How has recent AI Ethics literature addressed topics such as fairness and justice in the
context of continued social and structural power asymmetries? We trace both the historical …

Pairwise learning strategies are prevalent for optimizing recommendation models on implicit
feedback data, which usually learns user preference by discriminating between positive (ie …

Data-driven algorithms are studied and deployed in diverse domains to support critical
decisions, directly impacting people's well-being. As a result, a growing community of …

A growing community of researchers has been investigating the equity of algorithms,
advancing the understanding of risks and opportunities of automated decision-making for …

With the increasing use of AI in algorithmic decision making (eg based on neural networks),
the question arises how bias can be excluded or mitigated. There are some promising …

In 2019, a group of computer and social scientists began a project to 'converge'the two
disciplines, with the aim of harnessing data from social media to improve our understanding …

Questa tesi supporta la misurazione dell'equità algoritmica da una prospettiva incentrata sui
dati. In primo luogo, affrontiamo il problema della selezione dei dataset, evidenziando le …