61 citations · 271 across the 29 of their papers we have counts for
31 papers
Explainable AI Systems Must Be Contestable: Here's How to Make It Happen
Catarina Moreira, Anna Palatkina, Dacia Braca +4
As AI regulations around the world intensify their focus on system safety, contestability has become a mandatory, yet ill-defined, safeguard. In XAI, "contestability" remains an em…
Benchmarking Instance-Centric Counterfactual Algorithms for XAI: From White Box to Black Box
Catarina Moreira, Yu-Liang Chou, Chihcheng Hsieh +3
This study investigates the impact of machine learning models on the generation of counterfactual explanations by conducting a benchmark evaluation over three different types of mo…
An Extension Of Combinatorial Contextuality For Cognitive Protocols
Abdul Karim Obeid, Peter Bruza, Catarina Moreira +2
This article extends the combinatorial approach to support the determination of contextuality amidst causal influences. Contextuality is an active field of study in Quantum Cogniti…
Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms
Bemali Wickramanayake, Zhipeng He, Chun Ouyang +3
In this paper, we address the "black-box" problem in predictive process analytics by building interpretable models that are capable to inform both what and why is a prediction. Pre…
Explainable AI Enabled Inspection of Business Process Prediction Models
Chun Ouyang, Renuka Sindhgatta, Catarina Moreira
Modern data analytics underpinned by machine learning techniques has become a key enabler to the automation of data-led decision making. As an important branch of state-of-the-art…
DiCE4EL: Interpreting Process Predictions using a Milestone-Aware Counterfactual Approach
Chihcheng Hsieh, Catarina Moreira, Chun Ouyang
Predictive process analytics often apply machine learning to predict the future states of a running business~process. However, the internal mechanisms of many existing predictive a…