Fairness in ranking, part i: Score-based ranking
In the past few years, there has been much work on incorporating fairness requirements into
algorithmic rankers, with contributions coming from the data management, algorithms …
algorithmic rankers, with contributions coming from the data management, algorithms …
Factoring the matrix of domination: A critical review and reimagination of intersectionality in ai fairness
Intersectionality is a critical framework that, through inquiry and praxis, allows us to examine
how social inequalities persist through domains of structure and discipline. Given AI fairness' …
how social inequalities persist through domains of structure and discipline. Given AI fairness' …
Fairness in information access systems
Recommendation, information retrieval, and other information access systems pose unique
challenges for investigating and applying the fairness and non-discrimination concepts that …
challenges for investigating and applying the fairness and non-discrimination concepts that …
Are “intersectionally fair” ai algorithms really fair to women of color? a philosophical analysis
Y Kong - Proceedings of the 2022 ACM Conference on Fairness …, 2022 - dl.acm.org
A growing number of studies on fairness in artificial intelligence (AI) use the notion of
intersectionality to measure AI fairness. Most of these studies take intersectional fairness to …
intersectionality to measure AI fairness. Most of these studies take intersectional fairness to …
Fairness in ranking: A survey
In the past few years, there has been much work on incorporating fairness requirements into
algorithmic rankers, with contributions coming from the data management, algorithms …
algorithmic rankers, with contributions coming from the data management, algorithms …
Enhancing AI fairness through impact assessment in the European Union: a legal and computer science perspective
A Calvi, D Kotzinos - Proceedings of the 2023 ACM Conference on …, 2023 - dl.acm.org
How to protect people from algorithmic harms? A promising solution, although in its infancy,
is algorithmic impact assessment (AIA). AIAs are iterative processes used to investigate the …
is algorithmic impact assessment (AIA). AIAs are iterative processes used to investigate the …
Responsible data management
The need for responsible data management intensifies with the growing impact of data on
society. One central locus of the societal impact of data are Automated Decision Systems …
society. One central locus of the societal impact of data are Automated Decision Systems …
Mitigating bias in set selection with noisy protected attributes
A Mehrotra, LE Celis - Proceedings of the 2021 ACM conference on …, 2021 - dl.acm.org
Subset selection algorithms are ubiquitous in AI-driven applications, including, online
recruiting portals and image search engines, so it is imperative that these tools are not …
recruiting portals and image search engines, so it is imperative that these tools are not …
German ai start-ups and “ai ethics”: Using a social practice lens for assessing and implementing socio-technical innovation
M Sloane, J Zakrzewski - Proceedings of the 2022 ACM Conference on …, 2022 - dl.acm.org
The current AI ethics discourse focuses on developing computational interpretations of
ethical concerns, normative frameworks, and concepts for socio-technical innovation. There …
ethical concerns, normative frameworks, and concepts for socio-technical innovation. There …
Fair ranking with noisy protected attributes
A Mehrotra, N Vishnoi - Advances in Neural Information …, 2022 - proceedings.neurips.cc
The fair-ranking problem, which asks to rank a given set of items to maximize utility subject
to group fairness constraints, has received attention in the fairness, information retrieval, and …
to group fairness constraints, has received attention in the fairness, information retrieval, and …