Abstract The Fairness, Accountability, and Transparency (FAccT) literature tends to focus on
bias as a problem that requires ex post solutions (eg fairness metrics), rather than …

Purpose This paper aims to explore explainable artificial intelligence (XAI) in democracy,
proposing an applicable framework. With artificial intelligence's (AI) increasing use in …

The increasing use of AI decision systems in recruitment processes has created challenges,
including potential resistance from job applicants. To address this issue, drawing on …

The rapidly advancing domain of Explainable Artificial Intelligence (XAI) has sparked
significant interests in developing techniques to make AI systems more transparent and …

Supervised machine learning models rely on training datasets with positive (target class)
and negative examples. Therefore, the composition of the training dataset has a direct …

The aim of algorithmic recourse (AR) is generally understood to be the provision of"
actionable" recommendations to individuals affected by algorithmic decision-making …

As artificial intelligence is increasingly deployed in democracies around the world, there is
growing recognition of the need for transparency and accountability in Artificial Intelligence …