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    <title>EconStor Community:</title>
    <link>https://hdl.handle.net/10419/299619</link>
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        <rdf:li rdf:resource="https://hdl.handle.net/10419/300311" />
        <rdf:li rdf:resource="https://hdl.handle.net/10419/301119" />
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    <dc:date>2026-10-16T08:59:56Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/300311">
    <title>Artificial intelligence in Industry 4.0: Implications for occupational safety and health</title>
    <link>https://hdl.handle.net/10419/300311</link>
    <description>Title: Artificial intelligence in Industry 4.0: Implications for occupational safety and health
Authors: Bérastégui, Pierre
Abstract: Artificial intelligence (AI) has long been hailed as a transformative force set to revolutionise various aspects of our lives, including the way we work. Advances in complementary fields such as big data, cloud computing and the internet of-things have seen the emergence of new ways of organising the means of production. Behind these new ecosystems, often referred to using '4.0' terms, lies a complex web of intricate technologies, bringing with it a unique set of risks and challenges. This working paper analyses the role of AI in the context of Industry 4.0 (I4.0), with a specific focus on occupational safety and health (OSH) implications. Section 1 situates AI within the framework of I4.0 and provides a brief overview of application-pull and technology-push factors inducing a need for changes. Section 2 delves into ways in which an AI system may unexpectedly fail and discusses trends in AI accidents based on available data. Section 3 explains how the growing convergence of information and operational technology make organisations more vulnerable to cyber-physical attacks, ultimately putting workers' safety at risk. Section 4 provides a critical assessment of the various principles put forward to ensure proper human oversight. Section 5 discusses how the implementation of AI systems may influence workers' autonomy and, in this way, compromise workers' safety and health. Finally, Section 6 describes the poor working conditions of data workers behind AI systems.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/301119">
    <title>Job quality and digitalisation</title>
    <link>https://hdl.handle.net/10419/301119</link>
    <description>Title: Job quality and digitalisation
Authors: Piasna, Agnieszka
Abstract: This working paper examines the impact on job quality of new digital technologies at work. It applies the multidimensional framework of the ETUI Job Quality Index to an analysis of the 27 EU Member States and data from the 2021 European Working Conditions Telephone Survey. The effects of digitalisation are conceptualised on the basis of two theoretical approaches: one considers the impact of computerised systems and algorithmic management on task allocation, working time and work intensity; the other looks at digitalisation at work in terms of job demands and resources. The analysis examines how the use of computerised systems at work and their influence on the content and organisation of work affect different dimensions of job quality and how this may differ across groups of workers.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/301120">
    <title>Towards workers' environmental rights: An analysis of EU labour and environmental law</title>
    <link>https://hdl.handle.net/10419/301120</link>
    <description>Title: Towards workers' environmental rights: An analysis of EU labour and environmental law
Authors: Arabadjieva, Kalina; Tomassetti, Paolo
Abstract: Building on the ongoing discussion on the labour-environment nexus in labour law and other areas of scholarship, in this paper we systematically analyse EU legal instruments in the areas of labour law and environmental law, seeking to assess how these normative and policy domains are related to each other. We draw on the explicit and implicit intersections between these two domains when it comes to relevant EU legislation, in order to identify and conceptualise early examples of what we call 'workers' environmental rights'. These rights include individual and collective rights whose exercise contributes simultaneously to labour and environmental sustainability. Where such 'workers' environmental rights' are not explicitly set out in legislation, we provide insights into how they could be construed via judicial interpretation, as well as on how they could be integrated in future EU and national legislation through statutory provisions or collective agreements.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/302241">
    <title>Disability-based labour market inequalities</title>
    <link>https://hdl.handle.net/10419/302241</link>
    <description>Title: Disability-based labour market inequalities
Authors: Pettinicchio, David; Maroto, Michelle
Abstract: Despite changing attitudes around disability over time, people with disabilities still face large barriers to labour market participation. We apply a sociological framework that considers both supply- and demand-side explanations for labour market inequality to help understand the continuing earnings and employment disparities experienced by people with disabilities across countries. Specifically, we review reemployment disparities across different measures of disability, address sets of individual-level and structural explanations for these disparities, discuss how these explanations interact, and apply them to examples related to intersectionality, unionisation, contingent work, and employment in times of crisis. Paid employment is central to people's social and economic wellbeing within liberal market-based economies, making it important to understand the many dimensions of labour market inequality.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
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