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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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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.

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Özgül, Pelin, Marie-Christine Fregin, Michael Stops, Simon Janssen & Mark Levels (2024): High-skilled Human Workers in Non-Routine Jobs are Susceptible to AI Automation but Wage Benefits Differ between Occupations. (arXiv papers 2404.06472), 55 S. DOI:10.48550/arXiv.2404.06472

Abstract

"Artificial Intelligence (AI) will change human work by taking over specific job tasks, but there is a debate which tasks are susceptible to automation, and whether AI will augment or replace workers and affect wages. By combining data on job tasks with a measure of AI susceptibility, we show that more highly skilled workers are more susceptible to AI automation, and that analytical non-routine tasks are at risk to be impacted by AI. Moreover, we observe that wage growth premiums for the lowest and the highest required skill level appear unrelated to AI susceptibility and that workers in occupations with many routine tasks saw higher wage growth if their work was more strongly susceptible to AI. Our findings imply that AI has the potential to affect human workers differently than canonical economic theories about the impact of technology on work these theories predict." (Author's abstract, IAB-Doku) ((en))

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Acemoglu, Daron & Simon Johnson (2023): Rebalancing AI. In: Finance and development H. December, S. 26-29.

Abstract

"Optimistic forecasts regarding the growth implications of AI abound. AI adoption could boost productivity growth by 1.5 percentage points per year over a 10-year period and raise global GDP by 7 percent ($7 trillion in additional output), according to Goldman Sachs. Industry insiders offer even more excited estimates, including a supposed 10 percent chance of an “explosive growth” scenario, with global output rising more than 30 percent a year. All this techno-optimism draws on the “productivity bandwagon”: a deep-rooted belief that technological change— including automation—drives higher productivity, which raises net wages and generates shared prosperity. Such optimism is at odds with the historical record and seems particularly inappropriate for the current path of “just let AI happen,” which focuses primarily on automation (replacing people). We must recognize that there is no singular, inevitable path of development for new technology. And, assuming that the goal is to sustainably improve economic outcomes for more people, what policies would put AI development on the right path, with greater focus on enhancing what all workers can do?" (Text excerpt, IAB-Doku) ((en))

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Agrawal, Ajay K., Joshua S. Gans & Avi Goldfarb (2023): The Turing Transformation: Artificial Intelligence, Intelligence Augmentation, and Skill Premiums. (NBER working paper / National Bureau of Economic Research 31767), Cambridge, Mass, 12 S.

Abstract

"We ask whether a technical objective of using human performance of tasks as a benchmark for AI performance will result in the negative outcomes highlighted in prior work in terms of jobs and inequality. Instead, we argue that task automation, especially when driven by AI advances, can enhance job prospects and potentially widen the scope for employment of many workers. The neglected mechanism we highlight is the potential for changes in the skill premium where AI automation of tasks exogenously improves the value of the skills of many workers, expands the pool of available workers to perform other tasks, and, in the process, increases labor income and potentially reduces inequality. We label this possibility the “Turing Transformation.” As such, we argue that AI researchers and policymakers should not focus on the technical aspects of AI applications and whether they are directed at automating human-performed tasks or not and, instead, focus on the outcomes of AI research. In so doing, our goal is not to diminish human-centric AI research as a laudable goal. Instead, we want to note that AI research that uses a human-task template with a goal to automate that task can often augment human performance of other tasks and whole jobs. The distributional effects of technology depend more on which workers have tasks that get automated than on the fact of automation per se." (Author's abstract, IAB-Doku) ((en))

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Blien, Uwe, Oliver Ludewig & Anja Rossen (2023): Contradictory effects of technological change across developed countries. In: Review of International Economics, Jg. 31, H. 2, S. 580-608., 2022-08-31. DOI:10.1111/roie.12638

Abstract

"Will productivity gains lead to technological unemployment in a region or to new prosperity? In our article, we formally show that under general assumptions the price elasticity of demand on product markets is decisive: technological change leads to employment growth if product demand is elastic and it leads to employment decline if product demand is inelastic. In our empirical analysis, we use industry-level time series data on output, prices, employment, wages, and national income for nine countries (including Germany, UK, USA) to estimate aggregate Marshallian product demand functions based on IV regressions and state space models with time-varying coefficients. The resulting income and price elasticities are used as inputs in a second step in which we estimate the employment effects of productivity changes as interactions with the elasticities. The results correspond to theoretical expectations: demand is generally inelastic and the employment effect of technological progress is therefore moderately negative." (Author's abstract, IAB-Doku, © Wiley) ((en))

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Bowlus, Audra, Lance Lochner, Chris Robinson & Eda Suleymanoglu (2023): Wages, Skills, and Skill-Biased Technical Change. The Canonical Model Revisited. In: The Journal of Human Resources, Jg. 58, H. 6, S. 1783-1819. DOI:10.3368/jhr.0617-8889r1

Abstract

"While influential, the canonical supply–demand model of the wage returns to skill has faced challenges, including theoretically wrong-signed elasticities of substitution, counterintuitive paths for skill-biased technical change (SBTC), and an inability to account for observed deviations in college premia for younger versus older workers. We show that using improved estimates of skill prices and supplies that account for variation in skills across cohorts helps to explain the college premium differences between younger versus older workers and produces better out-of-sample predictions, positive elasticities of substitution between high- and low-skill workers, and a more modest role for SBTC. We further show that accounting for recession-induced jumps and trend adjustments in SBTC and linking SBTC to direct measures of information technology investment expenditures yield an improved fit, no puzzling slowdown in SBTC during the early 1990s, and a higher elasticity of substitution between high- and low-skill workers than previous ad hoc assumptions." (Author's abstract, IAB-Doku, © the Board of Regents of the University of Wisconsin System) ((en))

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Buch, Tanja, Annekatrin Niebuhr, Michael Stops & Andrea Stöckmann (2023): Kompetenzanforderungen in ausgewählten Berufen – Ergebnisse aus dem Kompetenz-Kompass Mecklenburg-Vorpommern (Tabellenband). Nürnberg, 39 S.

Abstract

"Digitalisierung und ökologische Transformation gehen mit einer Änderung der Kompetenzanforderungen einher. Für die technischen Berufe in Mecklenburg-Vorpommern haben Buch et al. (2023a) eine Studie zu den in Stellenanzeigen formulierten Kompetenzanforderungen vorgelegt. Für die Berufe der Informatik-, Informations- und Kommunikationstechnologie (IKT-Berufe) liegt ein entsprechender Tabellenband vor (Buch et al. 2023b). Der vorliegende nicht veröffentlichte Tabellenband ergänzt die genannten Publikationen um Kompetenzanforderungen in vier weiteren Berufsgruppen: Hochbau; Lagerwirtschaft, Post, Zustellung, Güterumschlag; Immobilienwirtschaft, Facility-Management; Werbung und Marketing. Bei der Dokumentation der Kompetenzanforderungen unterscheiden wir auch nach dem Anforderungsniveau der ausgeschriebenen Stellen. Zur Einordnung der Resultate verweisen wir auf die Studie von Buch et al. (2023a) für die technischen Berufe. Im Kapitel 2 beschreiben wir die Datenbasis und die Methodik der Analyse ausführlicher. In den Kapiteln 3 bis 6 erfolgt dann die detaillierte Darstellung der Kompetenzbedarfe in den einzelnen Berufsgruppen." (Autorenreferat, IAB-Doku)

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Buch, Tanja, Annekatrin Niebuhr, Michael Stops & Andrea Stöckmann (2023): Kompetenzanforderungen in ausgewählten Berufen – Ergebnisse aus dem Kompetenz-Kompass Hamburg (Tabellenband). Nürnberg, 38 S.

Abstract

"Digitalisierung und ökologische Transformation gehen mit einer Änderung der Kompetenzanforderungen einher. Für die technischen Berufe in Hamburg haben Buch et al. (2023a) eine Studie zu den in Stellenanzeigen formulierten Kompetenzanforderungen vorgelegt. Für die Berufe der Informatik, Informations- und Kommunikationstechnologie (IKT-Berufe) liegt ein entsprechender Tabellenband vor (Buch et al. 2023b). Der vorliegende nicht veröffentlichte Tabellenband ergänzt die genannten Publikationen um Kompetenzanforderungen in vier weiteren Berufsgruppen: Hochbau; Lagerwirtschaft, Post, Zustellung, Güterumschlag; Immobilienwirtschaft, Facility-Management; Werbung und Marketing. Bei der Dokumentation der Kompetenzanforderungen unterscheiden wir auch nach dem Anforderungsniveau der ausgeschriebenen Stellen. Im Kapitel 2 beschreiben wir die Datenbasis und die Methodik der Analyse ausführlicher. In den Kapiteln 3 bis 6 erfolgt dann die detaillierte Darstellung der Kompetenzbedarfe in den einzelnen ausgewählten Berufsgruppen." (Autorenreferat, IAB-Doku)

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Buch, Tanja, Annekatrin Niebuhr, Michael Stops & Andrea Stöckmann (2023): Kompetenzanforderungen in ausgewählten Berufen – Ergebnisse aus dem Kompetenz-Kompass Schleswig-Holstein (Tabellenband). Nürnberg, 38 S.

Abstract

"Für die technischen Berufe in Schleswig-Holstein haben Buch et al. (2023a) eine Studie zu den in Stellenanzeigen formulierten Kompetenzanforderungen vorgelegt. Für die Berufe der Informatik-, Informations- und Kommunikationstechnologie (IKT-Berufe) liegt ein entsprechender Tabellenband vor (Buch et al. 2023b). Der vorliegende nicht veröffentlichte Tabellenband ergänzt die genannten Publikationen um Kompetenzanforderungen in vier weiteren Berufsgruppen: Hochbau; Lagerwirtschaft, Post, Zustellung, Güterumschlag; Immobilienwirtschaft, Facility-Management; Werbung und Marketing. Bei der Dokumentation der Kompetenzanforderungen unterscheiden wir auch nach dem Anforderungsniveau der ausgeschriebenen Stellen. Zur Einordnung der Resultate verweisen wir auf die Studie von Buch et al. (2023a) für die technischen Berufe. Im Kapitel 2 beschreiben wir die Datenbasis und die Methodik der Analyse ausführlicher. In den Kapiteln 3 bis 6 erfolgt dann die detaillierte Darstellung der Kompetenzbedarfe in den einzelnen Berufsgruppen." (Autorenreferat, IAB-Doku)