Project description
A closer look at AI’s human workers
Today, AI is increasingly demanding low-tech human support in coding, verification and cleaning of software material. The so-called ghost workers perform such short-term tasks on demand, anonymously, through automated platforms, without any feedback from colleagues or managers. Despite the growth of this particular phenomenon, the influence of such an occupation on work-related well-being remains unresearched. To address this urgent gap, the EU-funded GHOSTWORK project will conduct an in-depth study of ghost workers’ working conditions and how these impact their overall well-being. A new multi-methodological approach will be developed, enabling an integrated framework incorporating models, theory and empirical findings.
Objective
Artificial intelligence depends on human labour to conduct tasks such as data cleaning, coding, and classifying content. This on-demand work is offered and performed online, paid by the task, on platforms like Amazon Mechanical Turk. Conceptualized as ‘ghost work’, this rapidly growing, platform-based work is largely unseen: workers are unable to speak with managers, do not get feedback, and lack labour protections. How do these specific work conditions influence ghost workers’ well-being? To ensure decent work conditions as automation continues to expand, knowledge about the effects of ghost work on well-being is urgently needed.
The proposed project will develop and test an integrative framework for analysing the effects of ghost work on worker’s well-being. Existing models for analysing the impact of work conditions on well-being fall short for studying ghost work, as these models assume a person has a job and most likely an employer and colleagues. Therefore, this project begins from the specificities of ghost work to synthesize theories and concepts about algorithmic control, occupational well-being, human computation, and platform labour, in order to understand how and through which mechanisms ghost work influences well-being.
The project will contribute to and advance cross-disciplinary scholarship on platform labour and organizational studies of algorithmic technologies. Using a multi-methodological approach to study the effects of ghost work, it begins with in-depth interview-based fieldwork on ghostworkers’ work conditions, and then entails qualitative diary studies of the short-term dynamics of ghost work for worker’s work conditions and well-being. Finally, a 4-wave longitudinal panel study will investigate the relationship between ghost work and well-being over time. Scholars in multiple fields, as well as policy makers and industry leaders, will be keenly interested in both the resulting integrative framework and empirical findings.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-COG - Consolidator Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2020-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3584 CS Utrecht
Netherlands
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.