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Author

Kacper Sokol

Observed names: SOKOL, Kacper Blazej, Sokol Kacper, Sokol, Kacper, Sokol, Kacper B.
Observed institutions: UNSW Sydney, ETH Zurich, University of Bristol, ARC Centre of Excellence for Automated Decision-Making and Society, University of Tartu, Università della Svizzera italiana, European Organization for Nuclear Research, RMIT University
ORCID: 0000-0002-9869-5896
Observed ORCID: 0000-0002-9869-5896
OpenAlex ID: A5083819794
FACE: Feasible and Actionable Counterfactual Explanations
2020 · Rafael Poyiadzi, Kacper Sokol, et al. · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · 404
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Explainability fact sheets: a framework for systematic assessment of explainable approaches
2020 · Kacper Sokol, Peter Flach · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · 334
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One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency
2020 · Kacper Sokol, Peter Flach · Künstliche Intell. · 213
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Artificial intelligence should genuinely support clinical reasoning and decision making to bridge the translational gap
2025 · Kacper Sokol, James Fackler, et al. · npj Digital Medicine · 139
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Glass-Box: Explaining AI Decisions With Counterfactual Statements Through Conversation With a Voice-enabled Virtual Assistant
2018 · Kacper Sokol, Peter Flach · International Joint Conference on Artificial Intelligence · 69
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Counterfactual explanations of machine learning predictions:Opportunities and challenges for AI safety
2019 · Sokol, Kacper, Flach, Peter · Bristol Research (University of Bristol) · 54
FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparency
2022 · Kacper Sokol, Raul Santos-Rodriguez, et al. · Software Impacts · 53
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bLIMEy: Surrogate Prediction Explanations Beyond LIME
2019 · Sokol, Kacper, Hepburn, Alexander, et al. · Bristol Research (University of Bristol) · 51
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LIMETREE: Consistent and Faithful Surrogate Explanations of Multiple Classes
2025 · Kacper Sokol, Peter Flach · Electronics · 42
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence
2021 · Sokol, Kacper, Flach, Peter · arXiv (Cornell University) · 41
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FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems
2020 · Kacper Sokol, Alexander Hepburn, et al. · The Journal of Open Source Software · 39
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Conversational Explanations of Machine Learning Predictions Through Class-contrastive Counterfactual Statements
2018 · Kacper Sokol, Peter Flach · International Joint Conference on Artificial Intelligence · 37
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Interpretable representations in explainable AI: from theory to practice
2024 · Kacper Sokol, Peter Flach · Data Mining and Knowledge Discovery · 36
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Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals
2019 · Kacper Sokol, Peter Flach · Proceedings of the AAAI Conference on Artificial Intelligence · 25
Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication
2023 · Keenan, Bernard, Sokol, Kacper · arXiv (Cornell University) · 24
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LIMEtree:Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees
2020 · Sokol, Kacper, Flach, Peter · Bristol Research (University of Bristol) · 22
What Does Evaluation of Explainable Artificial Intelligence Actually Tell Us? A Case for Compositional and Contextual Validation of XAI Building Blocks
2024 · Kacper Sokol, Julia E. Vogt · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · 20
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Comprehension is a double-edged sword: Over-interpreting unspecified information in intelligible machine learning explanations
2024 · Yueqing Xuan, Edward Small, et al. · International Journal of Human-Computer Studies · 18
BayCon: Model-agnostic Bayesian Counterfactual Generator
2022 · Piotr Romashov, Martin Gjoreski, et al. · International Joint Conference on Artificial Intelligence · 16
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Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness
2024 · Edward Small, Kacper Sokol, et al. · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · 14
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Releasing eHealth Analytics into the Wild
2018 · Tom Diethe, Mike Holmes, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 14
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(Un)reasonable Allure of Ante-hoc Interpretability for High-stakes Domains: Transparency Is Necessary but Insufficient for Comprehensibility
2023 · Sokol, Kacper, Vogt, Julia E. · arXiv (Cornell University) · 12
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Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity
2024 · Kacper Sokol, Meelis Kull, et al. · ACM Journal on Responsible Computing · 10
Helpful, Misleading or Confusing: How Humans Perceive Fundamental Building Blocks of Artificial Intelligence Explanations
2023 · Small, Edward, Xuan, Yueqing, et al. · arXiv (Cornell University) · 10
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FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems
2020 · Sokol, Kacper, Hepburn, Alexander, et al. · Zenodo (CERN European Organization for Nuclear Research) · 10
Works count: 63
Citation count: 1,781
H-index: 18
I10-index: 25
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