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Simons, Wouter, Alessandro Turrini & Lara Vivian (2024): Artificial Intelligence: Economic Impact, Opportunities, Challenges, Implications for Policy. (European economy. Discussion paper 210), Brüssel, 29 S.

Abstract

"This discussion paper presents the key features of Artificial Intelligence (AI), highlighting the main differences with respect to previous IT and digital technologies. It presents the most relevant facts about AI diffusion across EU countries, and discusses the main economic implications, focusing especially on its impact on productivity and labour markets. While AI presents a formidable opportunity, it also entails major challenges, with implications for policy. This paper focuses on policies to remove bottlenecks to AI development and adoption, regulatory policies, competition policy, policies to deal with labour market and distributive implications." (Author's abstract, IAB-Doku) ((en))

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Steinhau, Henry, Matthieu Binder, Merlin Münch & Lena Biskup (2024): Künstliche Intelligenz und Beschäftigte im Journalismus. (Working paper Forschungsförderung / Hans Böckler Stiftung 345), Düsseldorf, 55 S.

Abstract

"In dieser Kurzstudie untersuchen die Autor*innen den Einsatz von Künstlicher Intelligenz (KI) im Journalismus aus der Perspektive der Beschäftigten. Mithilfe von Expert*innenInterviews, der Auswertung wissenschaftlicher Literatur und einer Textanalyse von selbstverpflichtenden KI-Richtlinien und Positionspapieren erörtern sie wesentliche Fragen: Wie nehmen Journalist*innen die Verwendung von KI-gestützten Werkzeugen wahr? Welche Folgen erwarten sie für ihren Arbeitsalltag und ihr Berufsbild? Wie werden Betriebsräte einbezogen? Als Quintessenz formulieren sie sechs praxisorientierte Handlungsempfehlungen." (Autorenreferat, IAB-Doku)

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Suleyman, Mustafa (2024): The Coming Wave. Künstliche Intelligenz, Macht und das größte Dilemma des 21. Jahrhunderts. München: Beck, 377 S.

Abstract

"Die Menschheitsgeschichte kennt Innovationsschübe, die unaufhaltsam wie ein Tsunami alles verändern - die landwirtschaftliche Revolution, die Dampfmaschine, das Internet. Künstliche Intelligenz ist die nächste große Welle, die Coming Wave, die auf uns zurollt, und wir sind darauf nicht vorbereitet. Als Mitgründer von DeepMind weiß Mustafa Suleyman wie nur wenige andere, was die neuen Technologien können und was sie anzurichten vermögen. In seinem wegweisenden, vielgelobten Buch verortet der KI-Pionier die kommende Welle in der Geschichte der Menschheit, spielt die politischen und gesellschaftlichen Folgen der neuen Technologien durch, und stellt sich dem größten Dilemma des 21. Jahrhunderts: wie wir von ihnen profitieren, ohne die Kontrolle zu verlieren. Bald werden wir in unserem täglichen Leben von KI umgeben sein. Sie wird unseren Alltag organisieren, unsere Wirtschaft prägen, und sogar Kernaufgaben der Staatsverwaltung übernehmen. Als Mitgründer von DeepMind hat Mustafa Suleyman viele Jahre im Zentrum der KI-Revolution gearbeitet. Das kommende Jahrzehnt wird nach seiner Einschätzung von rasanten technologischen Sprüngen geprägt sein, von neuen technologischen Möglichkeiten, über deren Folgen und Risiken wir noch kein klares Bild haben. Eines aber wissen wir: Wir brauchen die KI, um die Herausforderungen zu meistern, vor denen wir stehen, etwa den Klimawandel. Gleichzeitig bergen die neuen Technologien Gefahren, wie sie von keiner vorherigen Fortschrittswelle ausgingen, bis hin zur Auflösung von Staaten und einer Verdrängung des Menschen. Was macht man mit einer Welle, die auf den Strand zurast und sich nicht aufhalten lässt? Man versucht sie zu kanalisieren. Genau das ist das Anliegen dieses Buches: Inmitten immer intensiver werdender geopolitischer Konflikte den schmalen Grat zu finden, auf dem wir die Früchte der Technologie ernten, ohne ihr zum Opfer zu fallen. Das ist die zentrale Aufgabe unserer Zeit. "Unsere Zukunft hängt von den neuen Technologien ab, ist gleichzeitig aber durch sie gefährdet." Was KI für die Zukunft der Menschheit bedeutet Alle, die heute leben, sind betroffen DAS Buch zu Risiken, Chancen und Folgen der neuen Technologien Mustafa Suleyman ist Mitbegründer von DeepMind und einer der Pioniere der KI-Industrie. Wie wir die Oberhand behalten: Mustafa Suleyman über die Kernfrage unseres Jahrhunderts Ein 12-Punkte-Plan für den Umgang mit KI" (Autorenreferat, IAB-Doku, © C.H. Beck)

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Tirabeni, Lia (2024): Bounded Well-Being: Designing Technologies for Workers' Well-Being in Corporate Programmes. In: Work, Employment and Society, Jg. 38, H. 6, S. 1506-1527. DOI:10.1177/09500170231203113

Abstract

"This article examines the relationship between workers’ well-being and digitalisation at work. It is based on the findings of a qualitative study carried out in a manufacturing company, and it focuses on the development of a wearable device for well-being. Using the analytical concepts of ‘translation’ and ‘inscription’ taken from Actor-Network Theory, it explores how digital technologies for well-being are designed in corporate programmes and shows how the final technology results from processes of inscription and translation performed by the actors involved in the design phase. The end device embodies a concept of well-being that has been called ‘bounded’ to emphasise how well-being at work is limited by organisational constraints. The article invites a rethinking of hedonic well-being at work as a precondition for eudaimonic well-being so that the human being is understood as a psychophysical unit that is part of a rich social context." (Author's abstract, IAB-Doku) ((en))

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Yilmaz, Erdem Dogukan & Christian Peukert (2024): Who Benefits from AI? Project-Level Evidence on Labor Demand, Operations and Profitability. (CESifo working paper 11321), München, 31 S.

Abstract

"We examine how the adoption of digital automation technology affects labor demand, operations and profitability in the context of the logistics industry. Our data covers 9,300 digital automation projects in a multinational company involving service robots and machine learning-based software from 2019 to 2021, alongside fine-grained labor and operations data. To identify causal effects, we leverage exogenous variation from supply-chain disruptions and travel restrictions during COVID-19 and an import ban on information and communication technologies imposed by the Trump administration. We find that total labor cost increased after the adoption of digital automation technology, attributable to increased labor demand and more reliance on temporary workers. However, managerial hours declined, possibly due to increased efficiency. Furthermore, digital automation technology increased revenue and profit through a reduction in operational cost, improved utilization of warehouse space, and higher profit margins. However, the effects of digital automation technology are not homogeneous. We highlight substantial complementarities between hardware and software technologies. Management units that only use software technology experience only half the increase in revenue and profit." (Author's abstract, IAB-Doku) ((en))

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Zhao, Yong, Da Yin, Lili Wang & Yihua Yu (2024): The rise of artificial intelligence, the fall of human wellbeing? In: International Journal of Social Welfare, Jg. 33, H. 1, S. 75-105. DOI:10.1111/ijsw.12586

Abstract

"Concerns exist regarding the impact on our lives of the rise of artificial intelligence (AI). Using a large dataset of 137 countries over the period 2005–2018 from multiple sources, we estimate the causal effect of AI on individual-level subjective wellbeing. Our identification strategy is inferred from the gravity framework and uses merely the variation in exogenous drivers of a country's AI development. We find a significant negative effect of AI on an individual's wellbeing, in terms of current levels or expectations of future wellbeing. The results are robust to alternative measures of AI, identification strategies, and sampling. Moreover, we find evidence of significant heterogeneity in the impact of AI on individual wellbeing. Further, this dampening effect on individual wellbeing resulting from the use of AI is more prominent among young people, men, high-income groups, high-skilled groups, and manufacturing workers." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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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))

Abstract

"Die Organisation für wirtschaftliche Zusammenarbeit und Entwicklung (OECD) übergab am 11. Juni einen von ihr erstellten Bericht zum Stand der Entwicklung und Nutzung von Künstlicher Intelligenz (KI) in Deutschland an Vertreterinnen und Vertreter der Bundesregierung. In ihrem Bericht hebt die OECD die gute Ausgangsposition Deutschlands für KI hervor und bescheinigt der Bundesregierung, dass die KI-Strategie der Grundstein dafür war, dass sich Deutschland zu einem weltweit führenden Standort für KI – insbesondere im Bereich Forschung – entwickelt hat. Der in Deutschland gewählte menschenzentrierte Ansatz setzt dabei weltweit Maßstäbe für einen verantwortungsvollen Umgang mit KI." (Autorenreferat, IAB-Doku)

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(2024): Assessing potential future artificial intelligence risks, benefits and policy imperatives. (OECD Artificial Intelligence Papers 27), Paris, 68 S. DOI:10.1787/3f4e3dfb-en

Abstract

"The swift evolution of AI technologies calls for policymakers to consider and proactively manage AI-driven change. The OECD’s Expert Group on AI Futures was established to help meet this need and anticipate AI developments and their potential impacts. Informed by insights from the Expert Group, this report distils research and expert insights on prospective AI benefits, risks and policy imperatives. It identifies ten priority benefits, such as accelerated scientific progress, productivity gains and better sense-making and forecasting. It discusses ten priority risks, such as facilitation of increasingly sophisticated cyberattacks; manipulation, disinformation, fraud and resulting harms to democracy; concentration of power; incidents in critical systems and exacerbated inequality and poverty. Finally, it points to ten policy priorities, including establishing clearer liability rules, drawing AI “red lines”, investing in AI safety and ensuring adequate risk management procedures. The report reviews existing public policy and governance efforts and remaining gaps." (Author's abstract, IAB-Doku) ((en))

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(2024): Job Creation and Local Economic Development 2024. The Geography of Generative AI. (Job creation and local economic development [6]), Paris, 189 S. DOI:10.1787/83325127-en

Abstract

"Regions across the OECD face a range of labour market challenges and are undergoing a significant transformation. An ageing workforce, low labour productivity growth, persistent regional disparities, pervasive labor shortages, and new technologies will require both people and places to undergo transitions. This report, Job Creation and Local Economic Development 2024: The Geography of Generative AI, examines the health of regional and local labor markets, including through new estimates on regional labour shortages and their drivers. New tools and technologies, such as Generative AI, could help policymakers address these challenges and seize new opportunities for job creation and local economic growth. This report provides novel evidence of the geography of the impact of Generative AI on jobs across the OECD. It examines which places within countries and types of workers are most exposed to Generative AI and contrasts this with the labor market impact of past waves of technologies that drove automation. Finally, it discusses local and place-based actions and policies for seizing the benefits of Generative AI, such as boosting productivity, mitigating labor shortages and demographic change, as well as for mitigating risks of job displacement." (Author's abstract, IAB-Doku) ((en))

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(2024): Using AI in the workplace : Opportunities, risks and policy responses. (OECD artificial intelligence papers 11), Paris, 15 S. DOI:10.1787/73d417f9-en

Abstract

"AI can bring significant benefits to the workplace. In the OECD AI surveys of employers and workers, four in five workers say that AI improved their performance at work and three in five say that it increased their enjoyment of work. But the benefits of AI depend on addressing the associated risks. Taking the effect of AI into account, occupations at highest risk of automation account for about 27% of employment in OECD countries. Workers also express concerns around increased work intensity, the collection and use of data, and increasing inequality. To support the adoption of trustworthy AI in the workplace, this policy paper identifies the main risks that need to be addressed when using AI in the workplace. It identifies the main policy gaps and offers possible policy avenues specific to labour markets." (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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Agarwal, Ayushi & Sreejith Alathur (2023): Metaverse revolution and the digital transformation: intersectional analysis of Industry 5.0. In: Transforming Government : People, Process and Policy, Jg. 17, H. 4, S. 688-707. DOI:10.1108/TG-03-2023-0036

Abstract

"Purpose: This study aims to investigate metaverse elements affecting digital transformation and examine how the metaverses ’ enabled digital transformation affects Industry 5.0. Design/methodology/approach This paper adopts intersectional research methodologies to understand how metaverse technologies facilitate digital transformation and contribute to Industry 5.0. The Metaverse literature is bibliometrically analyzed to identify the intersection of digital transformation and components of Industry 5.0. Findings The conceptualization of the metaverse, its ecosystem and its enabling technologies are consistent with the human-centric, resilient and sustainable vision of the industrial revolution. The findings show that scientific research into digital transformation contributes to refining potential conflicts and tensions that may arise at the intersection of the metaverse and Industry 5.0. Research limitations/implications Study have significant implications for digital transformation research, as transformation studies help to fine-tune emerging technologies such as the metaverse for the industrial revolution. Based on the findings, the authors have provided a threat model for the Sustainable Metaverse Revolution. Social implications The utility of metaverse technologies in industrial revolutions necessitates the formulation of business model policies that promote the metaverse-enabled digital transformation. Policy recommendations for integrated development approaches are also provided in this paper. Originality/value The metaverse-enabled digital transformation and its implications for the industrial revolution are less reported. The current study addresses the importance of such intersectional studies." (Author's abstract, IAB-Doku) ((en))

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Albanesi, Stefania, António Dias da Silva, Juan F. Jimeno, Ana Lamo & Alena Wabitsch (2023): New Technologies and Jobs in Europe. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 16227), Bonn, 58 S.

Abstract

"We examine the link between labour market developments and new technologies such as artificial intelligence (AI) and software in 16 European countries over the period 2011- 2019. Using data for occupations at the 3-digit level in Europe, we find that on average employment shares have increased in occupations more exposed to AI. This is particularly the case for occupations with a relatively higher proportion of younger and skilled workers. This evidence is in line with the Skill Biased Technological Change theory. While there exists heterogeneity across countries, only very few countries show a decline in employment shares of occupations more exposed to AI-enabled automation. Country heterogeneity for this result seems to be linked to the pace of technology diffusion and education, but also to the level of product market regulation (competition) and employment protection laws. In contrast to the findings for employment, we find little evidence for a relationship between wages and potential exposures to new technologies." (Author's abstract, IAB-Doku) ((en))

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Avery, Mallory, Andreas Leibbrandt & Joseph Vecci (2023): Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech. (Discussion paper / Monash University, Department of Economics 2023-09), Clayton, 69 S.

Abstract

"The use of Artificial Intelligence (AI) in recruitment is rapidly increasing and drastically changing how people apply to jobs and how applications are reviewed. In this paper, we use two field experiments to study how AI in recruitment impacts gender diversity in the male-dominated technology sector, both overall and separately for labor supply and demand. We find that the use of AI in recruitment changes the gender distribution of potential hires, in some cases more than doubling the fraction of top applicants that are women. This change is generated by better outcomes for women in both supply and demand. On the supply side, we observe that the use of AI reduces the gender gap in application completion rates. Complementary survey evidence suggests that this is driven by female jobseekers believing that there is less bias in recruitment when assessed by AI instead of human evaluators. On the demand side, we find that providing evaluators with applicants' AI scores closes the gender gap in assessments that otherwise disadvantage female applicants. Finally, we show that the AI tool would have to be substantially biased against women to result in a lower level of gender diversity than found without AI." (Author's abstract, IAB-Doku) ((en))

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Becker, Marco, Carl Heinz Daube & Ernst Reinking (2023): Industrie 5.0. (EconStor Preprints 270296), Kiel, 12 S.

Abstract

"Spätestens seit der Etablierung von ChatGPT als eine für die breite Masse sowohl der Unternehmen als auch der Bevölkerung gleichermaßen interessante Anwendung der Künstlichen Intelligenz im November 2022 neigt sich die Epoche der Industrie 4.0 dem Ende entgegen. In diesem Working Paper werden die Grenzen der Industrie 4.0 aufgezeigt und die Potenziale der Industrie 5.0 analysiert." (Autorenreferat, IAB-Doku)

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Berg, Janine, Francis Green, Laura Nurski & David A. Spencer (2023): Risks to job quality from digital technologies: Are industrial relations in Europe ready for the challenge? In: European journal of industrial relations, Jg. 29, H. 4, S. 347-365. DOI:10.1177/09596801231178904

Abstract

"We examine job quality effects of new digital technologies, using the European frame of seven job quality domains: Pay, Working Time Quality, Prospects, Skills and Discretion, Work Intensity, Social Environment, and Physical Environment. Theoretical effects are ambivalent across all domains. The analysis of these effects confirms that digital technologies can both improve and harm job quality depending on how they are used. In light of this analysis and to think through the challenge of regulating digital technologies, we review emerging regulations across several European countries. Drawing on the principles of human-centred design, we argue that worker participation is important for securing good job quality outcomes, at both the innovation and adoption stages. We also consider the application of data protection legislation to the regulation of job quality. Overall, the paper extends debate about the future of work beyond employment and pay, on to a consideration of job quality more broadly." (Author's abstract, IAB-Doku) ((en))

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Bertschek, Irene (2023): Jetzt bloß nicht den Anschluss verlieren! – Status quo, Potenziale und Herausforderungen von Künstlicher Intelligenz. In: Wirtschaftsdienst, Jg. 103, H. 8, S. 518-520. DOI:10.2478/wd-2023-0149

Abstract

"Artificial Intelligence (AI) is likely to be the next general purpose technology. The U.S. and China are important players in the development of AI. Germany has a vibrant AI startup scene and is among the first third of EU countries in applying AI technologies. In order not to lose touch with international developments, Germany should work toward creating research- and innovation-friendly framework conditions. Appropriate measures include improving data availability, building AI expertise and enabling flexible regulation." (Author's abstract, IAB-Doku) ((en))

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Bonfiglioli, Alessandra, Rosario Crinò, Gino Gancia & Ioannis Papadakis (2023): Artificial Intelligence and Jobs: Evidence from US Commuting Zones. (CESifo working paper 10685), München, 41 S.

Abstract

"We study the effect of Artificial Intelligence (AI) on employment across US commuting zones over the period 2000-2020. A simple model shows that AI can automate jobs or complement workers, and illustrates how to estimate its effect by exploiting variation in a novel measure of local exposure to AI: job growth in AI-related professions built from detailed occupational data. Using a shift-share instrument that combines industry-level AI adoption with local industry employment, we estimate robust negative effects of AI exposure on employment across commuting zones and time. We find that AI's impact is different from other capital and technologies, and that it works through services more than manufacturing. Moreover, the employment effect is especially negative for low-skill and production workers, while it turns positive for workers at the top of the wage distribution. These results are consistent with the view that AI has contributed to the automation of jobs and to widen inequality." (Author's abstract, IAB-Doku) ((en))

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Broecke, Stijn, Marguerita Lane & Morgan Williams (2023): The impact of AI on the workplace: Main findings from the OECD AI surveys of employers and workers. (OECD social, employment and migration working papers 288), Paris, 156 S. DOI:10.1787/ea0a0fe1-en

Abstract

"New OECD surveys of employers and workers in the manufacturing and finance sectors of seven countries shed new light on the impact that Artificial Intelligence has on the workplace —an under-researched area to date due to lack of data. The findings suggest that both workers and their employers are generally very positive about the impact of AI on performance and working conditions. However, there are also concerns, including about job loss—an issue that should be closely monitored. The surveys also indicate that, while many workers trust their employers when it comes to the implementation of AI in the workplace, more can be done to improve trust. In particular, the surveys show that both training and worker consultation are associated with better outcomes for workers." (Author's abstract, IAB-Doku) ((en))