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Project deliverable . 2019
License: CC BY
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ZENODO
Project deliverable . 2019
License: CC BY
Data sources: Datacite
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SIENNA D4.2: Analysis of the legal and human rights requirements for AI and robotics in and outside the EU

Authors: Rodrigues, Rowena; Siemaszko, Konrad; Warso, Zuzanna;

SIENNA D4.2: Analysis of the legal and human rights requirements for AI and robotics in and outside the EU

Abstract

This report presents the results of SIENNA research on legal developments and approaches to specific legal issues and human rights challenges related to artificial intelligence (AI) and robotics at the international, EU and national level (12 countries, EU and non-EU). The report broadly discusses the legal issues and human rights challenges of AI and robotics and analyses relevant international, EU and regional laws and human rights standards. It summarises and compares the results of the country studies on law, AI and robotics. It also discusses existing norms and standards and gaps and presents some recommendations and ways to overcome gaps. This report will feed into the forthcoming SIENNA work on enhancing the existing legal framework that will identify potential changes needed in dialogue with legislators and relevant committees.

Keywords

robotics, comparative analysis, regional laws, EU law, regulation, Legal analysis, artificial intelligence, human rights, national law, international laws

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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