Over the last few years, the interpretability of classification models has been a very active area of research. Recently, the concept of interpretability was given a more specific legal context. In 2016, the EU adopted the General Data Protection Regulation (GDPR), containing the right to...

Over the last few years, the interpretability of classification models has been a very active area of research. Recently, the concept of interpretability was given a more specific legal context. In 2016, the EU adopted the General Data Protection Regulation (GDPR), containing the right to...

We show that disclosing machine predictions to affected parties can trigger self-fulfilling prophecies. In an investment game, we experimentally vary investors' and recipients' access to a machine prediction about recipients' likelihood to pay back an investment. Recipients who privately learn...

Abstract This paper provides an overview of machine learning models, as compared to traditional economic models. It also lays out emerging issues in law and economics that the machine learning methodology raises. In doing so, Asian contexts are considered. Law and economics scholarship has...

Machine learning algorithms are now frequently used in sensitive contexts that substantially affect the course of human lives, such as credit lending or criminal justice. This is driven by the idea that 'objective' machines base their decisions solely on facts and remain unaffected by human...

Machine learning algorithms are now frequently used in sensitive contexts that substantially affect the course of human lives, such as credit lending or criminal justice. This is driven by the idea that 'objective' machines base their decisions solely on facts and remain unaffected by human...