112 citations
- The Open UniversityGB6 papers
- University of AlicanteES5 papers
- Imperial College LondonGB4 papers
- Cardiff UniversityGB3 papers
- IBM Research - ZurichCH3 papers
- IBM (United States)US3 papers
- University of OxfordGB3 papers
- University of SheffieldGB3 papers
- European Space AgencyFR2 papers
- Isaac Newton InstituteCL2 papers
- Pulkovo ObservatoryRU2 papers
- Sci-Tech DaresburyGB2 papers
Showing 2018 · cs.AIShow all
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cs.AI2018★ 42 cited
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…
cs.AI2018★ 83 cited
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…