Digitale Arbeitswelt – Chancen und Herausforderungen für Beschäftigte und Arbeitsmarkt
Der digitale Wandel der Arbeitswelt gilt als eine der großen Herausforderungen für Wirtschaft und Gesellschaft. Wie arbeiten wir in Zukunft? Welche Auswirkungen hat die Digitalisierung und die Nutzung Künstlicher Intelligenz auf Beschäftigung und Arbeitsmarkt? Welche Qualifikationen werden künftig benötigt? Wie verändern sich Tätigkeiten und Berufe? Welche arbeits- und sozialrechtlichen Konsequenzen ergeben sich daraus?
Dieses Themendossier dokumentiert Forschungsergebnisse zum Thema in den verschiedenen Wirtschaftsbereichen und Regionen.
Im Filter „Autorenschaft“ können Sie auf IAB-(Mit-)Autorenschaft eingrenzen.
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
- Qualifikationsanforderungen und Berufe
- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
- Arbeits- und sozialrechtliche Aspekte / digitale soziale Sicherung
- Deutschland
- Andere Länder/ internationaler Vergleich
- Besondere Personengruppen
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Literaturhinweis
Organized Labor Versus Robots? Evidence from Micro Data (2024)
Zitatform
Findeisen, Sebastian, Wolfgang Dauth & Oliver Schlenker (2024): Organized Labor Versus Robots? Evidence from Micro Data. (Working Paper Series / Universität Konstanz, Cluster of Excellence 'The Politics of Inequality' 25), Konstanz, 31 S. DOI:10.48787/kops/352-2-pkkgn822nr6u9
Abstract
"New technologies drive productivity growth but the distribution of gains might be unequal and is mediated by labor market institutions. We study the role that organized labor plays in shielding incumbent workers from the potential negative consequences of automation. Combining German individual-level administrative records with information on plant-level robot adoption and the presence of works councils, a form of shop-floor worker representation, we find positive moderating effects of works councils on retention for incumbent workers during automation events. Separations for workers with replaceable task profiles are significantly reduced. When labor markets are tight and replacement costs are high for firms, incumbent workers become more valuable and the effects of works councils during automation events start to disappear. Older workers, who find it more challenging to reallocate to new employers, benefit the most from organized labor in terms of wages employment. Concerning mechanisms we find that robot-adopting plants with works councils employ not more but higher quality robots. They also provide more training during robot adoption and have higher productivity growth thereafter." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy (2024)
Zitatform
Fleischer, Julia & Camilla Wanckel (2024): Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy. In: Review of Public Personnel Administration, Jg. 44, H. 3, S. 431-452. DOI:10.1177/0734371X221148403
Abstract
"Worldwide, governments have introduced novel information and communication technologies (ICTs) for policy formulation and service delivery, radically changing the working environment of government employees. Following the debate on work stress and particularly on technostress, we argue that the use of ICTs triggers “digital overload” that decreases government employees’ job satisfaction via inhibiting their job autonomy. Contrary to prior research, we consider job autonomy as a consequence rather than a determinant of digital overload, because ICT-use accelerates work routines and interruptions and eventually diminishes employees’ freedom to decide how to work. Based on novel survey data from government employees in Germany, Italy, and Norway, our structural equation modeling (SEM) confirms a significant negative effect of digital overload on job autonomy. More importantly, job autonomy partially mediates the negative relationship between digital overload and job satisfaction, pointing to the importance of studying the micro-foundations of ICT-use in the public sector." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
On the Automation of Job Tasks: Occupational exposure to Artificial Intelligence and Software (2024)
Zitatform
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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Literaturhinweis
Informationsbereitstellung zur Automatisierbarkeit von Berufen erhöht Weiterbildungsbereitschaft (2024)
Zitatform
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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Literaturhinweis
Künstliche Intelligenz und industrielle Arbeit – Perspektiven und Gestaltungsoptionen: Expertise des Forschungsbeirats Industrie 4.0 (2024)
Gabriel, Stefan; Kretzschmer, Veronika; Graunke, Jannis; Dumitrescu, Roman; Murrenhoff, Anike; Hompel, Michael ten ; Falkowski, Tommy;Zitatform
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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Literaturhinweis
Einsatz von KI in Werkstätten für behinderteMenschen (2024)
Garoscio, Lidia; Wiehe, Katharina;Zitatform
Garoscio, Lidia & Katharina Wiehe (2024): Einsatz von KI in Werkstätten für behinderteMenschen. In: Soziale Sicherheit, Jg. 73, H. 8-9, S. 23-27.
Abstract
"Werkstätten für behinderte Menschen haben bereits Erfahrungen mit dem Einsatz von KI-gestützten Assistenzsystemen gemacht. Diese können Menschen mit Behinderungen in unterschiedlichen Arbeitsbereichen unterstützen. Der Artikel zeigt die Potenziale des Einsatzes anhand einiger Praxisbeispiele auf, diskutiert aber auch dessen Hürden und geht auf die Rolle desProjekts „KI-Kompass Inklusiv“ ein." (Textauszug, IAB-Doku)
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Literaturhinweis
The pandemic push: Digital technologies and workforce adjustments (2024)
Zitatform
Gathmann, Christina, Christian Kagerl, Laura Pohlan & Duncan Roth (2024): The pandemic push: Digital technologies and workforce adjustments. In: Labour Economics, 2024-04-05. DOI:10.1016/j.labeco.2024.102541
Abstract
"Using a novel firm survey matched to administrative employee records, we demonstrate that the COVID-19 pandemic was a push factor for the diffusion of digital technologies in Germany. Two out of three firms invested in digital technologies. Three quarters of those investing firms invested because of the pandemic, particularly in hardware and software to enable decentralized communication, management, and coordination. These investments also fostered additional firm-sponsored training, underscoring the complementarity between investments in digital technologies and training. We then show that the investments helped firms insure their workers against the economic downturn. Firms with additional digital investments retained more of their employees on regular working hours and relied less on short-time work. Low- and medium-skilled, as well as young workers, benefited the most from the insurance effect of digital investments." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
AI, Task Changes in Jobs, and Worker Reallocation (2024)
Zitatform
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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Literaturhinweis
Artificial intelligence and wage inequality (2024)
Georgieff, Alexandre;Zitatform
Georgieff, Alexandre (2024): Artificial intelligence and wage inequality. (OECD artificial intelligence papers 13), Paris, 37 S. DOI:10.1787/bf98a45c-en
Abstract
"This paper looks at the links between AI and wage inequality across 19 OECD countries. It uses a measure of occupational exposure to AI derived from that developed by Felten, Raj and Seamans (2019) – a measure of the degree to which occupations rely on abilities in which AI has made the most progress. The results provide no indication that AI has affected wage inequality between occupations so far (over the period 2014-2018). At the same time, there is some evidence that AI may be associated with lower wage inequality within occupations – consistent with emerging findings from the literature that AI reduces productivity differentials between workers. Further research is needed to identify the exact mechanisms driving the negative relationship between AI and wage inequality within occupations. One possible explanation is that low performers have more to gain from using AI because AI systems are trained to embody the more accurate practices of high performers. It is also possible that AI reduces performance differences within an occupation through a selection effect, e.g. if low performers leave their job because they are unable to adapt to AI tools by shifting their activities to tasks that AI cannot automate." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Wie kollegial ist Künstliche Intelligenz?: Risikowahrnehmungen und Gestaltungsanforderungen aus Sicht von Beschäftigten (2024)
Gerlmaier, Anja; Bendel, Alexander;Zitatform
Gerlmaier, Anja & Alexander Bendel (2024): Wie kollegial ist Künstliche Intelligenz? Risikowahrnehmungen und Gestaltungsanforderungen aus Sicht von Beschäftigten. (IAQ-Report 2024-01), Duisburg ; Essen, 15 S. DOI:10.17185/duepublico/81427
Abstract
Zukünftig werden immer mehr Beschäftigte nicht nur in ihrem privaten Umfeld, sondern auch am Arbeitsplatz mit Systemen zusammenarbeiten, die auf Künstlicher Intelligenz (KI) basieren. Das IAQ untersuchte im Rahmen des "HUMAINE"-Projektes, wie Beschäftigte die Kooperation mit solchen KI-Systemen bewerten und welche Gestaltungsanforderungen sie an diese neue Form der hybriden Mensch-KI-Zusammenarbeit haben. Es zeigte sich, dass KI-Systeme je nach Interaktionsform unterschiedliche Potenziale und Risiken aufweisen. Um die KI-basierten Risiken zu verringern, sollten Nutzer*innen frühzeitig an der Konzeption und Implementierung beteiligt und dabei arbeitswissenschaftliche Gestaltungskriterien berücksichtigt werden. (Author's abstract, IAB-Doku)
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Literaturhinweis
Assessing the impact of new technologies on wages and labour income shares (2024)
Zitatform
Ghodsi, Mahdi, Robert Stehrer & Antea Barišić (2024): Assessing the impact of new technologies on wages and labour income shares. In: Technological forecasting & social change, Jg. 209. DOI:10.1016/j.techfore.2024.123782
Abstract
"This paper advances the literature on the impacts of new technologies on labor markets, focusing on wage and labor income shares. Using a dataset from 32 countries and 38 industries, we analyze the effects of new technologies – proxied by patents, information and communication technology (ICT) capital usage, and robot intensity – on average wages and labour income shares over time. Our results indicate a positive correlation between patents and wage levels along with a minor negative impact on labor income shares, suggesting that technology rents are not fully passed on to labor. Robot intensity is positively associated with labor income shares, while ICT capital has an insignificant effect. These effects persist over time and are reinforced by global value chain (GVC) linkages. Our conclusions align with recent research indicating that new technologies have a generally limited impact on wages and labour income shares." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Artificial intelligence and the changing demand for skills in the labour market (2024)
Zitatform
Green, Andrew (2024): Artificial intelligence and the changing demand for skills in the labour market. (OECD artificial intelligence papers 14), Paris, 55 S. DOI:10.1787/88684e36-en
Abstract
"Most workers who will be exposed to artificial intelligence (AI) will not require specialised AI skills (e.g. machine learning, natural language processing, etc.) to work with AI. Even so, AI will change the tasks these workers do, and the skills they require. This report provides first estimates for the effect of artificial intelligence (AI) on the demand for skills in jobs that do not require specialised AI skills. The results show that the skills most demanded in occupations highly exposed to AI are management and business skills. These include skills in general project management, finance, administration and clerical tasks. The results also show that there have been increases over time in the demand for these skills in occupations highly exposed to AI. For example, the share of vacancies in these occupations that demand at least one emotional, cognitive or digital skill has increased by 8 percentage points. However, using a panel of establishments (which induces plausibly exogenous variation in AI exposure), the report finds evidence that the demand for these skills is beginning to fall in establishments most exposed to AI." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Folgen des technologischen Wandels für den Arbeitsmarkt: Vor allem Hochqualifizierte bekommen die Digitalisierung verstärkt zu spüren (2024)
Zitatform
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)
Weiterführende Informationen
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Literaturhinweis
KI-Revolution der Arbeitswelt: Perspektiven für Management, Organisation und HR (2024)
Groß, Michael; Staff, Jörg;Zitatform
Groß, Michael & Jörg Staff (Hrsg.) (2024): KI-Revolution der Arbeitswelt. Perspektiven für Management, Organisation und HR. Freiburg: Haufe Group, 322 S.
Abstract
"Künstliche Intelligenz (KI) gilt als zentrales Zukunftsthema in nahezu allen Bereichen der Wirtschaft. Schon heute sind die Veränderungen durch KI in unserer Arbeitswelt spürbar. Dieses Buch von Prof. Dr. Michael Groß und Jörg Staff bietet hochaktuelle Beiträge über die bereits heute möglichen Anwendungen von KI im Personalbereich und deren Auswirkungen. Sie lernen die wesentlichen Perspektiven für den Einsatz von KI kennen und gewinnen einen Überblick über Chancen und Risiken von KI in Arbeit, Führung und Organisation. Zudem erhalten Sie wichtige Impulse für den Einsatz von KI im Management. Mit konkreten Handlungsempfehlungen sowie Praxisbeispielen namhafter Unternehmen und Institutionen, z.B. REWE, Zeiss, SAP, Workday, Coach Hub sowie Fraunhofer IAO, Ethikrat HR Tech, DGFP, DFKI." (Autorenreferat, IAB-Doku, © Haufe)
Weiterführende Informationen
Inhaltsverzeichnis bei der Deutschen Nationalbibliothek -
Literaturhinweis
Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis (2024)
Zitatform
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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Literaturhinweis
Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis (2024)
Zitatform
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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Literaturhinweis
Training, Automation, and Wages: Worker-Level Evidence (2024)
Zitatform
Guo, Yuchen Mo, Oliver Falck, Christina Langer, Valentin Lindlacher & Simon Wiederhold (2024): Training, Automation, and Wages: Worker-Level Evidence. In: Verein für Socialpolitik (Hrsg.) (2024): Upcoming Labor Market Challenges. Beiträge zur Jahrestagung des Vereins für Socialpolitik 2024.
Abstract
"This paper investigates the impact of job training on workers’ susceptibility to automation. Using rich individual-level data from the Programme for the International Assessment of Adult Competencies (PIAAC) across 37 industrialized countries, we construct a unique individual-level measure of automation risk based on the tasks performed at work. We uncover substantial variation in automation risk within detailed occupations, which would have been overlooked by previous occupation-level automation measures. To estimate the effect of training on workers’ automation risk, we include tested numeracy skills as a proxy for unobserved ability that are unique to our data, and apply entropy balancing to account for selection bias. We find that job training is an important factor in explaining workers’ susceptibility to automation, even within narrowly defined occupations. Our results show that workers who participate in job training witness a 4.7 percentage point reduction in their automation risk compared to observationally equivalent workers without training. Additionally, workers participating in training earn approximately 8 percent higher wages compared to their counterparts without training. While training is effective in reducing automation risk and increasing wages in all sample countries, there is a substantial heterogeneity in the magnitude of training effects. Moreover, training benefits both younger and older workers equally, and is more effective for women. Our findings thus underscore the crucial role of training in enabling the workforce to adapt and thrive amidst evolving technological changes." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Has labor-saving technology accelerated? Evidence from industry-level data (2024)
Zitatform
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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Literaturhinweis
Interests of the future: An integrative review and research agenda for an automated world of work (2024)
Hanna, Alexis ; Nye, Christopher D. ; Hoff, Kevin A. ; Rounds, James ; Samo, Andrew; Oswald, Frederick L. ; Chu, Chu ;Zitatform
Hanna, Alexis, Christopher D. Nye, Andrew Samo, Chu Chu, Kevin A. Hoff, James Rounds & Frederick L. Oswald (2024): Interests of the future: An integrative review and research agenda for an automated world of work. In: Journal of vocational behavior, Jg. 152. DOI:10.1016/j.jvb.2024.104012
Abstract
"Research on automation and the future of work is a major focus for both academics and practitioners due to technological changes disrupting the labor market and educational pathways. Although recent articles have published projections about the types of tasks and jobs most likely to be automated in the coming years, little attention has been devoted to how different types of vocational interests are susceptible to automation, as well as resulting changes to the match between people's interests and their jobs. In the present article, we provide an integrative review of vocational interests and automation projections within and across jobs. By standardizing and mapping projections to Holland's RIASEC interest model, we found that Investigative (scientific) and Conventional (detail-oriented) interests, including STEM interests, are most susceptible to automation, whereas Social (people-oriented) and Realistic (hands-on) interests are least susceptible. For Artistic and Enterprising interests, some creative work, decision-making, and leadership skills may be affected by automation across a range of jobs. We build on these projections to propose a future research agenda integrating interests, technology, and careers. Specifically, we identify five areas for future research, including using intentional work design to enhance interests, the role of interests in career decisions related to project-based work, changes in people's interests following automation, increased use of basic interests, and the systematic impacts of automation on different groups of people. Overall, this review highlights how vocational interests will remain an important topic with high relevance for career guidance, education, and organizations as the future of work evolves." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Generative Künstliche Intelligenz reduziert Nachfrage nach Freelance-Arbeit auf Online-Plattformen (2024)
Zitatform
Hannane, Jonas, Ozge Demirci & Xinrong Zhu (2024): Generative Künstliche Intelligenz reduziert Nachfrage nach Freelance-Arbeit auf Online-Plattformen. In: DIW-Wochenbericht, Jg. 91, H. 35, S. 539-545. DOI:10.18723/diw_wb:2024-35-1
Abstract
"Einführung generativer KI birgt das Potenzial für höheres Wirtschaftswachstum, stellt. Arbeitnehmer*innen aber auch vor große Herausforderungen • Auftragszahlen auf Online-Arbeitsmärkten zeigen: Nachfrage nach leicht automatisierbaren Tätigkeiten bleibt deutlich hinter der nach anderen Tätigkeiten zurück. Auftragszahlen für leicht ersetzbare Arbeiten wie Schreib- oder Grafikarbeiten sind aufgrund der Einführung generativer KI bis zu 30 Prozent zurückgegangen. Bei verbleibenden Aufträgen steigen die Anforderungen, also die Komplexität der Aufträge – sie werden zugleich aber auch besser dotiert. Weiter- und Fortbildungsmaßnahmen unerlässlich – insbesondere für Frauen und Ältere, die KI deutlich weniger am Arbeitsplatz nutzen als Männer und Jüngere." (Textauszug, IAB-Doku)
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Literaturhinweis
KI: Skepsis im Arbeitsalltag (2024)
Heider-Willms, Angela;Zitatform
Heider-Willms, Angela (2024): KI: Skepsis im Arbeitsalltag. In: Personalwirtschaft, Jg. 50, H. 9, S. 74-75.
Abstract
"Wann ist der Einsatz von Künstlicher Intelligenz in der Personalarbeit sinnvoll? Und was für einen Einfluss hat diese auf die Arbeitskultur? Damit beschäftigen sich zwei aktuelle Umfragen." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan (2024)
Zitatform
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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Literaturhinweis
Künstliche Intelligenz als Co-Pilot - Warum Unternehmen im Fahrersitz bleiben müssen (2024)
Hemel, Ulrich; Rusche, Christian; Leibrock, Edeltraud; Nüßgen, Alexander; Metzler, Christoph; Ruschitzka, Margot;Zitatform
Hemel, Ulrich, Edeltraud Leibrock, Christoph Metzler, Alexander Nüßgen, Margot Ruschitzka & Christian Rusche (2024): Künstliche Intelligenz als Co-Pilot - Warum Unternehmen im Fahrersitz bleiben müssen. (IW policy paper / Institut der Deutschen Wirtschaft Köln 2024,01), Köln, 27 S.
Abstract
"In today’s digital era, we are witnessing a revolution driven by the progressive development and integration of Artificial Intelligence (AI) into all aspects of life. This article sheds light on this transformation by highlighting the remarkable advancements and the growing significance of AI for society and economy. The article is divided into several chapters that illuminate various dimensions of AI integration in society and economy. Firstly, the article elaborates that AI enables not only productivity enhancements and efficiency gains but also serves as the foundation for innovations that can simplify our daily lives. The intelligent automation of routine tasks provides people with the freedom to engage in more creative and challenging activities, contributing to an improvement in quality of life and prosperity. Secondly, when examining the successful implementation of AI in companies, the article emphasiszes that a well-thought-out AI strategy is necessary to effectively utilize the technology: businesses must invest not only in the relevant tools but also in the training of their employees. Comprehensive AI competence within the workforce is crucial for developing innovative solutions and fully harnessing the potential of AI. Thirdly, the development of personnel and competencies represents another essential chapter. The world of work will transform due to AI, leading to new skill requirements for employees. Lifelong learning and continuous training in digital competencies are essential to keep pace with rapid technological advancements. Simultaneously, educational institutions must adapt their curricula to prepare the next generation for a future where AI plays a central role. Based on the insights from conducted analyses, actionable options regarding AI are derived. Regulatory frameworks and ethical guidelines ensure that the advancement and utilization of AI align with societal values and norms. Human-centricity remains paramount, with technology serving as a complement to human actions, enhancing and extending them, but not replacing them. AI presents a dual challenge: On one hand, it offers incredible opportunities for innovation and prosperity; on the other hand, it requires careful control and adaptation at individual, entrepreneurial, and societal levels. By developing critical AI competencies and practicing responsible use, we can fully harness the potential of AI while minimizing potential risks. Understanding AI as a co-pilot in this dynamic environment is the key to setting the course for a future where technology and humans collaborate harmoniously for mutual benefit." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Generative KI in der Hochschulkommunikation: Ergebnisse der 2. Welle (2024)
Zitatform
Henke, Justus (2024): Generative KI in der Hochschulkommunikation. Ergebnisse der 2. Welle. (HoF-Arbeitsberichte 126), Lutherstadt Wittenberg, 42 S.
Abstract
"Diese Studie untersucht erneut die Anwendung und Wahrnehmung generativer KI-Tools in der Hochschulkommunikation im Jahr 2024 und vergleicht die Ergebnisse mit 2023. Hochschulkommunikation umfasst die interne und externe organisationale Kommunikation der Hochschulen. Die Befragung unter deutschen Hochschulen fragte nach Nutzungsmustern, Herausforderungen und Potenzialen dieser Technologien. Die Ergebnisse zeigen, dass die Nutzung von Textgenerierungstools wie ChatGPT deutlich zugenommen hat, während Übersetzungstools wie DeepL weiterhin am häufigsten verwendet werden. Private Hochschulen integrieren generative KI-Tools häufiger und vielfältiger als öffentliche Einrichtungen. Die Zufriedenheit mit diesen Tools hat sich leicht verbessert, bleibt jedoch moderat. Im Vergleich zu 2023 zeigen sich spürbare Effizienzgewinne und eine erhöhte Anpassungsfähigkeit an verschiedene Kommunikationskanäle. Herausforderungen wie Faktentreue und Datenschutz bleiben zentrale Themen. Ein offener Dialog, die Etablierung hochschulspezifischer Umgangsweisen und Weiterbildung im Umgang mit generativen KI-Tools sind notwendig, um deren Potenziale und Risiken besser zu verstehen und produktiv für die Hochschulkommunikation zu nutzen. Die Studie betont die Notwendigkeit einer umfassenden Herangehensweise, die technologische Fähigkeiten, operative Bedürfnisse und das sozio-technische Umfeld berücksichtigt, um eine erfolgreiche Integration dieser Tools zu gewährleisten. Die Veränderungen zur Vorjahresstudie zeigen zunehmend positive Auswirkungen auf Arbeitsprozesse, während zentrale Herausforderungen weiterhin bestehen." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Generative AI and the Nature of Work (2024)
Hoffmann, Manuel; Peng, Sida; Nagle, Frank; Xu, Kevin; Boysel, Sam;Zitatform
Hoffmann, Manuel, Sam Boysel, Frank Nagle, Sida Peng & Kevin Xu (2024): Generative AI and the Nature of Work. (CESifo working paper 11479), München, 69 S.
Abstract
"Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid to how AI might change the nature of work itself. How do individuals, especially those in the knowledge economy, adjust how they work when they start using AI? Using the setting of open source software, we study individual level effects that AI has on task allocation. We exploit a natural experiment arising from the deployment of GitHub Copilot, a generative AI code completion tool for software developers. Leveraging millions of work activities over a two year period, we use a program eligibility threshold to investigate the impact of AI technology on the task allocation of software developers within a quasi-experimental regression discontinuity design. We find that having access to Copilot induces such individuals to shift task allocation towards their core work of coding activities and away from non-core project management activities. We identify two underlying mechanisms driving this shift - an increase in autonomous rather than collaborative work, and an increase in exploration activities rather than exploitation. The main effects are greater for individuals with relatively lower ability. Overall, our estimates point towards a large potential for AI to transform work processes and to potentially flatten organizational hierarchies in the knowledge economy." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Does robotization improve the skill structure? The role of job displacement and structural transformation (2024)
Zitatform
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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Literaturhinweis
Potenziale Generativer KI für den Mittelstand: Wie große KI-Modelle die Arbeitswelt verändern (2024)
Hölzle, Katharina ; Riedel, Oliver; Kaiser, Simone; Peissner, Matthias; Haner, Udo-Ernst; Renner, Thomas; Engelbach, Matthias; Uhler, Lydia; Mackensen, Jan; Mozer, Pia; Dworschak, Bernd; Bauer, Wilhelm; Drawehn, Jens; Wulf, Jessica; Bienzeisler, Bernd; Renner, Thomas; Beinhauer, Wolfgang; Klau, Dennis; Kintz, Maximilien;Zitatform
Hölzle, Katharina, Oliver Riedel, Wilhelm Bauer & Thomas Renner (Hrsg.) Kaiser, Simone, Matthias Peissner, Udo-Ernst Haner, Matthias Engelbach, Lydia Uhler, Jan Mackensen, Pia Mozer, Bernd Dworschak, Jens Drawehn, Jessica Wulf, Bernd Bienzeisler, Thomas Renner, Wolfgang Beinhauer, Dennis Klau & Maximilien Kintz (sonst. bet. Pers.) (2024): Potenziale Generativer KI für den Mittelstand. Wie große KI-Modelle die Arbeitswelt verändern. Stuttgart, 72 S. DOI:10.24406/publica-2246
Abstract
"Seit der Veröffentlichung von ChatGPT im November 2022 haben die Entwicklungen im Bereich Generative KI deutlich an Fahrt aufgenommen. In kurzer Abfolge wurden - und werden immer noch - neue Modelle und Funktionen vorgestellt. Zunehmend zeichnen sich breite Einsatzmöglichkeiten in den Unternehmen ab, mit einem hohen zu erwartenden Nutzenpotenzial. Vor allem für mittelständische Unternehmen stellt es eine Herausforderung dar, die Bedeutung der Entwicklungen einzuschätzen und eine strukturierte Vorgehensweise zum Thema Generative KI zu definieren und umzusetzen. Das Ministerium für Wirtschaft, Arbeit und Tourismus Baden-Württemberg hat das Fraunhofer IAO beauftragt, mittels einer Studie eine Orientierungshilfe zu den aktuellen Entwicklungen zu bieten und konkrete Empfehlungen für den Umgang mit Generativer KI zu geben. Ein vielköpfiges Autorenteam des Fraunhofer IAO aus verschiedenen Forschungsbereichen hat, neben einer ausführlichen Literaturrecherche, 48 Expertinnen und Experten im Bereich Generativer KI zu ihren Einschätzungen befragt. Es wurden sowohl Forschungseinrichtungen, KI-Anbieter, Dienstleister als auch Anwenderunternehmen miteinbezogen. Das Ergebnis der Recherche und Befragung liegt in Form dieser Studie vor, die einen Beitrag zum bewussten und zielgerichteten Umgang mit Generativer KI in den Unternehmen leisten soll." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Demographic change, secular stagnation, and inequality: automation as a blessing? (2024)
Zitatform
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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Literaturhinweis
Industrial robots, and information and communication technology: the employment effects in EU labour markets (2024)
Zitatform
Jestl, Stefan (2024): Industrial robots, and information and communication technology: the employment effects in EU labour markets. In: Regional Studies, Jg. 58, H. 11, S. 1981-1998. DOI:10.1080/00343404.2023.2292259
Abstract
"This paper explores the effects of industrial robots and information and communication technology (ICT) on regional employment in European Union countries. The empirical analysis relies on a harmonized comprehensive regional dataset that combines business statistics and national and regional accounts data. This rich dataset enables us to provide detailed insights into the employment effects of automation and computerisation in EU regions for the period 2001–16. The results suggest relatively weak effects on regional total employment dynamics. However, industrial robots show negative employment effects in local manufacturing industries and positive employment effects in local non-manufacturing industries. While the negative effect is concentrated in particular local manufacturing industries, the positive effect has operated in local service industries. Information technology investments show positive employment effects in local manufacturing industries and some individual local service industries, while communication technology investments are shown to be irrelevant for employment dynamics. In contrast, software and database investments have had a predominantly negative association with local employment." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Wie Roboter die Welt (und das Wirtschaften) verändern: Ein Überblick über Daten, Forschungsergebnisse und wirtschaftspolitische Strategien (2024)
Zitatform
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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Literaturhinweis
Neurodivergent Employees: AI's Role in New Work Challenges: Exploring Neurodiverse Team Dynamics in the Era of New Work: Leveraging AI for Inclusive Environments (2024)
Keil, Mareike Victoria; Ketzer, Dominic;Zitatform
Keil, Mareike Victoria & Dominic Ketzer (2024): Neurodivergent Employees: AI's Role in New Work Challenges. Exploring Neurodiverse Team Dynamics in the Era of New Work: Leveraging AI for Inclusive Environments. Mannheim, 20 S.
Abstract
"Disruptive change has driven the digitalization and transformation of work structures in the wake of the Covid-19 pandemic, with new types of work models increasingly finding their way into familiar work structures with lasting impact. This has triggered a rapid development as part of the New Work megatrend, which, alongside challenges such as teleworking, has created great opportunities such as better integration of individuals and certain groups of people, e.g. people with disabilities, into the primary labor market. Neurodiverse teams face particular challenges due to the changing workplace, especially in terms of communication, self-organization and working practices. This paper addresses these challenges and proposes solutions based on artificial intelligence (AI) to ensure the competitiveness of companies in the implementation of New Work methods and models and to counteract the shortage of skilled workers." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
KI-Kompetenzen gefragt: Studie zeigt tendenziell steigende Nachfrage in Stellenanzeigen (Interview) (2024)
Zitatform
Keitel, Christiane; Michael Stops & Lennert Peede (interviewte Person) (2024): KI-Kompetenzen gefragt: Studie zeigt tendenziell steigende Nachfrage in Stellenanzeigen (Interview). In: IAB-Forum H. 27.11.2024. DOI:10.48720/IAB.FOO.20241127.01
Abstract
"In den letzten Jahren gab es eine Vielzahl von Innovationen im Bereich der künstlichen Intelligenz (KI). Die öffentliche Debatte schwankt zwischen der Befürchtung, dass viele Tätigkeiten künftig nicht mehr von Menschen erledigt werden und Arbeitsplätze wegfallen, und der Hoffnung, dass neue Tätigkeitsfelder und damit eine neue Qualität von Arbeit entstehen. In einer Studie untersuchen die IAB-Forscher Michael Stops und Lennert Peede unter anderem anhand einer Analyse von Stellenanzeigen aus den Jahren 2015 bis 2019, wie sich KI-Technologien in dieser frühen Phase bereits auf die Arbeitsnachfrage und die Beschäftigung auf Betriebsebene auswirkten." (Autorenreferat, IAB-Doku)
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Literaturhinweis
No Thanks, Dear AI! Understanding the Effects of Disclosure and Deployment of Artificial Intelligence in Public Sector Recruitment (2024)
Zitatform
Keppeler, Florian (2024): No Thanks, Dear AI! Understanding the Effects of Disclosure and Deployment of Artificial Intelligence in Public Sector Recruitment. In: Journal of Public Administration Research and Theory, Jg. 34, H. 1, S. 39-52. DOI:10.1093/jopart/muad009
Abstract
"Applications based on artificial intelligence (AI) play an increasing role in the public sector and invoke political discussions. Research gaps exist regarding the disclosure effects—reactions to disclosure of the use of AI applications—and the deploymenteffect—efficiency gains in data savvy tasks. This study analyzes disclosure effects and explores the deployment of an AI application in a preregistered field experiment (n = 2,000) co-designed with a public organization in the context of employer-driven recruitment. The linear regression results show that disclosing the use of the AI application leads to significantly less interest in an offer among job candidates. The explorative analysis of the deployment of the AI application indicates that the person–job fit determined by the leaders can be predicted by the AIapplication. Based on the literature on algorithm aversion and digital discretion, this study provides a theoretical and empirical disentanglement of the disclosure effect and the deployment effect to inform future evaluations of AI applications in the public sector. It contributes to the understanding of how AI applications can shape public policy and management decisions, and discusses the potential benefits and downsides of disclosing and deploying AI applications in the public sector and in employer-driven recruitment." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Die Nutzung von Künstlicher Intelligenz in der deutschen Wirtschaft (2024)
Zitatform
Kerkhof, Anna, Thomas Licht, Manuel Menkhoff & Klaus Wohlrabe (2024): Die Nutzung von Künstlicher Intelligenz in der deutschen Wirtschaft. In: Ifo-Schnelldienst, Jg. 77, H. 8, S. 39-43.
Abstract
"Künstliche Intelligenz (KI) hat sich zu einem zentralen Treiber der modernen Wirtschaft entwickelt. Insbesondere in Deutschland transformiert KI eine Vielzahl von Branchen – von der Automobilindustrie bis hin zur Finanzbranche – und beeinflusst maßgeblich strategische Entscheidungen und Kundeninteraktionen. Die Europäische Verordnung über Künstliche Intelligenz, die im August 2024 in Kraft getreten ist, verfolgt einen risikobasierten Ansatz zur Regulierung von KI-Systemen, um hohe Sicherheits- und Ethikstandards zu gewährleisten. Trotz der regulatorischen Herausforderungen hat die KI-Nutzung in deutschen Unternehmen im vergangenen Jahr stark zugenommen: Der Anteil der Unternehmen, die angeben, KI zu nutzen, stieg von 13,3 % im Juni 2023 auf 27 % im Folgejahr. Besonders im Verarbeitenden Gewerbe nutzen 31 % der Unternehmen KI. Die Mehrheit der Unternehmen erwartet positive Produktivitätseffekte durch KI, mit geschätzten Produktivitätssteigerungen von 8 % für das eigene Unternehmen und gesamtwirtschaftlich 12 % in den nächsten fünf Jahren. Insgesamt zeigt sich, dass KI in Deutschland zunehmend als Schlüsseltechnologie wahrgenommen wird, die wesentliche Wachstumspotenziale für die Zukunft bietet." (Textauszug, IAB-Doku)
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Literaturhinweis
Automation and Offshoring on Wage Inequality in Japan (2024)
Kikuchi, Shinnosuke; Kikuchi, Shinnosuke;Zitatform
Kikuchi, Shinnosuke (2024): Automation and Offshoring on Wage Inequality in Japan. (RIETI discussion paper 24046), Tokyo, 24 S.
Abstract
"I examine the effect of task displacement from automation technology and offshoring on wage inequality using data for Japan since 1980. First, I do not find evidence that task displacement from automation increases wage inequality, which contrasts with the finding for the US. Second, I find that the rise in offshoring has distributional consequences and is progressive after the mid-1990s. The surge in offshoring is concentrated in industries where ex-ante low-wage workers work and disproportionally increases their wages. This increase in wages is due to the increases in monthly payroll, decreases in hours worked, decreases in employment rate, and decreases in the share of offshorable occupations." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The impact of robots on labor demand: evidence from job vacancy data in South Korea (2024)
Zitatform
Kim, Hyejin (2024): The impact of robots on labor demand: evidence from job vacancy data in South Korea. In: Empirical economics, Jg. 67, H. 3, S. 1185-1209. DOI:10.1007/s00181-024-02585-0
Abstract
"The debate about the impact of robots on employment has been lively. In this paper, I examine the effect of robots on local labor demand in South Korea, one of the most technologically advanced countries in terms of robotics. Using the regional variation in robot exposure constructed from national industry-level robot adoption data and the initial distribution of industrial employment in cities, I find that robots did not reduce local labor demand. However, I estimate declines in labor demand in the manufacturing sector and routine jobs. An increase in one robot per 1000 workers in terms of exposure to robots is correlated with a decline in the job vacancy growth rate of 2.6%p in the manufacturing sector and of 2.5%p in routine jobs. No significant relationship is found between robot exposure and labor demand in the service sector or non-routine jobs." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
Economic Policy Challenges for the Age of AI (2024)
Zitatform
Korinek, Anton (2024): Economic Policy Challenges for the Age of AI. (NBER working paper / National Bureau of Economic Research 32980), Cambridge, Mass, 27 S.
Abstract
"This paper examines the profound challenges that transformative advances in AI towards Artificial General Intelligence (AGI) will pose for economists and economic policymakers. I examine how the Age of AI will revolutionize the basic structure of our economies by diminishing the role of labor, leading to unprecedented productivity gains but raising concerns about job disruption, income distribution, and the value of education and human capital. I explore what roles may remain for labor post-AGI, and which production factors will grow in importance. The paper then identifies eight key challenges for economic policy in the Age of AI: (1) inequality and income distribution, (2) education and skill development, (3) social and political stability, (4) macroeconomic policy, (5) antitrust and market regulation, (6) intellectual property, (7) environmental implications, and (8) global AI governance. It concludes by emphasizing how economists can contribute to a better understanding of these challenges." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Is the wage premium on using computers at work gender-specific? (2024)
Zitatform
Kristal, Tali, Efrat Herzberg-Druker & Adena White (2024): Is the wage premium on using computers at work gender-specific? In: Research in Social Stratification and Mobility, Jg. 89. DOI:10.1016/j.rssm.2024.100890
Abstract
"Past research on the relationship between computers and wages has revealed two stylized facts. First, workers who use a computer at work earn higher wages than similar workers who do not (termed as ‘the computer wage premium’). Second, women are more likely to use a computer at work than are men. Given the recognized computer wage premium and women’s advantage in computer use at work, we ask: Is the wage premium on using computers at work gender- or non-gender-specific? Given gendered processes operating at both the occupational and within-occupation levels, we expect that returns to computer usage are gender-bias. This contrasts the skill-biased technological change (SBTC) theory assumption that the theorized pathways through which computers boost earnings are non-gender-specific productivity-enhancing mechanisms. Analyzing occupational data on computer use at work from O*NET attached to the 1979–2016 Current Population Surveys (CPS) and individual-level data from the 2012 Survey of Adult Skills (PIAAC), we find that the computer wage premium is biased in favor of men at the occupation level. We conclude by suggesting that computer-based technologies relate to reproducing old forms of gender pay inequality due to gendered processes that operate mainly at the structural level (i.e., occupations) rather than at the individual level." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Business 5.0: Der Praxis-Guide für Künstliche Intelligenz in Unternehmen - Chancen und Risiken (2024)
Köhler, Thomas R.; Finkeissen, Julia;Zitatform
Köhler, Thomas R. & Julia Finkeissen (2024): Business 5.0. Der Praxis-Guide für Künstliche Intelligenz in Unternehmen - Chancen und Risiken. Frankfurt;New York: Campus Verlag, 253 S.
Abstract
"Endlich ist er da, der Durchbruch für Künstliche Intelligenz (KI) bzw. Artificial Intelligence (AI). Doch Zweifel an der "Universalwaffe" ChatGPT und ähnlichen KI-Systemen sind erlaubt. Thomas R. Köhler und Julia Finkeissen liefern in ihrem neuen Buch eine Bestandsaufnahme der aktuellen Technologien und trennen dabei schonungslos Hype von Wirklichkeit. Sie liefern das Rüstzeug für jede Führungskraft, um KI aktiv im Unternehmen sinnvoll einzusetzen. Business 5.0 zeigt in sieben Schritten, wo und wie KI-Projekte im Unternehmen etabliert werden können, und liefert konkrete Beispiele für unterschiedliche Branchen und Querschnittsfunktionen. Ein nachhaltiger KI-Einsatz im Unternehmen steht dabei im Mittelpunkt." (Autorenreferat, IAB-Doku, © Campus)
Weiterführende Informationen
Inhaltsverzeichnis bei der Deutschen Nationalbibliothek -
Literaturhinweis
Generalisiertes Vertrauen in automatisierten Journalismus: Bedeutung und Einflussfaktoren auf das Vertrauen deutscher Leser*innen (2024)
Körner, Theresa;Zitatform
Körner, Theresa (2024): Generalisiertes Vertrauen in automatisierten Journalismus. Bedeutung und Einflussfaktoren auf das Vertrauen deutscher Leser*innen. Wiesbaden: Springer VS, 279 S. DOI:10.1007/978-3-658-42735-1
Abstract
"In dieser Arbeit geht es um die Frage, wie Leser:innen in Deutschland automatisiert generierte Nachrichten wahrnehmen und welche Bedeutung sie den Verfahren im Journalismus zuschreiben. Im Mittelpunkt steht die Frage, ob das Publikum dem automatisierten Journalismus vertraut und welche Einflussfaktoren bei dieser Entscheidung eine Rolle spielen. Ein Mindestmaß an Vertrauen der Bevölkerung in Journalismus ist wichtig für die Stabilität demokratischer Gesellschaften. In der Forschung ist bisher wenig thematisiert, ob Medieninnovationen wie die automatisierte Berichterstattung Einfluss auf das generalisierte Vertrauen der Lesenden haben. Zudem gibt es wenig Wissen über den Umgang mit dem, sowie über die Wahrnehmung und die Bewertung des automatisierten Journalismus durch verschiedene Publika. Basierend auf der Operationalisierung verschiedener Vertrauensbeziehungen und der Aufarbeitung des Forschungsstands zur bewerteten Glaubwürdigkeit computergenerierter Nachrichtentexte wurde ein Modell entwickelt, das mögliche Einflussfaktoren auf die Vertrauensbewertung des automatisierten Journalismus darstellt sowie Raum für die Exploration weiterer Faktoren lässt. Zur empirischen Überprüfung wurden Focus Groups mit gezielt rekrutierten Leser:innen eingesetzt: Neben einer heterogen gemischten Focus Group haben einmal Personen mit hoher Technikaffinität und Vorwissen zu Verfahren der Künstlichen Intelligenz sowie einmal Personen mit hoher Medienkompetenz teilgenommen. Die Studienergebnisse zeigen, dass es keine monokausalen Antworten auf die Frage nach dem Vertrauen der Lesenden in automatisierten Journalismus gibt. Grundsätzlich stehen sie dem Technologieeinsatz neutral und gleichzeitig neugierig sowie – vor allem mit Blick auf die Zukunft – skeptisch gegenüber. Die Teilnehmenden fordern einen transparenten Umgang der Medienorganisationen mit automatisierter Berichterstattung und wollen mehr Informationen zum Einsatz, zur Verbreitung und zur Technologie haben. Als Einflussfaktoren auf die Vertrauensbewertung wurden ausgewählte Personen- sowie Text- und Publikationsmerkmale und Eigenschaften des Untersuchungsgegenstands getestet. Hohe Relevanz haben erkennbar die Angst vor gezielter Manipulation, die individuellen Vorstellungen über Künstliche Intelligenzen sowie die Kontingenz von Texten. Die Bedeutung dieser Studie besteht darin, dass sie das theoretische Verständnis von Vertrauen in Journalismus erweitert sowie die Wahrnehmung des automatisierten Journalismus vertieft. Außerdem wird das empirische Verständnis der Bewertung und Einordnung des Publikums der automatisiert generierten Berichterstattung durch die Studienergebnisse exploriert." (Autorenreferat, IAB-Doku, © Springer)
Beteiligte aus dem IAB
Körner, Theresa; -
Literaturhinweis
Who will be the workers most affected by AI?: A closer look at the impact of AI on women, low-skilled workers and other groups (2024)
Lane, Marguerita;Zitatform
Lane, Marguerita (2024): Who will be the workers most affected by AI? A closer look at the impact of AI on women, low-skilled workers and other groups. (OECD Artificial Intelligence Papers 26), Paris, 60 S. DOI:10.1787/14dc6f89-en
Abstract
"This paper examines how different socio-demographic groups experience AI at work. As AI can automate non-routine, cognitive tasks, tertiary educated workers in “white-collar” occupations will likely face disruption, even if empirical analysis does not suggest that overall employment levels have fallen due to AI, even in “white-collar” occupations. The main risk for those without tertiary education, female and older workers is that they lose out due to lower access to AI-related employment opportunities and to productivity-enhancing AI tools in the workplace. By identifying the main risks and opportunities associated with different socio-demographic groups, the ultimate aim is to allow policy makers to target supports and to capture the benefits of AI (increased productivity and economic growth) without increasing inequalities and societal resistance to technological progress." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The Artificial Recruiter: Risks of Discrimination in Employers’ Use of AI and Automated Decision‐Making (2024)
Zitatform
Larsson, Stefan, James Merricks White & Claire Ingram Bogusz (2024): The Artificial Recruiter: Risks of Discrimination in Employers’ Use of AI and Automated Decision‐Making. In: Social Inclusion, Jg. 12. DOI:10.17645/si.7471
Abstract
"Extant literature points to how the risk of discrimination is intrinsic to AI systems owing to the dependence on training data and the difficulty of post hoc algorithmic auditing. Transparency and auditability limitations are problematic both for companies’ prevention efforts and for government oversight, both in terms of how artificial intelligence (AI) systems function and how large-scale digital platforms support recruitment processes. This article explores the risks and users’ understandings of discrimination when usingAI and automated decision-making (ADM) in worker recruitment. We rely on data in the form of 110 completed questionnaires with representatives from 10 of the 50 largest recruitment agencies in Sweden and representatives from 100 Swedish companies with more than 100 employees (“major employers”). In this study, we made use of an open definition of AI to accommodate differences in knowledge and opinion around how AI and ADM are understood by the respondents. The study shows a significant difference between direct and indirect AI and ADM use, which has implications for recruiters’ awareness of the potential for bias or discrimination in recruitment. All of those surveyed made use of large digital platforms like Facebook and LinkedIn for their recruitment, leading to concerns around transparency and accountability—not least because most respondents did not explicitly consider this to be AI or ADM use. We discuss the implications of direct and indirect use in recruitment in Sweden, primarily in terms of transparency and the allocation of accountability for bias and discrimination during recruitment processes." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation, Bargaining Power, and Labor Market Fluctuations (2024)
Zitatform
Leduc, Sylvain & Zheng Liu (2024): Automation, Bargaining Power, and Labor Market Fluctuations. In: American Economic Journal. Macroeconomics, Jg. 16, H. 4, S. 311-349. DOI:10.1257/mac.20220181
Abstract
"We argue that the threat of automation weakens workers’ bargaining power in wage negotiations, dampening wage adjustments and amplifying unemployment fluctuations. We make this argument based on a business cycle model with labor market search frictions, generalized to incorporate automation decisions. In the model, procyclical automation threats create endogenous real wage rigidity that amplifies labor market fluctuations. The automation mechanism is consistent with empirical evidence. It is also quantitatively important for explaining the large volatilities of unemployment and vacancies relative to that of real wages, a puzzling observation through the lens of standard business cycle models." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Reshoring, Automation, and Labor Markets Under Trade Uncertainty (2024)
Zitatform
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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Literaturhinweis
Bedarfsermittlung Zukunft Mittelstand-Digital Vergabenummer 331-2022-15 PT 6681119: Studie für den DLR Projektträger im Rahmen der Projektträgerschaft „Mittelstand-Digital“ (2024)
Zitatform
Lerch, Christian, Elna Schirrmeister, Angela Jäger, Daniel Berner & Philipp Köbe (2024): Bedarfsermittlung Zukunft Mittelstand-Digital Vergabenummer 331-2022-15 PT 6681119. Studie für den DLR Projektträger im Rahmen der Projektträgerschaft „Mittelstand-Digital“. Köln, 117 S.
Abstract
"Diese Studie im Auftrag des DLR-PT untersucht ergebnisoffen die Herausforderungen und Bedarfe des Mittelstands bei der Digitalisierung. Sie geht verschiedenen Fragestellungen nach: Wie ist der Stand der Digitalisierung im Mittelstand? Welche Unterschiede gibt es? Wie wird die Digitalisierung im Mittelstand vorangetrieben? Vor welchen zukünftigen, absehbaren Herausforderungen steht „der Mittelstand“ bis circa zum Jahr 2030? Welche digitalen Technologien sind für den Mittelstand relevant? Welchen Beitrag leistet die Digitalisierung zur Nachhaltigkeit? Welche Hemmnisse lassen sich bei der Digitalisierung im Mittelstand feststellen? Welche Förderbedarfe gibt es aus Sicht der Unternehmen in den nächsten Jahren? Welche Förderungen gibt es bereits? Gibt es vor diesem Hintergrund Lücken bei der Förderung der Digitalisierung im Mittelstand? Welche Ansätze gibt es zur zukünftigen Stärkung der Digitalisierung im Mittelstand?" (Textauszug, IAB-Doku)
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Literaturhinweis
AI Adoption Among German Firms (2024)
Zitatform
Licht, Thomas & Klaus Wohlrabe (2024): AI Adoption Among German Firms. (CESifo working paper 11459), München, 21 S.
Abstract
"This paper examines the adoption of Artificial Intelligence (AI) among German firms, leveraging firm-level data from the ifo Business Survey. We analyze the diffusion of AI across sectors and firm sizes, showing a significant increase in AI usage from 2023 to 2024, particularly in manufacturing and services. The survey data allows us to explore not only sectoral patterns of adoption but also the drivers and barriers that firms face, including firm-specific characteristics and industry dynamics. Additionally, we investigate the role of managerial traits, such as risk tolerance and patience, in shaping AI adoption decisions. Finally, we assess the potential pro-ductivity impacts of AI at the firm level, with a focus on the expected long-term benefits of AI for different sectors of the German economy. Our findings contribute to the growing body of research on AI adoption by providing new evidence from a non-US context, offering valuable insights for both academia and politics." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Embracing artificial intelligence in the labour market: the case of statistics (2024)
Zitatform
Liu, Jin, Kaizhe Chen & Wenjing Lyu (2024): Embracing artificial intelligence in the labour market: the case of statistics. In: Humanities and Social Sciences Communications, Jg. 11. DOI:10.1057/s41599-024-03557-6
Abstract
"In an era marked by rapid advancements in artificial intelligence (AI), the dynamics of the labor market are undergoing significant transformation. A common concern amidst these changes is the potential obsolescence of traditional disciplines due to AI-driven productivity enhancements. This study delves into the evolving role and resilience of these disciplines within the AI-influenced labor market. Focusing on statistics as a representative field, we investigate its integration with AI and its interplay with other disciplines. Analyzing 279.87 million online job postings in the United States from 2010 to 2022, we observed a remarkable 31-fold increase in the demand for AI-specialized statistical talent, diversifying into 932 distinct AI-related job roles. Additionally, our research identified four major interdisciplinary clusters, encompassing 190 disciplines with a statistical focus. The findings also highlight a growing emphasis on specific hard skills within these AI roles and the differences in demand for AI talent in statistics across economic sectors and regions. Contrary to the pessimistic view of traditional disciplines’ survival in the AI age, our study suggests a more optimistic outlook. We recommend that professionals and organizations proactively adapt to AI advancements. Governments and academic institutions should collaborate to foster interdisciplinary skill development and evaluation for AI talents, thereby enhancing the employability of individuals from traditional disciplines and contributing to broader economic growth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Generative AI: Catalyst for Growth or Harbinger of Premature De-Professionalization? (2024)
Zitatform
Liu, Yan (2024): Generative AI. Catalyst for Growth or Harbinger of Premature De-Professionalization? (Policy research working paper 10915), Washington, DC, 60 S.
Abstract
"This paper presents a multi-sector growth model to elucidate the general equilibrium effects of generative artificial intelligence on economic growth, structural transformation, and international production specialization. Using parameters from the literature, the paper employs simulations to quantify the impacts of artificial intelligence across various scenarios. The paper introduces a crucial distinction between high-skill, highly digitalized, tradable services and low-skill, less digitalized, less-tradable services. The model’s key propositions align with empirical evidence, and the simulations yield novel and sobering predictions. Unless artificial intelligence achieves widespread cross-sector adoption and catalyzes paradigm-shifting innovations that fundamentally reshape consumer preferences, its growth benefits may be limited. Conversely, its disruptive impact on labor markets could be profound. This paper highlights the risk of “premature de-professionalization”, where artificial intelligence likely shrinks the space for countries to generate well-paid jobs in high-skill services. The analysis portends that developing countries failing to adopt artificial intelligence swiftly risk entrapment as commodity exporters, potentially facing massive youth underemployment, diminishing social mobility, and stagnating or even declining living standards. The paper also discusses artificial intelligence ’s broader implications on inequality, exploring multiple channels through which it may exacerbate or mitigate economic disparities." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Job loss and Covid-19: an analysis on the impacts of remote work and automation (2024)
Zitatform
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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Literaturhinweis
KI und der Wandel von Angestelltenarbeit: Zum „blinden Fleck“ der aktuellen Automatisierungsdebatte (2024)
Zitatform
Lühr, Thomas & Tobias Kämpf (2024): KI und der Wandel von Angestelltenarbeit. Zum „blinden Fleck“ der aktuellen Automatisierungsdebatte. In: WSI-Mitteilungen, Jg. 77, H. 2, S. 98-106. DOI:10.5771/0342-300X-2024-2-98
Abstract
"Der Beitrag analysiert den Wandel von Angestelltenarbeit vor dem Hintergrund der digitalen Transformation. Ausgangspunkt ist ein Automatisierungsschub, der durch erweiterte Möglichkeiten der Nutzung Künstlicher Intelligenz (KI) geprägt ist. Auf der Grundlage empirischer Befunde werden die qualitativen Veränderungstendenzen von Arbeit in den Blick genommen, und zwar sowohl aus der Anwenderperspektive der Sachbearbeiter*innen als auch aus der Sicht der hochqualifizierten Entwickler*innen und Implementoren neuer KI-Lösungen. Insgesamt wird ein Strukturwandel von Angestelltenarbeit konstatiert, der nicht nur das Risiko von Jobverlusten, sondern auch Potenziale für eine Aufwertung und Höherqualifizierung hervorbringt und sich im Angestelltenbewusstsein manifestiert. In arbeitspolitischer Perspektive eröffnen sich Anknüpfungspunkte für eine Vorwärtsstrategie im Sinne eines nachhaltigen Umbaus von Beschäftigung." (Autorenreferat, IAB-Doku)
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