Results for:

Geographical Discrimination in the Gig Economy

Online labor platforms were expected to flatten labor markets by reducing the importance of worker location and, as a result, promote employment and wage growth in developing countries based on cost differentials. We test these propositions using transactional data from Nubelo, a large online labor platform for Spanish-speaking employers/freelance workers.

Income security in the on-demand economy: Findings and policy lessons from a survey of crowdworkers

This article assesses the validity of many of the assumptions made about work in the on-demand economy and analyses whether proposals advanced for improving workers’ income security are sufficient for remedying current shortcomings. It draws on findings from a survey of crowdworkers conducted in late 2015 on the Amazon Mechanical Turk and Crowdflower platforms on workers’ employment patterns, work histories, and financial security. Based on this information, it provides an analysis of crowdworkers’ economic dependence on the platform, including the share of workers who depend on crowdwork as their main source of income, as well as their working conditions, the problems they encounter while crowdworking and their overall income security. Drawing on these findings, the article recommends an alternative way of organizing work that can improve the income security of crowdworkers as well as the overall efficiency and productivity of crowdwork.

Strengthening social protection for the future of work

Over the past several decades, there has been a growing diversification in working arrangements in G20 countries. This diversification reflects profound changes in the world of work, namely globalization and technological advances, including digitalization, that have facilitated the creation and dispersion of production networks across the globe. These transformations, coupled with the rise of artificial intelligence and robotics, the growth of the “platform economy” and subsequent casualization of labour markets, have raised questions about the future of work. In particular, they have also raised questions about how social protection systems, including social insurance and tax-financed mechanisms, can adapt to these changes.

The Future of Work: Race with—not against—the Machine

Will the revolution in digital and information technologies make us obsolete? Will jobs be lost and never replaced? Will wages drop to intolerable levels? History and economic theory and evidence suggest that in the long term, such fears are misplaced. However, in the short and medium term, dislocation can be severe for certain types of work, places, and populations. In the transition period, policies are needed to facilitate labor market flexibility and mobility, introduce and strengthen safety nets and social protection, and improve education and training.

Skills, social protection and empowerment in the platform economy: A research and policy agenda for the global South

From information and communication technologies to artificial intelligence, from hardware like smart phones to software such as big data management systems, rapid advances in digital technology are transforming the way people live and work. These varying forms of technological innovation pose different risks and opportunities, yet the discourse on how emerging technologies will impact labor markets – still in its nascent stages – tends to treat all of them in the aggregate.

Getting ahead of the Future of Work: Focus on the Systems, not the Skills

What will the future of work look like? If we can understand the ways in which technology, demographic and economic trends will reshape labor markets, we will have a better understanding of what we should be emphasizing
in our educational and training systems to be as well-prepared as possible for tomorrow’s world. Rapid advances in artificial intelligence and robotics have, in particular, created a new momentum to understand exactly how widespread the impacts of technology will be on jobs. Recent reports from the OECD, World Bank, McKinsey, Nesta and others have attempted to ascertain which types of occupations are most at risk of automation, and also which skills and occupations are likely to be most immune to obsolescence.