"The Right to Explanation, Explained"
Open accessAbstract
Many have called for algorithmic accountability: laws governing decision-making by complex algorithms, or AI. The EU’s General Data Protection Regulation (GDPR) now establishes exactly this. The recent debate over the right to explanation (a right to information about individual decisions made by algorithms) has obscured the significant algorithmic accountability regime established by the GDPR. The GDPR’s provisions on algorithmic accountability, which include a right to explanation, have the potential to be broader, stronger, and deeper than the preceding requirements of the Data Protection Directive. This Essay clarifies, largely for a U.S. audience, what the GDPR actually requires, incorporating recently released authoritative guidelines.
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Scholars differ on whether a data subject has a right to an ex post explanation of automated decisions affecting them.
“Scholars differ on whether a data subject has a right to an ex post explanation of automated decisions affecting them (Edwards and Veale 2017; Edwards and Veale 2018; Kaminski 2019; Mendoza and Bygrave 2017; Selbst and Powles 2017; Wachter et al. 2017) and on the extent to which such a right is inherent, if not in Article 22, in the various other provisions of the GDPR (Maglieri 2019).”
From Simplification of Administrative Procedures through Fully Automated Decision-Making: The Case of Norway (2021) · cites this paper as Kaminski 2019
Mutual influences between the national and EU legal orders will occur.
“Although this may be undesirable from the perspective of striving for an EU-standard of protection, it can be concluded that mutual influences between the national and EU legal orders will occur.”
From Digitizing the public administration and safeguarding individual rights: automated decision-making at the intersection of the GDPR and Polish administrative procedure (2021) · cites this paper as Kaminski (2019): 195
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- Authors
- Kaminski, M. E.
- Corresponding author
- Kaminski, Margot E.
- ORCID
- Kaminski, Margot E.
- Venue
- btlj
- Publisher
- btlj
- Published
- 2019
- Volume
- 34
- Issue
- 1
- Pages
- 189
- OpenAlex
- W3123831349
- Cited by
- 146
- References
- 0
- Citations by year
- 2026: 8 · 2025: 9 · 2024: 12 · 2023: 37 · 2022: 20 · 2021: 22 · 2020: 27 · 2019: 11
- FWCI
- 174.54
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Colorado Law Scholarly Commons (University of Colorado Colorado Springs) (submittedVersion)
- Berkeley technology law journal
- UC Berkeley
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- right to explanation, algorithmic accountability, General Data Protection Regulation, GDPR, EU Data Protection Directive, algorithmic decision-making, AI regulation, EU data protection law, algorithmic transparency
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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