Summary
Combining expertise across all facets of transport and analytical tools, WE-TRANSFORM aims to apply a participatory approach, using Collective Intelligence (CI), to generate an evidence-based and action-oriented agenda to research, formulate and prioritize the challenges connected to the effects of automation on the transport labour force, on future working conditions and on skills requirements. The WE-TRANSFORM consortium, leveraging existing data and people’s expertise, and empowered by the range and depth of its composition, will create a system of thematic and modal cross-national living hub as a knowledge & prioritization agenda-creation platform, offering a path forward for smarter decisions, more innovative and evidence-based policymaking, through informed governance. The approach of WE-TRANSFORM is highly collaborative, promoting discovery, debate and prioritization of themes by the active participation of representative types of stakeholders, using state-of-the-art data collection and analysis tools while drawing information and themes for the collectively constructed agenda from wide-ranging environments. The composition of the consortium and the Artificial Intelligence (AI) tools to be used guarantee access and involvement across a wide range of relevant parties ranging from transport-chains’ stakeholders and extending to citizens’ associations and beyond including information mining from electronic social media. Robust analytical tools are combined with information findings drawn at AI speed and coverage potential, while the simulation of a social debate within a living hub environment allows the dialogue and ultimately the formulation of a collectively defined agenda enriched with co-created knowledge. The proposal includes also a final provision for maintaining the electronic environment created in a sustainable way as to serve for future research in the area.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101006900 |
| Start date: | 01-12-2020 |
| End date: | 31-03-2024 |
| Total budget - Public funding: | 3 130 636,00 Euro - 2 499 396,00 Euro |
Cordis data
Original description
Combining expertise across all facets of transport and analytical tools, WE-TRANSFORM aims to apply a participatory approach, using Collective Intelligence (CI), to generate an evidence-based and action-oriented agenda to research, formulate and prioritize the challenges connected to the effects of automation on the transport labour force, on future working conditions and on skills requirements. The WE-TRANSFORM consortium, leveraging existing data and people’s expertise, and empowered by the range and depth of its composition, will create a system of thematic and modal cross-national living hub as a knowledge & prioritization agenda-creation platform, offering a path forward for smarter decisions, more innovative and evidence-based policymaking, through informed governance. The approach of WE-TRANSFORM is highly collaborative, promoting discovery, debate and prioritization of themes by the active participation of representative types of stakeholders, using state-of-the-art data collection and analysis tools while drawing information and themes for the collectively constructed agenda from wide-ranging environments. The composition of the consortium and the Artificial Intelligence (AI) tools to be used guarantee access and involvement across a wide range of relevant parties ranging from transport-chains’ stakeholders and extending to citizens’ associations and beyond including information mining from electronic social media. Robust analytical tools are combined with information findings drawn at AI speed and coverage potential, while the simulation of a social debate within a living hub environment allows the dialogue and ultimately the formulation of a collectively defined agenda enriched with co-created knowledge. The proposal includes also a final provision for maintaining the electronic environment created in a sustainable way as to serve for future research in the area.Status
SIGNEDCall topic
MG-2-14-2020Update Date
27-10-2022
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