Tensions in transparent urban AI: designing a smart electric vehicle charge point

The increasing use of artificial intelligence (AI) by public actors has led to a push for more transparency. Previous research has conceptualized AI transparency as knowledge that empowers citizens and experts to make informed choices about the use and governance of AI. Conversely, in this paper, we critically examine if transparency-as...

The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making

Governments look at explainable artificial intelligence's (XAI) potential to tackle the criticisms of the opaqueness of algorithmic decision-making with AI. Although XAI is appealing as a solution for automated decisions, the wicked nature of the challenges governments face complicates the use of XAI. Wickedness means that the facts that define...

Interpretable confidence measures for decision support systems

Decision support systems (DSS) have improved significantly but are more complex due to recent advances in Artificial Intelligence. Current XAI methods generate explanations on model behaviour to facilitate a user's understanding, which incites trust in the DSS. However, little focus has been on the development of methods that establish and...