Despite its constitutional relevance, the technical “individual fairness” criterion has not been operationalized in U.S. state or federal statutes/regulations. We conduct a human subjects experiment to address this gap, evaluating which demographic features are relevant for individual fairness evaluation of recidivism risk assessment (RRA) tools. Our analyses conclude that the individual similarity function should consider age and sex, but it should ignore race.

Previous work on extracting ideology from text has focused on domains where expression of political views is expected, but it's unclear if current technology can work in domains where displays of ideology are considered inappropriate.We present a supervised ensemble n-gram model for ideology extraction with topic adjustments and apply it to one such domain: research papers written by academic economists.We show economists' political leanings can be correctly predicted, that our predictions generalize to new domains, and that they correlate with public policy-relevant research findings.We also present evidence that unsupervised models can under-perform in domains where ideological expression is discouraged.

This paper explores the incentive schemes that have been used by cyberlockers, and examines to what extent they have helped to foster the current environment. This short paper also presents a preliminary economic analysis of incentives in cyberlockers based on measurement results from three different types of sites related to cyberlockers- a search engine, a discussion forum, and a popular cyberlocker site.