Beyond Explainability: The Case for AI Validation | Paper Citation Record

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This paper cites AIin health and medicine.

Beyond Explainability: The Case for AI Validation AIin health and medicine

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This paper cites Deep neural net- works improve radiologists’ performance in breast cancer screening.

Beyond Explainability: The Case for AI Validation Deep neural net- works improve radiologists’ performance in breast cancer screening

Reference 2

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This paper cites International evaluation of an AIsys- tem for breast cancer screening.

Beyond Explainability: The Case for AI Validation International evaluation of an AIsys- tem for breast cancer screening

Reference 3

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This paper cites Bias in medical ai: Impli- cations for clinical decision-making.

Beyond Explainability: The Case for AI Validation Bias in medical ai: Impli- cations for clinical decision-making

Reference 4

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This paper cites Algorithmic hiring in prac- tice: Recruiter and hr professional’s per- spectives on AIuse in hiring.

Beyond Explainability: The Case for AI Validation Algorithmic hiring in prac- tice: Recruiter and hr professional’s per- spectives on AIuse in hiring

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This paper cites AIhiring bias: Everything you need to know.

Beyond Explainability: The Case for AI Validation AIhiring bias: Everything you need to know

Reference 6

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This paper cites Using artiﬁcial intelli- gence to address criminal justice needs.

Beyond Explainability: The Case for AI Validation Using artiﬁcial intelli- gence to address criminal justice needs

Reference 8

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This paper cites Criminal justice, artiﬁcial in- telligence systems, and human rights.

Beyond Explainability: The Case for AI Validation Criminal justice, artiﬁcial in- telligence systems, and human rights

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This paper cites Arti- ﬁcial intelligence in the criminal justice sys- tem: leading trends and possibilities.

Beyond Explainability: The Case for AI Validation Arti- ﬁcial intelligence in the criminal justice sys- tem: leading trends and possibilities

Reference 10

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This paper cites Recommendation of the council on artiﬁcial intelligence.

Beyond Explainability: The Case for AI Validation Recommendation of the council on artiﬁcial intelligence

Reference 11

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This paper cites Proposal for a regulation of the european parliament and of the council laying down har- monized rules on artiﬁcial intelligence.

Beyond Explainability: The Case for AI Validation Proposal for a regulation of the european parliament and of the council laying down har- monized rules on artiﬁcial intelligence

Reference 12

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This paper cites Reg- ulation (eu) 2016/679 on the protection of natural persons with regard to the processing of personal data (gdpr).

Beyond Explainability: The Case for AI Validation Reg- ulation (eu) 2016/679 on the protection of natural persons with regard to the processing of personal data (gdpr)

Reference 13

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This paper cites Explainable AI is Responsible AI: How Explainability Creates Trustworthy and Socially Responsible Artificial Intelligence.

Beyond Explainability: The Case for AI Validation Explainable AI is Responsible AI: How Explainability Creates Trustworthy and Socially Responsible Artificial Intelligence

Reference 14

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This paper cites Unexplainability and incomprehensibility of AI.

Beyond Explainability: The Case for AI Validation Unexplainability and incomprehensibility of AI

Reference 15

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This paper cites The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery.

Beyond Explainability: The Case for AI Validation The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery

Reference 16

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This paper cites The Case Against Explainability.

Beyond Explainability: The Case for AI Validation The Case Against Explainability

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This paper cites Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation.

Beyond Explainability: The Case for AI Validation Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation

Reference 18

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This paper cites Beware of "Explanations" of AI.

Beyond Explainability: The Case for AI Validation Beware of "Explanations" of AI

Reference 19

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This paper cites Painting the black box white: experimental ﬁndings from applying XAI to an ECG reading setting.

Beyond Explainability: The Case for AI Validation Painting the black box white: experimental ﬁndings from applying XAI to an ECG reading setting

Reference 20

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This paper cites Explana- tions considered harmful: the impact of mis- leading explanations on accuracy in hybrid human-AI decision making.

Beyond Explainability: The Case for AI Validation Explana- tions considered harmful: the impact of mis- leading explanations on accuracy in hybrid human-AI decision making

Reference 21

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This paper cites Stop explaining black box machine learning models for high stakes de- cisions and use interpretable models instead.

Beyond Explainability: The Case for AI Validation Stop explaining black box machine learning models for high stakes de- cisions and use interpretable models instead

Reference 22

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This paper cites Lost in translation: the limits of explainability in AI.

Beyond Explainability: The Case for AI Validation Lost in translation: the limits of explainability in AI

Reference 23

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This paper cites The false hope of cur- rent approaches to explainable artiﬁcial in- telligence in health care.

Beyond Explainability: The Case for AI Validation The false hope of cur- rent approaches to explainable artiﬁcial in- telligence in health care

Reference 24

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This paper cites Types of penetration testing: Black box, white box & grey box, 2024.

Beyond Explainability: The Case for AI Validation Types of penetration testing: Black box, white box & grey box, 2024

Reference 25

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This paper cites Black box and white box testing techniques- a literature review.

Beyond Explainability: The Case for AI Validation Black box and white box testing techniques- a literature review

Reference 26

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This paper cites A comparative study of white box, black box and grey box testing techniques.

Beyond Explainability: The Case for AI Validation A comparative study of white box, black box and grey box testing techniques

Reference 27

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This paper cites Proposal for a regulation of the european parliament and of the council laying down har- monized rules on artiﬁcial intelligence.

Beyond Explainability: The Case for AI Validation Proposal for a regulation of the european parliament and of the council laying down har- monized rules on artiﬁcial intelligence

Reference 28

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This paper cites 6580, 117th cong., 2022.

Beyond Explainability: The Case for AI Validation 6580, 117th cong., 2022

Reference 29

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This paper cites Fairness and bias in algorithmic hiring: A multidisciplinary survey.

Beyond Explainability: The Case for AI Validation Fairness and bias in algorithmic hiring: A multidisciplinary survey

Reference 30

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Beyond Explainability: The Case for AI Validation Fairness, AI & recruit- ment

Reference 31

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Beyond Explainability: The Case for AI Validation Systematic Literature Review of Validation Methods for AI Systems

Reference 32

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Beyond Explainability: The Case for AI Validation Food & Drug Admin

Reference 33

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This paper cites Recommendations for designing for simplicity and eﬃciency: Azure well- architected framework reliability, 2023.

Beyond Explainability: The Case for AI Validation Recommendations for designing for simplicity and eﬃciency: Azure well- architected framework reliability, 2023

Reference 34

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This paper cites Aﬀord- able system operational eﬀectiveness (asoe) model.

Beyond Explainability: The Case for AI Validation Aﬀord- able system operational eﬀectiveness (asoe) model

Reference 35

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This paper cites Guidance on model risk management, sr 11-7.

Beyond Explainability: The Case for AI Validation Guidance on model risk management, sr 11-7

Reference 36

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Beyond Explainability: The Case for AI Validation Provi- sions on the management of algorithmic rec- ommendations in internet information ser- vices, 2022

Reference 37

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Beyond Explainability: The Case for AI Validation Mea- sures for the management of generative ar- tiﬁcial intelligence services (draft for com- ment), April 2023

Reference 38

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Beyond Explainability: The Case for AI Validation Food and Drug Administration

Reference 39

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Beyond Explainability: The Case for AI Validation A comparative look at various countries’ legal regimes governing automated vehicles

Reference 40

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This paper cites Vali- dation of automated and autonomous vehi- cles.

Beyond Explainability: The Case for AI Validation Vali- dation of automated and autonomous vehi- cles

Reference 41

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Beyond Explainability: The Case for AI Validation Au- tonomous vehicle technology: A guide for policymakers

Reference 42

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This paper cites Identifying main drivers on inven- tory using regression analysis.

Beyond Explainability: The Case for AI Validation Identifying main drivers on inven- tory using regression analysis

Reference 43

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This paper cites Minoxi- dil: mechanisms of action on hair growth.

Beyond Explainability: The Case for AI Validation Minoxi- dil: mechanisms of action on hair growth

Reference 44

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Beyond Explainability: The Case for AI Validation Arslan, and D

Reference 45

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This paper cites Evalua- tion of post-hoc interpretability methods in time-series classiﬁcation.

Beyond Explainability: The Case for AI Validation Evalua- tion of post-hoc interpretability methods in time-series classiﬁcation

Reference 46

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This paper cites The role of causality in explain- able artiﬁcial intelligence.

Beyond Explainability: The Case for AI Validation The role of causality in explain- able artiﬁcial intelligence

Reference 47

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This paper cites A review of explainable artiﬁ- cial intelligence in supply chain manage- ment using neurosymbolic approaches.

Beyond Explainability: The Case for AI Validation A review of explainable artiﬁ- cial intelligence in supply chain manage- ment using neurosymbolic approaches

Reference 48

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This paper cites Ai-driven ﬁnancial risk manage- ment systems: Enhancing predictive capa- bilities and operational eﬃciency.

Beyond Explainability: The Case for AI Validation Ai-driven ﬁnancial risk manage- ment systems: Enhancing predictive capa- bilities and operational eﬃciency

Reference 49

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This paper cites Not all AI health tools with regulatory authorization are clinically validated.

Beyond Explainability: The Case for AI Validation Not all AI health tools with regulatory authorization are clinically validated

Reference 50

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This paper cites Framework convention on artiﬁcial intelligence and human rights, democracy and the rule of law, 2024.

Beyond Explainability: The Case for AI Validation Framework convention on artiﬁcial intelligence and human rights, democracy and the rule of law, 2024

Reference 51

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This paper cites Secretary of State for Science, Inno- vation & Technology.

Beyond Explainability: The Case for AI Validation Secretary of State for Science, Inno- vation & Technology

Reference 52

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This paper cites Executive order no.

Beyond Explainability: The Case for AI Validation Executive order no

Reference 53

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This paper cites an unresolved cited work.

Beyond Explainability: The Case for AI Validation Unresolved cited work

Reference 54

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Observation 1492fd80-f4a4-4970-9415-51dbc6f2e37b · outbound

This paper cites M- 25-21: Accelerating federal use of AI through innovation, governance, and pub- lic trust.

Beyond Explainability: The Case for AI Validation M- 25-21: Accelerating federal use of AI through innovation, governance, and pub- lic trust

Reference 55

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Observation da592f54-2aad-42c1-a9f9-50149ffe73b4 · outbound

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Beyond Explainability: The Case for AI Validation Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:51:19.123617Z

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Observation 8f8cda65-9291-4bb6-a3da-fdd5fa45d911 · outbound

This paper cites Ab 331 bill, section 22756.3(a)(3), 2023.

Beyond Explainability: The Case for AI Validation Ab 331 bill, section 22756.3(a)(3), 2023

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:18.940761Z

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Observation 127fb940-3cb4-4ed0-80b6-2be2b5ef2557 · outbound

This paper cites NIST AI 600-1 artiﬁcial intelli- gence risk management framework: Genera- tive artiﬁcial intelligence proﬁle, 2024.

Beyond Explainability: The Case for AI Validation NIST AI 600-1 artiﬁcial intelli- gence risk management framework: Genera- tive artiﬁcial intelligence proﬁle, 2024

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:18.720323Z

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Observation 3ebbfbb1-4baf-4e8d-a8ef-4eafbd1f9f90 · outbound

This paper cites Partially in- terpretable models with guarantees on cov- erage and accuracy.

Beyond Explainability: The Case for AI Validation Partially in- terpretable models with guarantees on cov- erage and accuracy

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:18.480933Z

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Observation c70b84d8-c7c3-4a61-b76a-3fadd0b381f4 · outbound

This paper cites Shap and lime: an evaluation of discriminative power in credit risk.

Beyond Explainability: The Case for AI Validation Shap and lime: an evaluation of discriminative power in credit risk

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:18.284225Z

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Observation 2ff6098a-4fe5-4585-a6f0-b96c38905110 · outbound

This paper cites Fooling lime and shap: Adversarial attacks on post hoc explanation methods.

Beyond Explainability: The Case for AI Validation Fooling lime and shap: Adversarial attacks on post hoc explanation methods

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:18.088119Z

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Observation 28bf84ae-ee41-4faf-af12-d98fc737ebe6 · outbound

This paper cites To- ward trustworthy artiﬁcial intelligence (tai) in the context of explainability and robust- ness.

Beyond Explainability: The Case for AI Validation To- ward trustworthy artiﬁcial intelligence (tai) in the context of explainability and robust- ness

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:17.864378Z

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Observation 762d4858-ac24-4380-86cc-e5454c12a258 · outbound

This paper cites Experimental regulations and regulatory sandboxes: Law without or- der? Law and method , 2021, 2021.

Beyond Explainability: The Case for AI Validation Experimental regulations and regulatory sandboxes: Law without or- der? Law and method , 2021, 2021

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:17.644220Z

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Observation 2ec85e7c-2fb2-4b4b-9972-f93de88ad59e · outbound

This paper cites Manipulating and measuring model interpretability.

Beyond Explainability: The Case for AI Validation Manipulating and measuring model interpretability

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:17.458637Z

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Observation 193b5011-5431-4023-ae63-1bc20a54ff85 · outbound

This paper cites Interpreting interpretability: understanding data scien- tists’ use of interpretability tools for ma- chine learning.

Beyond Explainability: The Case for AI Validation Interpreting interpretability: understanding data scien- tists’ use of interpretability tools for ma- chine learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:17.227972Z

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Observation a7b61adc-7e5a-4004-aa08-9fd0d3471853 · outbound

This paper cites Artiﬁcial neural network classiﬁcation of high dimensional data with novel opti- mization approach of dimension reduction.

Beyond Explainability: The Case for AI Validation Artiﬁcial neural network classiﬁcation of high dimensional data with novel opti- mization approach of dimension reduction

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:17.010463Z

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Observation bc83493b-6132-4ce0-bc63-efeed345908a · outbound

This paper cites Verma, and Namita Sri- vastava.

Beyond Explainability: The Case for AI Validation Verma, and Namita Sri- vastava

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:16.818611Z

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Observation 041c5297-2b30-4eda-8d28-0143580eb98a · outbound

This paper cites Thinking responsibly about responsible ai and ‘the dark side’of ai.

Beyond Explainability: The Case for AI Validation Thinking responsibly about responsible ai and ‘the dark side’of ai

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:16.582744Z

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Observation 48741dfa-0818-4d7a-9df8-4caf38359a59 · outbound

This paper cites The dangers of human- like bias in machine-learning algorithms.

Beyond Explainability: The Case for AI Validation The dangers of human- like bias in machine-learning algorithms

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:16.391415Z

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Observation f2240a22-1e57-4d49-87e6-5a033af864cb · outbound

This paper cites The black box society: The secret algorithms that control money and in- formation.

Beyond Explainability: The Case for AI Validation The black box society: The secret algorithms that control money and in- formation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:16.210193Z

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Observation e37210b4-d2c8-405d-89ef-ed2f2cf6b231 · outbound

This paper cites Towards the certiﬁcation of ai-based systems.

Beyond Explainability: The Case for AI Validation Towards the certiﬁcation of ai-based systems

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:15.972679Z

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Observation dcc7b535-b6d2-4202-a65d-7f71e2b33b34 · outbound

This paper cites Report on the safety and liability implications of artiﬁcial intelli- gence, the internet of things and robotics, February 2020.

Beyond Explainability: The Case for AI Validation Report on the safety and liability implications of artiﬁcial intelli- gence, the internet of things and robotics, February 2020

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:15.829266Z

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Observation 555ea032-f2b8-4161-85c0-1ed6734ef443 · outbound

This paper cites Report on li- ability for AI and other emerging technolo- gies (new technologies formation), Novem- ber 2019.

Beyond Explainability: The Case for AI Validation Report on li- ability for AI and other emerging technolo- gies (new technologies formation), Novem- ber 2019

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:15.587367Z

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Observation 8cd59f9f-d430-40c1-bfba-55f88ac1fcad · outbound

This paper cites The expert group’s report on liability for ar- tiﬁcial intelligence and other emerging digi- tal technologies: a critical assessment.

Beyond Explainability: The Case for AI Validation The expert group’s report on liability for ar- tiﬁcial intelligence and other emerging digi- tal technologies: a critical assessment

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:15.334653Z

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Observation c2110df2-58bc-49bc-bdc4-e019564ee3f6 · outbound

This paper cites Identifying unreliable predictions in clinical risk models.

Beyond Explainability: The Case for AI Validation Identifying unreliable predictions in clinical risk models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:15.102968Z

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Observation f7ef0116-1c06-4990-bfc5-26cdffcaba85 · outbound

This paper cites Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization.

Beyond Explainability: The Case for AI Validation Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:51:12.027708Z

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Observation fc423ecc-d70f-4190-b258-fafd6b5e9b43 · outbound

This paper cites AI Failures: A Review of Underlying Issues.

Beyond Explainability: The Case for AI Validation AI Failures: A Review of Underlying Issues

Reference 77

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:51:11.783183Z

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Observation e702fd62-bf40-4af7-a0d6-8e2bb9de1f44 · outbound

This paper cites Dakka, T.V.

Beyond Explainability: The Case for AI Validation Dakka, T.V

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:14.831725Z

Source-reported events for the cited work

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Observation e193068e-215d-4df0-9e40-864f855cafc1 · outbound

This paper cites Factors for accelerating the development speed in systems of artiﬁcial intelligence.

Beyond Explainability: The Case for AI Validation Factors for accelerating the development speed in systems of artiﬁcial intelligence

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:14.626427Z

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Observation 03fc8648-e572-4757-aa12-38372051b51e · outbound

This paper cites A Blueprint for Auditing Generative AI.

Beyond Explainability: The Case for AI Validation A Blueprint for Auditing Generative AI

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:51:11.603977Z

Source-reported events for the cited work

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Observation 2c10a85e-70f3-47a8-b114-a550d13f2f80 · outbound

This paper cites AI-generated synthetic data for stress testing ﬁnancial systems: A ma- chine learning approach to scenario analysis and risk management.

Beyond Explainability: The Case for AI Validation AI-generated synthetic data for stress testing ﬁnancial systems: A ma- chine learning approach to scenario analysis and risk management

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:14.438611Z

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Observation 0bac1177-2a43-40fa-a9e9-5f7c8f1d8cfa · outbound

This paper cites The implica- tions of AIfor criminal justice: Key take- aways from a convening of leading stake- holders.

Beyond Explainability: The Case for AI Validation The implica- tions of AIfor criminal justice: Key take- aways from a convening of leading stake- holders

Reference 82

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Observation ae2aa259-3207-41eb-b84c-2276464e6253 · outbound

This paper cites Justice by algorithm: The lim- its of AI in criminal sentencing.

Beyond Explainability: The Case for AI Validation Justice by algorithm: The lim- its of AI in criminal sentencing

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:14.256552Z

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Observation 5987497e-f56f-4a49-8ccf-40484d5c4fd2 · outbound

This paper cites The need for trans- parency in the age of predictive sentencing algorithms.

Beyond Explainability: The Case for AI Validation The need for trans- parency in the age of predictive sentencing algorithms

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:14.043173Z

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Observation 4078d7cc-ec8c-443e-ad7f-26406d358ad0 · outbound

This paper cites Smart dispute resolution: Artiﬁcial intelli- gence to reduce litigation.

Beyond Explainability: The Case for AI Validation Smart dispute resolution: Artiﬁcial intelli- gence to reduce litigation

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:13.885393Z

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Observation a40b605f-a596-4b93-a1bb-d9301bf1d60b · outbound

This paper cites Arti- ﬁcial intelligence and civil liability—do we need a new regime? International Jour- nal of Law and Information Technology , 30(4):385–397, 2022.

Beyond Explainability: The Case for AI Validation Arti- ﬁcial intelligence and civil liability—do we need a new regime? International Jour- nal of Law and Information Technology , 30(4):385–397, 2022

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:13.645741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e5568dde-661a-4b7c-8f44-e79e9b3305f2 · outbound

This paper cites The reputational risks of AI.

Beyond Explainability: The Case for AI Validation The reputational risks of AI

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:13.484681Z

Source-reported events for the cited work

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Observation 8b2bf579-1d4d-4e29-b685-c0310830fe0a · outbound

This paper cites The contributions of the economics of information to twentieth cen- tury economics.

Beyond Explainability: The Case for AI Validation The contributions of the economics of information to twentieth cen- tury economics

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:13.309562Z

Source-reported events for the cited work

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Observation 37d5b821-9340-456f-9480-db4974cc6eed · outbound

This paper cites ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models.

Beyond Explainability: The Case for AI Validation ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-07T13:51:10.888133Z

Source-reported events for the cited work

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Observation 0c1e3fb6-e904-40a3-9838-40a6469da5a4 · outbound

This paper cites all of us.

Beyond Explainability: The Case for AI Validation all of us

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:13.186093Z

Source-reported events for the cited work

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Observation 3de90f0a-55b4-462a-9511-d8e1fa2157df · outbound

This paper cites Iso/iec 23053:2022 — frame- work for artiﬁcial intelligence (AI) systems using machine learning (ML), 2022.

Beyond Explainability: The Case for AI Validation Iso/iec 23053:2022 — frame- work for artiﬁcial intelligence (AI) systems using machine learning (ML), 2022

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:12.947839Z

Source-reported events for the cited work

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Observation 43dee68b-bf88-4554-8198-e43b6a79d59c · outbound

This paper cites Policies, data and analysis for trustworthy artiﬁcial intelligence.

Beyond Explainability: The Case for AI Validation Policies, data and analysis for trustworthy artiﬁcial intelligence

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:12.794803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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