Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation

In recent months, researchers, government bodies, and the media have claimed that a ‘right to explanation’ of decisions made by automated and artificially intelligent algorithmic systems is legally mandated by the forthcoming European Union General Data Protection Regulation 2016/679 (GDPR). The rig...

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Veröffentlicht in:International data privacy law Jg. 7; H. 2; S. 76 - 99
Hauptverfasser: Wachter, Sandra, Mittelstadt, Brent, Floridi, Luciano
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Oxford University Press 01.05.2017
Oxford Publishing Limited (England)
Schlagworte:
Accountability
Algorithms
Artificial intelligence
Automation
Civil rights
Data security
Decision making
Ethics
European Community law
Feedback
General Data Protection Regulation
Internet
Interpretation and construction
Laws, regulations and rules
Libraries
Machine learning
Political aspects
Technology application
Transparency
Europe
ISSN:2044-3994, 2044-4001
Online-Zugang:Volltext
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Zusammenfassung:In recent months, researchers, government bodies, and the media have claimed that a ‘right to explanation’ of decisions made by automated and artificially intelligent algorithmic systems is legally mandated by the forthcoming European Union General Data Protection Regulation 2016/679 (GDPR). The right to explanation is viewed as a promising mechanism in the broader pursuit by government and industry for accountability and transparency in algorithms, artificial intelligence, robotics, and other automated systems. However, there are several reasons to doubt the existence, scope, and feasibility of a ‘right to explanation’ of automated decisions. In this article, we examine the legal status of the ‘right to explanation’ in the GDPR, and identify several barriers undermining its implementation. We argue that the GDPR does not, in its current form, implement a right to explanation, but rather what we term a limited ‘right to be informed’.
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ISSN:2044-3994
2044-4001
DOI:10.1093/idpl/ipx005