Abstract Explainable Artificial Intelligence (XAI) has experienced a significant growth over
the last few years. This is due to the widespread application of machine learning, particularly …

A key insight from research on organizational justice is that fairness is in the eye of the
beholder. With increasing discussions–especially among computer scientists and …

The use of black box algorithms in medicine has raised scholarly concerns due to their
opaqueness and lack of trustworthiness. Concerns about potential bias, accountability and …

The goal of this study is to investigate the direct and indirect relationships that exist between
artificial intelligence (AI), social innovation (SI), and smart decision-making (SDM). This …

What stories are told in national artificial intelligence (AI) policies? Combining the novel
technique of structural topic modeling (STM) and qualitative narrative analysis, this paper …

Abstract Algorithms based on Artificial Intelligence technologies are slowly transforming
street‐level bureaucracies, yet a lack of algorithmic transparency may jeopardize citizen …

In this paper, we present a fundamental framework for defining different types of
explanations of AI systems and the criteria for evaluating their quality. Starting from a …

Recently, the AI/ML research community has indicated an urgent need to establish
Responsible AI (RAI) values and practices as part of the AI/ML lifecycle. Several …

The present case study examines the product landscape of current AI-empowered co-
creative tools. Specifically, I review literature in both creativity and HCI research and …

Using a survey experiment on the topic of tax auditing, we investigate artificial intelligence
(AI) use in government decision making through the lenses of citizen red tape and trust. We …