290 citations · 881 across the 29 of their papers we have counts for
31 papers
Trust Hinders Bidirectional Human-AI Alignment
Michaela Benk, Kacper Sokol
Trust calibration remains the dominant framing of AI-assisted decision making: the goal is to close the gap between perceived and actual trustworthiness of AI systems so that users…
Explanation Navigator: Rectifying Out-of-Scope Human Interpretations of Leaky AI Explanations through Conversational Guidance
Yueqing Xuan, Kacper Sokol, Danula Hettiachchi
As explanations of artificial intelligence systems proliferate, their recipients must grasp not only what they convey but also recognise what they cannot. We conducted an interview…
Diversity-Augmented Negative Sampling for Implicit Collaborative Filtering
Yueqing Xuan, Kacper Sokol, Mark Sanderson +1
Recommenders built upon implicit collaborative filtering are typically trained to distinguish between users' positive and negative preferences. When direct observations of the latt…
Leveraging Complementary AI Explanations to Mitigate Misunderstanding in XAI
Yueqing Xuan, Kacper Sokol, Mark Sanderson +1
Artificial intelligence explanations can make complex predictive models more comprehensible. To be effective, however, they should anticipate and mitigate possible misinterpretatio…
Uncertainty Quantification as a Principled Foundation for Explainable Artificial Intelligence: A Case Study of Counterfactual Explanations
Kacper Sokol, Santo M. A. R. Thies, Eyke Hüllermeier
In this paper we argue that, to its detriment, transparency research overlooks many foundational concepts of artificial intelligence. As an illustrating example we focus on uncerta…
Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse
Yueqing Xuan, Kacper Sokol, Mark Sanderson +1
Algorithmic recourse suggests actions to individuals who have been adversely affected by automated decision-making, helping them to achieve the desired outcome. Knowing the recours…