Automated decision-making systems implemented in public life are typically standardized. One algorithmic decision-making system can replace thousands of human deciders. Each of the humans so replaced had her own decision-making criteria: some good, some ...

Algorithms are now routinely used to make consequential decisions that affect human lives. Examples include college admissions, medical interventions or law enforcement. While algorithms empower us to harness all information hidden in vast amounts of ...

In this paper, we present TILT, a transparency information language and toolkit explicitly designed to represent and process transparency information in line with the requirements of the GDPR and allowing for a more automated and adaptive use of such ...

Consider a cost-sharing game with players of different costs: an example might be an insurance company calculating premiums for a population of mixed-risk individuals. Two natural and competing notions of fairness might be to a) charge each individual ...

Government agencies are embracing machine learning to support a variety of resource allocation decisions. The U.S. Environmental Protection Agency (EPA), for example, has engaged academic research labs to test the use of machine learning in support of ...

Price discrimination - offering different prices to different customers - has become common practice. While it allows sellers to increase their profits, it also raises several concerns in terms of fairness. This topic has received extensive attention ...