Abstract:

In this talk I will pick up threads of research dating back to early work in the 1990s on gender and ethnic bias in black-box machine-learning systems, as well as more recent developments such as deep learning and concerns such as those that gave rise to the EPSRC human–like computing programme. In particular I will present nascent work on an AIX Toolkit (AI explainability): a structured collection of techniques designed to help developers of intelligent systems create more comprehensible representations of the reasoning.  Crucial to the AIX Toolkit is the understanding that human–human explanations are rarely utterly precise or reproducible, but they are sufficient to inspire confidence and trust in a collaborative endeavour.