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11. Working Conditions in Madagascar’s Apparel Industry: Comparing Export and Domestic Market Firms

Author:
Kristoffer Marslev and Lindsay Whitfield
Publication Date:
06-2023
Content Type:
Working Paper
Institution:
Centre for Business and Development Studies (CBDS), Copenhagen Business School
Abstract:
The apparel export industry in Madagascar is one of the largest in Sub-Saharan Africa, yet limited data exists on the conditions of its 180,000 predominantly female workers. This paper draws on new ILO quantitative and qualitative data generated in 2021 and 2022 to provide a systematic mapping of wages and working conditions in Madagascar’s apparel industry. The analysis shows important variations by end market. While workers in export firms are more likely to do excessive overtime and have inadequate rest time, they earn higher wages and enjoy better social protections such as paid leave, insurance, pension, and maternity. In contrast, nearly half of workers in firms producing for the domestic market earn incomes below the national minimum wage and have limited social benefits. These findings point to a paradox in which workers in export firms are more exploited in terms of their labor power but better off in terms of wages and benefits. The paper attributes these differences to the governance dynamics of global apparel supply chains, in which buyers on the one hand require suppliers to meet certain social standards and to comply with domestic labor laws, but on the other hand impose high flexibility demands that incentivize excessive overtime and work intensification. In both export and domestic market firms, however, wages fall severely below living wage benchmarks. In the context of high levels of absolute poverty in Madagascar and even lower incomes in agriculture, there is not much upwards pressure on wages and working conditions from the labor market.
Topic:
Labor Issues, Global Value Chains, Labor Market, Wages, Garment Industry, Work, and Apparel
Political Geography:
Africa and Madagascar

12. Risks to job quality from digital technologies: are industrial relations in Europe ready for the challenge?

Author:
Janine Berg, Francis Green, Laura Nurski, and David Spencer
Publication Date:
09-2022
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
We examine the job quality effects of new digital technologies in Europe, using the framework of seven job quality ‘domains’: pay, working time quality, prospects, skills and discretion, work intensity, social environment and physical environment. The theoretical effects from new technology are ambivalent for all domains. Data on robot shocks matched to the European Working Conditions Surveys for 2010 and 2015 is used to generate empirical estimates, which show significant aggregate negative effects in three domains, and a positive effect in one. Some negative effects are enhanced where there is below-median collective bargaining. In light of these analyses, and in order to think through the challenge of regulating the development and implementation of all forms of digital technologies, we review regulations in several European countries. Drawing on the principles of human-centred design, we advance the general hypothesis that worker participation is important for securing good job quality outcomes, at both the innovation and adoption stages. We also consider the application to the regulation of job quality of national and supra-national data protection legislation. In these ways, the paper extends the debate about the future of work beyond employment and pay, to a consideration of job quality more broadly.
Topic:
Industrial Policy, Science and Technology, Employment, and Work
Political Geography:
Europe

13. A gender perspective on artificial intelligence and jobs: The vicious cycle of digital inequality

Author:
Estrella Gomez-Herrera and Sabine Köszegi
Publication Date:
08-2022
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
The worldwide artificial intelligence market is expected to increase enormously in the next few years. Because of AI’s immense potential, virtually all industries will be affected by the implementation of AI systems, resulting in the digitalisation and automation of work processes. This will cause disruptive shifts in labour markets, in terms of the number and profiles of jobs in industries as well as worker skill requirements. We take a gender perspective and analyse how gender stereotypes and gendered work segregation on the one hand, and digitalisation and automation (as a consequence of AI implementation) on the other hand, are entangled and result in a vicious cycle of digital gender inequality. We provide insights into the gender-specific impact of AI technologies, which is relevant for the mitigation of the potential risk of the creation of social inequality and exclusion. We show that existing empirical evidence already indicates that AI will not increase gender equality but will somewhat further exacerbate the gender inequality in labour markets, ranging from further horizontal and vertical occupational gender segregation to an increase in the gender pay gap. We summarise policy guidance and measures to decrease gender inequality in the future.
Topic:
Inequality, Digital Economy, Artificial Intelligence, Gender, and Work
Political Geography:
Global Focus

14. The impact of artificial intelligence on the nature and quality of jobs

Author:
Laura Nurski and Mia Hoffmann
Publication Date:
07-2022
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Artificial intelligence (AI), like any workplace technology, changes the division of labour in an organisation and the resulting design of jobs. When used as an automation technology, AI changes the bundle of tasks that make up an occupation. In this case, implications for job quality depend on the (re)composition of those tasks. When AI automates management tasks, known as algorithmic management, the consequences extend into workers’ control over their work, with impacts on their autonomy, skill use and workload. We identify four use cases of algorithmic management that impact the design and quality of jobs: algorithmic work-method instructions; algorithmic scheduling of shifts and tasks; algorithmic surveillance, evaluation and discipline; and algorithmic coordination across tasks. Reviewing the existing empirical evidence on automation and algorithmic management shows significant impact on job quality across a wide range of jobs and employment settings. While each AI use case has its own particular effects on job demands and resources, the effects tend to be more negative for the more prescriptive (as opposed to supportive) use cases. These changes in job design demonstrably affect the social and physical environment of work and put pressure on contractual employment conditions as well. As technology development is a product of power in organisations, it replicates existing power dynamics in society. Consequently, disadvantaged groups suffer more of the negative consequences of AI, risking further job-quality polarisation across socioeconomic groups. Meaningful worker participation in the adoption of workplace AI is critical to mitigate the potentially negative effects of AI adoption on workers, and can help achieve fair and transparent AI systems with human oversight. Policymakers should strengthen the role of social partners in the adoption of AI technology to protect workers’ bargaining power.
Topic:
Science and Technology, Economy, Artificial Intelligence, Inclusion, and Work
Political Geography:
Global Focus