18 citations · 71 across the 16 of their papers we have counts for
5 papers · 2 filters
AAAI FSS-18: Artificial Intelligence in Government and Public Sector Proceedings
Frank Stein, Alun Preece, Mihai Boicu
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA, October 18-20, 2018
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…
Defining the Collective Intelligence Supply Chain
Iain Barclay, Alun Preece, Ian Taylor
Organisations are increasingly open to scrutiny, and need to be able to prove that they operate in a fair and ethical way. Accountability should extend to the production and use of…
Uncertainty Aware AI ML: Why and How
Lance Kaplan, Federico Cerutti, Murat Sensoy +2
This paper argues the need for research to realize uncertainty-aware artificial intelligence and machine learning (AI\&ML) systems for decision support by describing a number of mo…
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…