Documents automation 369 results

"This study identifies the job attributes, and in particular skills and abilities, which predict the likelihood a job is recently automatable drawing on the Josten and Lordan (2020) classification of automatability, EU labour force survey data and a machine learning regression approach. We find that skills and abilities which relate to non-linear abstract thinking are those that are the safest from automation. We also find that jobs that require ‘people' engagement interacted with ‘brains' are also less likely to be automated. The skills that are required for these jobs include soft skills. Finally, we find that jobs that require physically making objects or physicality more generally are most likely to be automated unless they involve interaction with ‘brains' and/or ‘people'."

"Artificial Intelligence and advanced robotics are transforming how human labour is designed and performed. This report presents types and definitions of AI-based systems and advanced robotics for the automation of tasks, their distribution according to different sectors and a description of the tasks that are impacted the most.
The report also maps existing and potential uses and provides an overview of policies, strategies and programmes at national and international levels concerning these systems for the automation of tasks and occupational health and safety. "

"This short, accessible book seeks to explore the future of work through the views and opinions of a range of expertise, encompassing economic, historical, technological, ethical and anthropological aspects of the debate. The transition to an automated society brings with it new challenges and a consideration for what has happened in the past; the editors of this book carefully steer the reader through future possibilities and policy outcomes, all the while recognising that whilst such a shift to a robotised society will be a gradual process, it is one that requires significant thought and consideration."

"Societies and economies are experiencing deep and intertwined structural changes that may unsettle the perceptions European citizens have of their economic and employment security. Such labour-market perceptions are likely in turn to alter people's political positions. For instance, those worried by labour-market competition may prefer greater social protection to compensate for the accrued risk, or might prefer more closed economies where external borders provide protection (or the illusion of protection). We test these expectations with a conjoint experiment in 13 European countries on European-level social policy, studying how citizens' demands align with parties' political supply. Results broadly corroborate our expectations on the moderating effects of different types of concerns about perceived sources of labour-market competition on the features of preferred European-level social policy."

"This study assesses the potential global exposure of occupations to Generative AI, particularly GPT-4. It predicts that the overwhelming effect of the technology will be to augment occupations, rather than to automate them. The greatest impact is likely to be in high and upper-middle income countries due to a higher share of employment in clerical occupations. As clerical jobs are an important source of female employment, the effects are highly gendered. Insights from this study underline the need for proactive policies that focus on job quality, ensure fair transitions, and that are based on dialogue and adequate regulation."

"This article sets out the case for co-determination in the context of work, with a particular emphasis on why this is mandated in relation to algorithmically managed work and workplaces in particular. Having set out the theoretical case for collective regulation of algorithmic management that includes extensive rights of co-determination, focusing on the power relations implied by algorithmic management for this purpose, the article goes on to explore the current state of collective regulation of algorithmic management in the UK and in Germany. From here, it explores existing EU law mechanisms relating to algorithmic management, highlighting their limits and potential, and identifying how, and in what ways, the blueprint outlined by Adams-Prassl et al in this Special Issue might be further elaborated and improved. The article then presents certain proposals for how to establish conditions conducive to the introduction of co-determination in the EU, both generally and in relation to algorithmic technologies more specifically, while engaging critically with the potential and the limitations of legal, top-down—as opposed to bottom-up—mechanisms to achieve this end."

"Seitdem erschienen zahlreiche wissenschaftliche Studien, um die Beschäftigungseffekte einzelner Technologie(-gruppen) wie der Robotik näher zu untersuchen. Aktuell liegt der Fokus stark auf Anwendungen der Künstlichen Intelligenz (KI), die durch Chatbots wie ChatGPT oder Google Bard in das Bewusstsein der breiten Öffentlichkeit gelangt sind. Im ersten Teil der vorliegenden Studie werden die wissenschaftlichen Papiere über die Arbeitsmarkteffekte von KI dargestellt und Stärken und Schwächen von drei unterschiedlichen Ansätzen diskutiert. Diese nähern sich der Fragestellung i) mittels der Ermittlung der potenziellen Betroffenheit von Tätigkeiten, Aufgaben und Fähigkeiten der Beschäftigten, ii) über die Auswertung von Stellenanzeigen und iii) den Rückgriff auf Befragungsdaten zum Einsatz von KI-Anwendungen. Im zweiten Teil wird der Zusammenhang zwischen dem Einsatz von KI-Verfahren und der tatsächlichen und erwarteten Mitarbeiterentwicklung von Unternehmen am Standort Deutschland empirisch untersucht. Hierfür werden mehrerer Wellen des IW-Zukunftspanels, einer regelmäßigen Befragung von Unternehmen des Industrie-Dienstleistungsverbunds, im Zeitraum zwischen 2019 bis 2022 mit rund 4.300 Beobachtungen von über 2.800 Unternehmen ausgewertet.

In der empirischen Analyse auf Basis des IW-Zukunftspanels zeigt sich kein robuster Zusammenhang zwischen dem Einsatz von KI-Verfahren und der tatsächlichen sowie der erwarteten Mitarbeiterentwicklung auf Unternehmensebene. Die wechselnden Vorzeichen von KI-Verfahren je nach Betrachtungszeitraum könnten auf gegenläufige Wirkungsmechanismen über positive Produktivitäts- und Substitutionseffekte menschlicher Arbeit hindeuten, die in der Literatur diskutiert werden. Um diese stärker voneinander zu trennen, bräuchte es jedoch mehr Informationen über die Art der KI-Anwendungen in den Unternehmen. Zusammengefasst weisen die wissenschaftlichen Befunde in der Literatur bislang nicht auf starke negative Beschäftigungseffekte hin. Es deutet sich vielmehr an, dass KI die menschliche Arbeit bisher weitestgehend ergänzt. Technologische Fortschritte von KI-Verfahren am aktuellen Rand sind jedoch in der Studienlage noch nicht abgebildet, sodass die Forschung zu Beschäftigungseffekten durch KI erst am Anfang steht."

"Contact centers have long been lead innovators in adopting new technologies to restructure jobs and manage workers. Between the 1990s and 2000s, the first wave of digitalization transformed what were then called ‘call centers' through innovations in call volume tracking, automatic call distribution, and electronic monitoring and performance management. 2 The growth of the internet and fiber-optic digital networks enabled the relocation of jobs far from customers through outsourcing and offshoring. Since the mid-2010s – and accelerating in the early 2020s – a new set of technologies have been transforming contact center jobs. This second digital transformation is based on advances in artificial intelligence (AI), enabled by faster network speeds and cloud computing. A range of new AI-based tools are being used to automate customer service and sales via chatbots and voicebots, to perform a growing range of back-office tasks, and to enable more intensive and tailored forms of remote monitoring, coaching, training, and scheduling."

"Using survey data from 20 European countries, we construct novel worker-level indices of routine, abstract, social, and physical tasks across 20 European countries, which we combine with industry-level robotization exposure. Our conceptual framework builds on the insight that robotization simultaneously replaces, creates, and modifies workers' tasks and studies how these forces impact workers' job content. We rely on instrumental variable techniques and show that robotization reduces physically demanding activities. Yet, this reduction in manual work does not coincide with a shift to more challenging and interesting tasks. Instead, robotization makes workers' tasks more routine, while diminishing the opportunities for cognitively challenging work and human contact. The adverse impact of robotization on social tasks is particularly pronounced for highly skilled and educated workers. Our study offers a unique worker-centric viewpoint on the interplay between technology and tasks, highlighting nuances that macro-level indicators overlook. As such, it sheds light on the mechanisms underpinning the impact of robotization on labor markets."

"Artificial intelligence systems are developing very rapidly in all areas. This is particularly true in the case of work, where we are seeing their use in the robotisation of industrial production or the automation of certain functions in services (from chatbots to robotic process automation). In the context of a prospective study devoted to the use of artificial intelligence for occupational risk prevention, a very diverse project group was set up: occupational health practitioners, artificial intelligence specialists, lawyers, futurists, sociologists, and everyday users of artificial intelligence techniques. Using the method of contrasting scenarios, this project group successively documented variables likely to influence the use of artificial intelligence in the service of occupational health and safety, put forward hypotheses on their possible development over the next ten to fifteen years, and constructed scenarios. These relatively general scenarios were then adapted specifically to the subject studied, in particular during seminars devoted to specific uses (possible uses of artificial intelligence tools in epidemiology and accidentology, technologies for securing working environments using artificial intelligence, advanced robotics using artificial intelligence). Based on all the material produced during the study, the study finally resulted in recommendations of the project group on the use of AI in occupational risk prevention proposed for discussion. The subject is indeed of interest to the whole community of practitioners involved in occupational risk prevention whose practices will certainly be affected by these new technological developments."