9 citations · 20 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
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…
Comprehension Is a Double-Edged Sword: Over-Interpreting Unspecified Information in Intelligible Machine Learning Explanations
Yueqing Xuan, Edward Small, Kacper Sokol +2
Automated decision-making systems are becoming increasingly ubiquitous, which creates an immediate need for their interpretability and explainability. However, it remains unclear w…
Helpful, Misleading or Confusing: How Humans Perceive Fundamental Building Blocks of Artificial Intelligence Explanations
Edward Small, Yueqing Xuan, Danula Hettiachchi +1
Explainable artificial intelligence techniques are developed at breakneck speed, but suitable evaluation approaches lag behind. With explainers becoming increasingly complex and a…