dc.contributor.author | KUZIEMSKI, Maciej | |
dc.contributor.author | PALKA, Przemyslaw | |
dc.date.accessioned | 2019-09-17T14:04:48Z | |
dc.date.available | 2019-09-17T14:04:48Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 9789290847724 | |
dc.identifier.issn | 2599-5928 | |
dc.identifier.uri | https://hdl.handle.net/1814/64146 | |
dc.description.abstract | Recent breakthroughs in the development of Artificial Intelligence (AI) have initiated heated debates regarding its governance. As of today, the success of AI relies on machine learning – the ability of algorithms to learn from, and find patterns in, large amounts of data. Consequently, governance of AI will in practice mean policies regarding both the design and access to algorithms, as well as collection and usage of information. Regarding the latter, the European Union (EU) has put in place a comprehensive normative framework: the General Data Protection Regulation (GDPR)1, applicable since 25 May 2018. Based on the discussion that took place during the School of Transnational Governance’s High-Level Policy Dialogue on 26 June 2018, we present three actionable recommendations for global and local policymakers
coming to grasp with the questions of AI Governance | |
dc.format.mimetype | application/pdf | en |
dc.language.iso | en | en |
dc.publisher | European University Institute | en |
dc.relation.ispartofseries | STG Policy Briefs | en |
dc.relation.ispartofseries | 2019/07 | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.subject.other | CoFoE | en |
dc.subject.other | Digital transformation | en |
dc.title | AI governance post-GDPR : lessons learned and the road ahead | en |
dc.type | Other | en |
dc.identifier.doi | 10.2870/470055 | |