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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

“Explaining” machine learning reveals policy challenges
Diane Coyle, Adrian Weller
Science (2020) Vol. 368, Iss. 6498, pp. 1433-1434
Open Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

Algorithmic bias: Senses, sources, solutions
Sina Fazelpour, David Danks
Philosophy Compass (2021) Vol. 16, Iss. 8
Closed Access | Times Cited: 157
Artificial intelligence in educational leadership: a symbiotic role of human-artificial intelligence decision-making
Yinying Wang
Journal of Educational Administration (2021) Vol. 59, Iss. 3, pp. 256-270
Open Access | Times Cited: 72
A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences
Mara Graziani, L. Dutkiewicz, Davide Calvaresi, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 4, pp. 3473-3504
Open Access | Times Cited: 66
Algorithmic fairness in business analytics: Directions for research and practice
Maria De‐Arteaga, Stefan Feuerriegel, Maytal Saar‐Tsechansky
Production and Operations Management (2022) Vol. 31, Iss. 10, pp. 3749-3770
Open Access | Times Cited: 48
Explainable machine learning for public policy: Use cases, gaps, and research directions
Kasun Amarasinghe, Kit T. Rodolfa, Hemank Lamba, et al.
Data & Policy (2023) Vol. 5
Open Access | Times Cited: 29
Artificial intelligence in government: Concepts, standards, and a unified framework
Vincent J. Straub, Deborah Morgan, Jonathan Bright, et al.
Government Information Quarterly (2023) Vol. 40, Iss. 4, pp. 101881-101881
Open Access | Times Cited: 29
A comparative study of Machine Learning and Deep Learning methods for flood forecasting in the Far-North region, Cameroon
Francis Yongwa Dtissibe, Ado Adamou Abba Ari, Hamadjam Abboubakar, et al.
Scientific African (2023) Vol. 23, pp. e02053-e02053
Open Access | Times Cited: 21
Machine learning in human creativity: status and perspectives
Mirko Farina, Andrea Lavazza, Giuseppe Sartori, et al.
AI & Society (2024) Vol. 39, Iss. 6, pp. 3017-3029
Closed Access | Times Cited: 9
Diversity in sociotechnical machine learning systems
Sina Fazelpour, Maria De‐Arteaga
Big Data & Society (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 28
Explainable digital forensics AI: Towards mitigating distrust in AI-based digital forensics analysis using interpretable models
Abiodun A. Solanke
Forensic Science International Digital Investigation (2022) Vol. 42, pp. 301403-301403
Open Access | Times Cited: 28
Deep Learning Enabled Early Predicting Cardiovascular Status Using Highly Sensitive Piezoelectric Sensor of Solution‐Processable Nylon‐11
Anand Babu, Spandan Ranpariya, Dhirendra Kumar Sinha, et al.
Advanced Materials Technologies (2023) Vol. 8, Iss. 10
Closed Access | Times Cited: 19
Algorithmic decision-making: The right to explanation and the significance of stakes
Lauritz Aastrup Munch, Jens Christian Bjerring, Jakob Thrane Mainz
Big Data & Society (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 5
Data technologies and analytics for policy and governance: a landscape review
Omar Isaac Asensio, Catherine E. Moore, Nícola Ulibarrí, et al.
Data & Policy (2025) Vol. 7
Open Access
Quantum Computing and Machine Learning in Medical Decision-Making: A Comprehensive Review
James C. L. Chow
Algorithms (2025) Vol. 18, Iss. 3, pp. 156-156
Open Access
On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis
Banamali Panigrahi, Saman Razavi, Lorne E. Doig, et al.
Water Resources Research (2025) Vol. 61, Iss. 3
Open Access
Progress in the Application of Machine Learning in Combustion Studies
Zhi-Hao Zheng, Xiaodong Lin, Ming Yang, et al.
ES Energy & Environments (2020)
Open Access | Times Cited: 43
Mitigating belief projection in explainable artificial intelligence via Bayesian teaching
Scott Cheng‐Hsin Yang, Wai Keen Vong, Ravi B. Sojitra, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 36
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021)
Peter Vamplew, Benjamin J. Smith, Johan Källström, et al.
Autonomous Agents and Multi-Agent Systems (2022) Vol. 36, Iss. 2
Open Access | Times Cited: 22
Extrapolation and AI transparency: Why machine learning models should reveal when they make decisions beyond their training
Xuenan Cao, Roozbeh Yousefzadeh
Big Data & Society (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 14
Machine learning for food security: Principles for transparency and usability
Yujun Zhou, Erin Lentz, Hope Michelson, et al.
Applied Economic Perspectives and Policy (2021) Vol. 44, Iss. 2, pp. 893-910
Closed Access | Times Cited: 25
Achieving Equity with Predictive Policing Algorithms: A Social Safety Net Perspective
Chun-Ping Yen, Tzu-Wei Hung
Science and Engineering Ethics (2021) Vol. 27, Iss. 3
Closed Access | Times Cited: 24
Reconstruction of the pan evaporation based on meteorological factors with machine learning method over China
Hong Wang, Fubao Sun, Fa Liu, et al.
Agricultural Water Management (2023) Vol. 287, pp. 108416-108416
Open Access | Times Cited: 9
Shedding Light on Shadowbanning
Gabriel Nicholas
(2022)
Open Access | Times Cited: 15
An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance
Suriyan Jomthanachai, Wai Peng Wong, Khai Wah Khaw
Computational Economics (2023) Vol. 63, Iss. 2, pp. 741-792
Open Access | Times Cited: 7
AI Governance
Allan Dafoe
Oxford University Press eBooks (2023), pp. 21-44
Closed Access | Times Cited: 7
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