… forms of bias can occur, automation is their common ground. The paper highlights the role
of automation and explains why deep automation bias (DAB) is a metarisk of AI. Based on …

… an approach that focuses on a meta-risk inherent in AI systems: deep automation bias. It is
… Bias in ML is a wicked problem inherent to AI. However, unbiasing and fostering FAT is not …

… cultural meanings, and artificial intelligence (AI). This work … to prevent unintended biases
in AI algorithms is crucial. … we can facilitate a deeper understanding of human cognition …

… It then identifies how AI-based digital technologies can once … There is more to AI than
perceptual computing’s deep … real-time AI to address the many human biases that underpin much …

… “easy problem” can be provisionally solved by tackling bias, … to governing AI systems, which
we label the “easy problem” of AI … The “easy problem” concerns how organizations’ use of AI …

… when dealing with the wicked problems we face on larger … We are prone to a range of
biases and heuristics that skew … in the face of deep uncertainty inherent to wicked problems, …

… Machine learning (ML) and deep learning (DL) are strategies for making AI … the AI discourse,
issues related to data bias and algorithmic discrimination occur most frequently. Automated …

… wicked problems into more nuanced categories to understand better what makes such …
decision problems under ‘great’ or ‘deep’ uncertainty. For example, wicked policy problems are …

… of ethical concerns regarding AI applications and, in this paper, we will focus more
concretely on bias leading to potential discrimination. While it is true that on the one hand, AI-infused …

… Contrary to the perception of AI as a neutral tool, biases in its use and practices of … questions
about AI's compatibility with democratic values. This thesis argues that if the use of AI in the …