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09/15/2023
Can Users Correctly Interpret Machine Learning Explanations and Simultaneously Identify Their Limitations?
Automated decision-making systems are becoming increasingly ubiquitous, ...
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09/08/2023
Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse
Counterfactuals operationalised through algorithmic recourse have become...
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06/05/2023
Navigating Explanatory Multiverse Through Counterfactual Path Geometry
Counterfactual explanations are the de facto standard when tasked with i...
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06/04/2023
(Un)reasonable Allure of Ante-hoc Interpretability for High-stakes Domains: Transparency Is Necessary but Insufficient for Explainability
Ante-hoc interpretability has become the holy grail of explainable machi...
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04/19/2023
Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness
Group fairness is achieved by equalising prediction distributions betwee...
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04/15/2023
More Is Less: When Do Recommenders Underperform for Data-rich Users?
Users of recommender systems tend to differ in their level of interactio...
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03/02/2023
Helpful, Misleading or Confusing: How Humans Perceive Fundamental Building Blocks of Artificial Intelligence Explanations
Explainable artificial intelligence techniques are evolving at breakneck...
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02/07/2023
Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication
Over the past decade explainable artificial intelligence has evolved fro...
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10/14/2022
Analysing Donors' Behaviour in Non-profit Organisations for Disaster Resilience: The 2019–2020 Australian Bushfires Case Study
With the advancement and proliferation of technology, non-profit organis...
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09/08/2022
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components
Explainability techniques for data-driven predictive models based on art...
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09/08/2022
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems
Predictive systems, in particular machine learning algorithms, can take ...
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08/14/2022
Simply Logical – Intelligent Reasoning by Example (Fully Interactive Online Edition)
"Simply Logical – Intelligent Reasoning by Example" by Peter Flach was f...
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07/11/2022
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
With the introduction of machine learning in high-stakes decision making...
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03/14/2022
Ethical and Fairness Implications of Model Multiplicity
While predictive models are a purely technological feat, they may operat...
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12/29/2021
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence
Explainable artificial intelligence and interpretable machine learning a...
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07/02/2021
You Only Write Thrice: Creating Documents, Computational Notebooks and Presentations From a Single Source
Academic trade requires juggling multiple variants of the same content p...
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08/16/2020
Towards Faithful and Meaningful Interpretable Representations
Interpretable representations are the backbone of many black-box explain...
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05/04/2020
LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees
Systems based on artificial intelligence and machine learning models sho...
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01/27/2020
One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency
The need for transparency of predictive systems based on Machine Learnin...
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12/11/2019
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches
Explanations in Machine Learning come in many forms, but a consensus reg...
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10/29/2019
bLIMEy: Surrogate Prediction Explanations Beyond LIME
Surrogate explainers of black-box machine learning predictions are of pa...
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09/20/2019
FACE: Feasible and Actionable Counterfactual Explanations
Work in Counterfactual Explanations tends to focus on the principle of "...
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09/11/2019
FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency
Machine learning algorithms can take important decisions, sometimes lega...
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08/07/2019