- Date de réalisation : 22 Mai 2019
- Durée du programme : 32 min
- Classification Dewey : Traitement des données. Informatique
- Auteur(s) : VERHULST Stefaan
- Réalisateur(s) : GUIFFARD Thomas
Dans la même collectionQui travaille derrière l’intelligence artificielle ? Enjeux éthiques et sociétaux d’une ... Recommandation algorithmique et diversité de l’information : comment analyser l’impact des ... Où en sont les utopies productives ? Plateformes, makers et fabrication distribuée Swimming up the waterfall: Researching the permanence and ephemerality of 4chan/pol/ Artificial Intelligence and Copyright: The Way Forward Les Peer Production Studies : un champ de recherche à construire ?
Discussion - The Promise and Perils of Public-Private Partnerships around Data for Social Good
“Data Collaborative” refers to an emergent form of public-private partnership in which actors from different sectors exchange and analyze data (and/or provide data science insights and expertise) to create new public value and generate new insights. As evidenced by the 150+ case studies included the Data Collaboratives Explorer, data collaboratives in a variety of different forms have been used with increasing frequency, across sectors ranging from agriculture to telecoms to government, in a growing number of countries around the world.
The value of data collaboratives stems from the fact that the supply of and demand for data are generally widely dispersed — spread across government, the private sector, and civil society — and often poorly matched. This failure (a form of “market failure”) results in tremendous inefficiencies and lost potential. Much data that is released is never used. And much data that is actually needed is never made accessible to those who could productively put it to uses.
Data collaboratives, when designed responsibly, are the key to addressing this shortcoming. Despite their clear potential, the evidence base for data collaboratives is thin. There’s an absence of a systemic, structured framework that can be replicated across projects and geographies, and there’s a lack of clear understanding about what works, what doesn’t, and how best to maximize the potential of data collaboratives. This talk will seek to take stock of what is known and explore pathways to increase both our understanding and practice of data collaboration.
Stefaan G. Verhulst is Co-Founder and Chief of Research and Development of the Governance Laboratory (GovLab) at New York University where he is building a foundation of evidence on how to improve people’s lives by transforming how we govern using advances in science and technology.
His current scholarly focus is on the perils and promise of collaborative technologies and how to harness the unprecedented volume of data to advance the public good. Recently he was selected as one of the 100 most influential people in Digital Government.