6 citations · 8 across the 2 of their papers we have counts for
4 papers · 1 filter
An Experimentation Platform for Explainable Coalition Situational Understanding
Katie Barrett-Powell, Jack Furby, Liam Hiley +8
We present an experimentation platform for coalition situational understanding research that highlights capabilities in explainable artificial intelligence/machine learning (AI/ML)…
Explainable AI for Intelligence Augmentation in Multi-Domain Operations
Alun Preece, Dave Braines, Federico Cerutti +1
Central to the concept of multi-domain operations (MDO) is the utilization of an intelligence, surveillance, and reconnaissance (ISR) network consisting of overlapping systems of r…
Stakeholders in Explainable AI
Alun Preece, Dan Harborne, Dave Braines +2
There is general consensus that it is important for artificial intelligence (AI) and machine learning systems to be explainable and/or interpretable. However, there is no general c…
Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems
Richard Tomsett, Dave Braines, Dan Harborne +2
Several researchers have argued that a machine learning system's interpretability should be defined in relation to a specific agent or task: we should not ask if the system is inte…