The need for citizens to better understand the ethical and social challenges of algorithmic
systems has led to a rapid proliferation of AI literacy initiatives. After reviewing the literature …

The application of regulatory technology (RegTech) for monitoring comprehensive data
sources has gained increased importance. Nevertheless, previous research neglects that …

There is a growing movement in undergraduate computer science (CS) programs to embed
ethics across CS classes rather than relying solely on standalone ethics courses. One …

Prior work has developed responsible AI (RAI) toolkits and studied how AI practitioners use
such resources when practicing RAI. However, AI practitioners may not have the relevant …

Responsible AI (RAI) is an emerging topic in the Information Systems (IS) literature. RAI
entails ensuring ethical, transparent, and accountable use of AI technologies in line with …

This paper proposes a methodology to feature sorting as well as feature selection in the
context of supervised machine learning algorithms. Feature sorting has been revealed as a …

This paper explores the use of an architectural perspective to study complex data
ecosystems and to facilitate a normative discourse on such ecosystems. It argues that an …

Law and legal studies has been an exciting new field for data science applications whereas
the technological advancement also has profound implications for legal practice. For …

The need for citizens to better understand the ethical and social challenges of algorithmic
systems has led to a rapid proliferation of AI literacy initiatives. After reviewing the literature …

This paper analyzes the lessons of data-driven economics, investigating the prospects for
applying the principles of Data Science on Law, or simply data-driven law. By understanding …