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GHOSTWORK

Financiado

The ghostworker s well being An integrative framework

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 Tu... ver más

31/08/2026

EUR

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

ERASMUS UNIVERSITEIT ROTTERDAM No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-03-11

ERC-2020-COG: ERC CONSOLIDATOR GRANTS

I+D

Cerrada hace 4 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

EUR

1.96M€ | Lider

CARBONAR, EN LIQUIDACIÓN

577.68K€ | Participante

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Duración del proyecto: 65 meses Fecha Inicio: 2021-03-11
Fecha Fin: 2026-08-31

Líder del proyecto

ERASMUS UNIVERSITEIT ROTTERDAM No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Descripción del proyecto 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.

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