right to explanation
In plain wordsThe idea that a person affected by a decision made or shaped by an algorithm — a refused loan, a rejected job application — is entitled to a meaningful account of why.
An individual's entitlement to an intelligible account of how an automated system reached, or contributed to, a decision about them. Its existence under the EU's General Data Protection Regulation (GDPR) was long debated: Article 22 restricts solely automated decisionsautomated decision-making, n.: When a computer system, rather than a person, makes or effectively makes a decision about someone — such as approving credit, screening job applicants or flagging possible welfare fraud. with legal or similarly significant effects, Articles 13–15 require 'meaningful information about the logic involved', and only the non-binding Recital 71 mentions obtaining an explanation. In Dun & Bradstreet Austria (C-203/22, 2025) the Court of Justice of the EU held that people are entitled to a concise, intelligible explanation of the procedure and principles actually applied to their data. The EU AI ActEU AI Act, prop. n.: The European Union's law on artificial intelligence, the first broad AI law anywhere: it bans some uses, sets strict checks for risky ones and puts duties on the makers of the biggest AI models. (Art. 86) adds an express right to explanation for decisions based on certain high-risk AI systemshigh-risk AI system, n.: Under EU law, an AI system used where mistakes could seriously hurt people's safety or rights — in hiring, schooling, loans, policing, borders or products like medical devices — and which must therefore pass strict checks.. In US consumer credit, the Equal Credit Opportunity Act requires lenders to state specific reasons for adverse decisions, including when they use complex models.
Citing her right to explanation, she asked the insurer which factors had driven the automated refusal.
Origin
The debate was launched by Bryce Goodman and Seth Flaxman's 2016 paper arguing that the GDPR creates a right to explanation; Sandra Wachter, Brent Mittelstadt and Luciano Floridi (2017) countered that it guarantees at most a right to be informed, while Andrew Selbst and Julia Powles (2017) defended a functional right. The dispute helped drive research on explainable AIexplainable AI, n.: The field and set of methods that let people understand why an AI system produced a particular output — for example, which factors led it to reject a loan application..
Usage note
A legal explanation need not expose a model's internals: counterfactual explanations (you would have been approved had your income been higher), proposed by Wachter and colleagues in 2017, are one way to comply. Post hoc explanations may not faithfully reflect how a model actually reached its output.
Related
- automated decision-makingautomated decision-making, n.: When a computer system, rather than a person, makes or effectively makes a decision about someone — such as approving credit, screening job applicants or flagging possible welfare fraud.
- explainable AIexplainable AI, n.: The field and set of methods that let people understand why an AI system produced a particular output — for example, which factors led it to reject a loan application.
- interpretabilityinterpretability, n.: The effort to understand how an AI system arrives at its outputs — what information it uses and how it combines it — instead of treating it as a sealed black box.
- algorithmic accountabilityalgorithmic accountability, n.: The idea that the people and organizations behind automated decision systems must be able to explain and justify those systems' effects, answer for the harm they cause, and fix it.
- counterfactual explanationcounterfactual explanation, n.: An explanation that tells someone the smallest change that would have produced a different outcome — for example, that the application would have been accepted if it had listed two more years of work experience.
- Blueprint for an AI Bill of RightsBlueprint for an AI Bill of Rights, prop. n.: A 2022 White House document listing five protections Americans should have when automated systems affect their lives — safety, fairness, privacy, explanation and a human alternative. It was guidance, not law.
Sources
- Goodman, B. & Flaxman, S. (2017). European Union Regulations on Algorithmic Decision-Making and a 'Right to Explanation'. AI Magazine 38(3). (First circulated 2016.)
- Wachter, S., Mittelstadt, B. & Floridi, L. (2017). Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation. International Data Privacy Law 7(2).
Defined in law or standards
GDPR (Reg. (EU) 2016/679), Arts. 13(2)(f), 14(2)(g), 15(1)(h) and 22; EU AI Act (Reg. (EU) 2024/1689), Art. 86
Mentioned in
explainabilityexplainability, n.: How well the reasons behind an AI system's outputs can be put into terms that people can understand, check and, if needed, challenge., explainable AIexplainable AI, n.: The field and set of methods that let people understand why an AI system produced a particular output — for example, which factors led it to reject a loan application., AI transparencyAI transparency, n.: Openness about AI: telling people when they are dealing with one, how a system was built and tested, and why it reached a particular decision., algorithmic accountabilityalgorithmic accountability, n.: The idea that the people and organizations behind automated decision systems must be able to explain and justify those systems' effects, answer for the harm they cause, and fix it., automated decision-makingautomated decision-making, n.: When a computer system, rather than a person, makes or effectively makes a decision about someone — such as approving credit, screening job applicants or flagging possible welfare fraud., black boxblack box, n.: A system whose inner workings are hidden or too complex to understand: we can see what goes in and what comes out, but not why it gave a particular answer., Blueprint for an AI Bill of RightsBlueprint for an AI Bill of Rights, prop. n.: A 2022 White House document listing five protections Americans should have when automated systems affect their lives — safety, fairness, privacy, explanation and a human alternative. It was guidance, not law., counterfactual explanationcounterfactual explanation, n.: An explanation that tells someone the smallest change that would have produced a different outcome — for example, that the application would have been accepted if it had listed two more years of work experience., data protectiondata protection, n.: Laws and practices that control how organizations collect, use, store and share information about people, and that give people rights over it, such as seeing it or having it deleted., General Data Protection RegulationGeneral Data Protection Regulation, prop. n.: The European Union's main privacy law, in force since 2018, which controls how personal information is collected and used — including to train and run AI systems., local explanationlocal explanation, n.: An explanation of why an AI model gave one particular answer for one particular case — this patient, this loan — rather than how it behaves in general., RobodebtRobodebt, prop. n.: An Australian government program that used an automated calculation to accuse hundreds of thousands of welfare recipients of owing money, often wrongly. An official inquiry later found it unfair and illegal., algorithmic recoursealgorithmic recourse, n.: Giving a person who received an unfavorable automated decision a realistic set of actions they could take to get a better result next time, such as paying down a particular debt.