Towards A Rigorous Science of Interpretable Machine Learning

Finale Doshi‐Velez; Been Kim

doi:https://doi.org/10.48550/arxiv.1702.08608

Towards A Rigorous Science of Interpretable Machine Learning

2017 · arXiv (Cornell University) · 3,190 citations · 11 from inside this corpus

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

16 of 16 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

this paper works it cites works citing it node size = global citations · hover for the full title

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
A survey of methods for explaining black box models→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
On the Opportunities and Risks of Foundation Models→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Machine Learning Interpretability: A Survey on Methods and Metrics→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
The false hope of current approaches to explainable artificial intelligence in health care→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Automated Machine Learning→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Towards A Rigorous Science of Interpretable Machine Learning→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
Towards A Rigorous Science of Interpretable Machine Learning→Playing Atari with Deep Reinforcement LearningLegacy edge — source detail unavailable
Towards A Rigorous Science of Interpretable Machine Learning→Fairness through awarenessLegacy edge — source detail unavailable
Towards A Rigorous Science of Interpretable Machine Learning→Reading Tea Leaves: How Humans Interpret Topic ModelsLegacy edge — source detail unavailable
Towards A Rigorous Science of Interpretable Machine Learning→Agnostic Learning with Unknown UtilitiesLegacy edge — source detail unavailable
Agnostic Learning with Unknown Utilities→Fairness through awarenessLegacy edge — source detail unavailable
Agnostic Learning with Unknown Utilities→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI→Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…Legacy edge — source detail unavailable
Machine Learning Interpretability: A Survey on Methods and Metrics→Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Fairness through awarenessLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)Legacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…Legacy edge — source detail unavailable
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
On the Opportunities and Risks of Foundation Models→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
On the Opportunities and Risks of Foundation Models→Agnostic Learning with Unknown UtilitiesLegacy edge — source detail unavailable
On the Opportunities and Risks of Foundation Models→Explainable AI: A Review of Machine Learning Interpretability MethodsLegacy edge — source detail unavailable
Automated Machine Learning→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Machine Learning Interpretability: A Survey on Methods and MetricsLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Explainable AI: A Review of Machine Learning Interpretability MethodsLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→The false hope of current approaches to explainable artificial intelligence in health careLegacy edge — source detail unavailable

What this paper cites, inside the corpus

Paper	Year	Cited
Mastering the game of Go with deep neural networks and tree search	2016	16,014
Playing Atari with Deep Reinforcement Learning	2013	5,104
Fairness through awareness	2012	3,476
Reading Tea Leaves: How Humans Interpret Topic Models	2009	1,882
Agnostic Learning with Unknown Utilities	2016	1,416

What cites it, inside the corpus

Paper	Year	Cited
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…	2019	9,796
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)	2018	6,166
A survey of methods for explaining black box models	2019	4,992
Explainable AI: A Review of Machine Learning Interpretability Methods	2020	2,907
A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI	2020	2,377
On the Opportunities and Risks of Foundation Models	2021	2,265
Machine Learning Interpretability: A Survey on Methods and Metrics	2019	1,822
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…	2023	1,679
The false hope of current approaches to explainable artificial intelligence in health care	2021	1,572
Automated Machine Learning	2019	1,451
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications	2021	1,424

Links

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Topics

Explainable Artificial Intelligence (XAI)	Computer Science
Adversarial Robustness in Machine Learning	Computer Science
Machine Learning and Data Classification	Computer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

supports2 author record(s) attached.
supports26 reference(s) recorded.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:47+00:00.

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