms choose to which extent they automate in response to a declining workforce and rising old-age dependency. An important element in our model is the integration of two capital types: automation capital that acts as a substitute to human labor, and traditional capital that is a complement to labor. Empirically, our model's predictions largely match data regarding automation (robotization) density across OECD countries. Simulating the model, we find that aging-induced automation only partially compensates the negative growth effect of aging in the absence of technical progress in automation technology. One reason is that automated tasks are no perfect substitutes for non-automated tasks. A second reason is that automation raises the interest rate and thus inhibits positive behavioral reactions to aging (later retirement and investment in human capital). Moreover, increased automation generates a falling net labor share of income and rising welfare inequality. We evaluate alternative policy responses to cope with this inequality." (Author's abstract, IAB-Doku) ((en))

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Jurkat, Anne, Rainer Klump & Florian Schneider (2024): Wie Roboter die Welt (und das Wirtschaften) verändern: Ein Überblick über Daten, Forschungsergebnisse und wirtschaftspolitische Strategien. In: Perspektiven der Wirtschaftspolitik, Jg. 25, H. 2, S. 130-152. DOI:10.1515/pwp-2024-0007

Abstract

"Der industrielle Einsatz von Robotern und die damit verbundenen Veränderungen wirtschaftlicher und sozialer Beziehungen sind ein schnell wachsendes Forschungsfeld. In diesem Beitrag geben Anne Jurkat, Rainer Klump und Florian Schneider einen Überblick über Datenquellen und aktuelle Ergebnisse der empirischen Forschung zum Robotereinsatz. Nach einer Präsentation der thematischen Schwerpunkte der Forschung erörtern sie die unterschiedlichen Analyseebenen und die drei zentralen Wirkungseffekte des Robotereinsatzes (Produktivitäts-, Substitutions- und Wiedereinsetzungseffekt). Abschließend analysieren sie die aktuellen wirtschaftspolitischen Strategien zum Umgang mit Robotik in Deutschland, die auf die Sicherung von Wettbewerbsfähigkeit und technologischer Souveränität abzielen." (Autorenreferat, IAB-Doku)

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Leduc, Sylvain & Zheng Liu (2024): Reshoring, Automation, and Labor Markets Under Trade Uncertainty. (Working papers series / Federal Reserve Bank of San Francisco 2024-16), San Francisco, Calif., 42 S. DOI:10.24148/wp2024-16

Abstract

"We study the implications of trade uncertainty for reshoring, automation, and U.S. labor markets. Rising trade uncertainty creates incentive for firms to reduce exposures to foreign suppliers by moving production and distribution processes to domestic producers. However, we argue that reshoring does not necessarily bring jobs back to the home country or boost domestic wages, especially when firms have access to labor-substituting technologies such as automation. Automation improves labor productivity and facilitates reshoring, but it can also displace jobs. Furthermore, automation poses a threat that weakens the bargaining power of low-skilled workers in wage negotiations, depressing their wages and raising the skill premium and wage inequality. The model predictions are in line with industry-level empirical evidence." (Author's abstract, IAB-Doku) ((en))

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Livanos, Ilias & Panagiotis Ravanos (2024): Job loss and Covid-19: an analysis on the impacts of remote work and automation. In: Applied Economics Letters, Jg. 31, H. 8, S. 712-723. DOI:10.1080/13504851.2022.2146641

Abstract

"Using a unique dataset from a dedicated Cedefop Skills Forecast scenario on the impacts of COVID-19, this paper explores two possible determinants of expected job loss in the European Union (EU) due to the pandemic, namely the potential of work from home and the impacts of automation. Our findings suggest that less remote work and more automation are both related to future job losses across countries and occupations. These links are stronger in 2020–2021 at the country level, while becoming significant at the occupation level after 2022 when several protective measures taken by EU governments are expected to have been lifted." (Author's abstract, IAB-Doku) ((en))

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Matthes, Britta (2024): Wie KI und andere digitale Technologien die Arbeit von Ingenieuren in der Elektro- und Informationstechnik verändern könnten. In: VDE Verband der Elektrotechnik, Elektronik und Informationstechnik (Hrsg.) (2024): Rolle der Künstlichen Intelligenz in der Elektro- und Informationstechnik, S. 21-27, 2024-10-14.

Abstract

"Die Liste der Technologien, die für die Arbeit von Ingenieuren in der Elektro- und Informationstechnik in den nächsten Jahren relevant sind, ist sehr lang. Dabei spielt KI in vielen technologischen Bereichen eine wichtige Rolle. Dennoch: Auch wenn die Automatisierungspotenziale bei diesen Berufen durch Einsatz von KI und anderen digitalen Technologien hoch sind, steht überhaupt nicht zur Debatte, dass es in Zukunft diese Berufe nicht mehr geben wird! Das hat verschiedene Gründe: Der wichtigste ist, dass KI erst dann produktiv zum Einsatz gebracht werden kann, wenn sie mit fachspezifischen Kenntnissen zusammentrifft. Es geht aber auch darum, dass sich die heute bereits bestehende Fachkräfteknappheit in diesen Berufen in den nächsten Jahren eher weiter verschärfen als abschwächen wird. Nicht nur, dass in den Ingenieurberufen der Elektro- und Informationstechnik in den kommenden Jahren überproportional viele der sozialversicherungspflichtig Beschäftigten in den Ruhestand gehen. Mit großer Wahrscheinlichkeit führt auch die Nutzung der Potenziale, die sich durch den Einsatz von KI in Wirtschaft und Gesellschaft ergeben, zu einer deutlichen Nachfragesteigerung in diesen Berufen. Hinzu kommt, dass die Elektro- und Informationstechnik zu denjenigen Gebieten gehört, die eine besondere Rolle bei der parallel zur digitalen Transformation stattfindenden ökologischen Transformation spielt. Gut ausgebildete Ingenieure der Elektro- und Informationstechnik werden zusätzlich gebraucht, um ihr spezifisches Wissen bei der Erzeugung und Speicherung von Wind- und Solarenergie, aber auch beim Umstieg vom Verbrenner zum Elektroantrieb einzusetzen. Eine der wichtigsten Fragen, die sich aus diesen Überlegungen ergibt, ist deshalb weniger, ob es auch in Zukunft noch Ingenieure der Elektro- und Informationstechnik geben wird. Vielmehr stellt sich die Frage, was lässt sich an der Arbeit, wie sie heute noch von diesen Ingenieuren erledigt wird, durch den Einsatz von KI und anderen modernen Technologien effizienter machen oder sogar automatisieren, um zu verhindern, dass die Fachkräftelücke noch größer wird. Dabei geht es nicht nur um die technologischen Potenziale, sondern auch darum, unter welchen Bedingungen tatsächlich automatisiert werden kann. Denn Automatisierung ist äußerst voraussetzungsvoll: Es muss investiert werden, nicht nur in Maschinen und Anlagen, sondern auch in Dateninfrastruktur und in die Fähigkeiten und Motivation derjenigen, die damit zukünftig arbeiten sollen. Häufig müssen erst die Datengrundlagen geschaffen, Prozesse neu etabliert, eine Aufbruchstimmung erzeugt werden; es gibt rechtliche Hürden wie zum Beispiel datenschutz- oder urheberrechtliche Vorgaben; die Wahrung von Geschäftsgeheimnissen steht einer Automatisierung entgegen; oder es bestehen ethische Bedenken." (Textauszug, IAB-Doku)

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Montobbio, Fabio, Jacopo Staccioli, Maria Enrica Virgillito & Marco Vivarelli (2024): The empirics of technology, employment and occupations: Lessons learned and challenges ahead. In: Journal of Economic Surveys, Jg. 38, H. 5, S. 1622-1655. DOI:10.1111/joes.12601

Abstract

"This paper is a critical review of the empirical literature resulting from recent years of debate and analysis regarding technology and employment and the future of work as threatened by technology, outlining both lessons learned and challenges ahead. We distinguish three waves of studies and relate their heterogeneous findings to the choice of technological proxies, the level of aggregation, the adopted research methodology and to the relative focus on robots, automation and AI. The challenges ahead include the need for awareness of possible ex‐ante biases associated with the adopted proxiesfor innovation; the recognition of the trade‐off between microeconometric precision and a more holistic macroeconomic approach; the need for granular analysis of the reallocation and transformation of occupations and tasks brought about by different types of new technologies; the call for a closer focus on impacts on labor quality, in terms of types of jobs and working conditions." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Nikolova, Milena, Femke Cnossen & Boris Nikolaev (2024): Robots, meaning, and self-determination. In: Research Policy, Jg. 53, H. 5. DOI:10.1016/j.respol.2024.104987

Abstract

"This paper is the first to examine the impact of robotization on work meaningfulness, autonomy, competence, and relatedness, which are essential to motivation and well-being at work. Using surveys of workers and robotization data for 14 industries in 20 European countries spanning 2005–2021, we find a consistent negative impact of robotization on perceived work meaningfulness and autonomy. Using instrumental variables, we find that doubling robotization leads to a 0.9 % decrease in work meaningfulness and a 1 % decline in autonomy. To put this in perspective, if the robotization levels of the top 5 industry were to match those of the leading industry in terms of robot adoption in 2020 (equivalent to a 7.5-fold increase), it would result in a decline of 6.8 % in work meaningfulness and 7.5 % in autonomy. The link between robotization, competence, and relatedness is also negative but less robust. We also examine how tasks, skills, and socio-demographic characteristics moderate the main relationships. We find that workers with routine tasks experience an even greater negative effect of robotization in terms of declines in their autonomy, competence, and relatedness. However, we also discover that utilizing computers as tools for independent work can help workers maintain a sense of autonomy, competence, and relatedness in industries and job roles that adopt robots. Our results highlight that by deteriorating work meaningfulness and self-determination, robotization can impact work life above and beyond its consequences for employment and wages." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Nurski, Laura & Nina Ruer (2024): Exposure to generative artificial intelligence in the European labour market. (Working paper / Bruegel 2024,06), Brüssel, 33 S.

Abstract

"We apply two sets of generative artificial intelligence (GenAI) occupational exposure scores – one task-based, one ability-based – to the European Labour Force Survey. While using different methodologies, our findings reveal consistent demographic patterns across the two approaches: jobs held by women, highly educated and younger workers are more exposed to GenAI technology in Europe. We also review the literature on the recent productivity impact of GenAI. Within the same occupations, less-experienced or less-skilled workers consistently get the largest productivity gains from GenAI support. We argue that a task-based analysis is more fruitful than an ability-based one, both for guiding GenAI adoption in organisations and their workplaces, and for assessing the employment and job quality impact on workers. Finally, we provide policy recommendations that can help workers (ie the labor supply) adjust to technological disruption, such as providing training and social safety nets. But we go further by also suggesting policy interventions that could redirect future labor demand towards better jobs, by promoting job redesign and organisational agility. Monitoring GenAI’s employment effects and researching the ‘jagged technological frontier’ is necessary to further build our understanding of the employment impact of this transformational technology." (Author's abstract, IAB-Doku) ((en))

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Seele, Stefanie (2024): Experten sind besonders nah an KI. (IW-Kurzberichte / Institut der Deutschen Wirtschaft Köln 2024,20), Köln, 3 S.

Abstract

"Früher haben Digitalisierungstechnologien eher Helfer und Fachkräfte ersetzt als Höherqualifizierte. Durch die Fortschritte der künstlichen Intelligenz (KI) sind zunehmend Spezialisten und Experten betroffen." (Autorenreferat, IAB-Doku)

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Sharfaei, Shahab (2024): Robots and employment: A review. In: International Labour Review, Jg. 163, H. 2, S. 271-293. DOI:10.1111/ilr.12417

Abstract

"Rapid advances in robotics signal a scientific breakthrough that could have major implications for the world economy and the field of economics. This article reviews recent literature on this topic to examine the evidence from two perspectives. First, I critically review the theoretical literature on the effects of robot adoption on employment and analyse the capacity of different theories to describe these influences. Second, I evaluate the current empirical evidence regarding the impact of robot technology on the economy in terms of employment and reshoring. This exercise highlights the limitations in the literature and points to avenues for future research." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Vasiakina, Mariia & Christian Dudel (2024): From efficiency to illness: do highly automatable jobs take a toll on health in Germany? (MPIDR working paper / Max Planck Institute for Demographic Research 2024-041), Rostock, 30 S. DOI:10.4054/MPIDR-WP-2024-041

Abstract

"Automation transforms work at a rapid pace, with gradually increasing shares of the workforce being at risk of replacement by machines. However, little is known about how this risk is affecting workers. In this study, we investigate the impact of exposure to a high risk of automation at work on the subjective (self-reported health, anxiety, and health satisfaction) and objective (healthcare use and sickness absence) health outcomes of workers in Germany. We base our analysis on survey data from the German Socio-Economic Panel (SOEP) and administrative data from the Occupational Panel for Germany (2013-2018). Employing panel regression, we demonstrate that for workers, exposure to a high risk of automation at the occupational level is associated with lower self-reported health and health satisfaction, increased sickness absence, and, depending on how the risk is measured, anxiety. No effect on healthcare use is found. Our heterogeneity analysis provides evidence that none of the analyzed demographic and occupational groups is disproportionally affected by high automation risk. We also conduct several robustness checks (i.e., alternative model specifications and risk measures with different thresholds), with the results remaining largely consistent with our main findings." (Author's abstract, IAB-Doku) ((en))

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Walwei, Ulrich (2024): Substituierungspotenziale sind nicht gleichbedeutend mit Arbeitsplatzverlusten. In: Goinger Kreis (Hrsg.) (2024): Liebeserklärung an die Arbeit. Was Arbeit ausmacht, wie sie uns bereichert und wie wir sie wertschätzen müssen, getr. Sz.