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dc.contributor.authorHAMON RONANen_GB
dc.contributor.authorJUNKLEWITZ HENRIKen_GB
dc.contributor.authorSANCHEZ MARTIN JOSE IGNACIOen_GB
dc.date.accessioned2020-01-14T01:05:08Z-
dc.date.available2020-01-13en_GB
dc.date.available2020-01-14T01:05:08Z-
dc.date.created2020-01-10en_GB
dc.date.issued2020en_GB
dc.date.submitted2019-12-18en_GB
dc.identifier.isbn978-92-76-14660-5 (online)en_GB
dc.identifier.issn1831-9424 (online)en_GB
dc.identifier.otherEUR 30040 ENen_GB
dc.identifier.otherOP KJ-NA-30040-EN-N (online)en_GB
dc.identifier.urihttps://publications.jrc.ec.europa.eu/repository/handle/JRC119336-
dc.description.abstractIn the light of the recent advances in artificial intelligence (AI), the serious negative consequences of its use for EU citizens and organisations have led to multiple initiatives from the European Commission to set up the principles of a trustworthy and secure AI. Among the identified requirements, the concepts of robustness and explainability of AI systems have emerged as key elements for a future regulation of this technology. This Technical Report by the European Commission Joint Research Centre (JRC) aims to contribute to this movement for the establishment of a sound regulatory framework for AI, by making the connection between the principles embodied in current regulations regarding to the cybersecurity of digital systems and the protection of data, the policy activities concerning AI, and the technical discussions within the scientific community of AI, in particular in the field of machine learning, that is largely at the origin of the recent advancements of this technology. The individual objectives of this report are to provide a policy-oriented description of the current perspectives of AI and its implications in society, an objective view on the current landscape of AI, focusing of the aspects of robustness and explainability. This also include a technical discussion of the current risks associated with AI in terms of security, safety, and data protection, and a presentation of the scientific solutions that are currently under active development in the AI community to mitigate these risks. This report puts forward several policy-related considerations for the attention of policy makers to establish a set of standardisation and certification tools for AI. First, the development of methodologies to evaluate the impacts of AI on society, built on the model of the Data Protection Impact Assessments (DPIA) introduced in the General Data Protection Regulation (GDPR), is discussed. Secondly, a focus is made on the establishment of methodologies to assess the robustness of systems that would be adapted to the context of use. This would come along with the identification of known vulnerabilities of AI systems, and the technical solutions that have been proposed in the scientific community to address them. Finally, the promotion of transparency systems in sensitive systems is discussed, through the implementation of explainability-by-design approaches in AI components that would provide guarantee of the respect of the fundamental rights.en_GB
dc.description.sponsorshipJRC.E.3-Cyber and Digital Citizens' Securityen_GB
dc.format.mediumOnlineen_GB
dc.languageENGen_GB
dc.publisherPublications Office of the European Unionen_GB
dc.relation.ispartofseriesJRC119336en_GB
dc.titleRobustness and Explainability of Artificial Intelligenceen_GB
dc.typeEUR - Scientific and Technical Research Reportsen_GB
dc.identifier.doi10.2760/57493 (online)en_GB
JRC Directorate:Space, Security and Migration

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