Fairness in rankings and recommendations: an overview
We increasingly depend on a variety of data-driven algorithmic systems to assist us in many
aspects of life. Search engines and recommender systems among others are used as …
aspects of life. Search engines and recommender systems among others are used as …
Fairness perceptions of algorithmic decision-making: A systematic review of the empirical literature
Algorithmic decision-making increasingly shapes people's daily lives. Given that such
autonomous systems can cause severe harm to individuals and social groups, fairness …
autonomous systems can cause severe harm to individuals and social groups, fairness …
Toward algorithmic accountability in public services: A qualitative study of affected community perspectives on algorithmic decision-making in child welfare services
A Brown, A Chouldechova… - Proceedings of the …, 2019 - dl.acm.org
Algorithmic decision-making systems are increasingly being adopted by government public
service agencies. Researchers, policy experts, and civil rights groups have all voiced …
service agencies. Researchers, policy experts, and civil rights groups have all voiced …
A qualitative exploration of perceptions of algorithmic fairness
A Woodruff, SE Fox, S Rousso-Schindler… - Proceedings of the 2018 …, 2018 - dl.acm.org
Algorithmic systems increasingly shape information people are exposed to as well as
influence decisions about employment, finances, and other opportunities. In some cases …
influence decisions about employment, finances, and other opportunities. In some cases …
How do fairness definitions fare? Examining public attitudes towards algorithmic definitions of fairness
What is the best way to define algorithmic fairness? While many definitions of fairness have
been proposed in the computer science literature, there is no clear agreement over a …
been proposed in the computer science literature, there is no clear agreement over a …
Racial categories in machine learning
S Benthall, BD Haynes - Proceedings of the conference on fairness …, 2019 - dl.acm.org
Controversies around race and machine learning have sparked debate among computer
scientists over how to design machine learning systems that guarantee fairness. These …
scientists over how to design machine learning systems that guarantee fairness. These …
Investigating ad transparency mechanisms in social media: A case study of Facebook's explanations
Targeted advertising has been subject to many privacy complaints from both users and
policy makers. Despite this attention, users still have little understanding of what data the …
policy makers. Despite this attention, users still have little understanding of what data the …
Human decision making with machine assistance: An experiment on bailing and jailing
N Grgić-Hlača, C Engel, KP Gummadi - … of the ACM on human-computer …, 2019 - dl.acm.org
Much of political debate focuses on the concern that machines might take over. Yet in many
domains it is much more plausible that the ultimate choice and responsibility remain with a …
domains it is much more plausible that the ultimate choice and responsibility remain with a …
What makes a “bad” ad? user perceptions of problematic online advertising
Online display advertising on websites is widely disliked by users, with many turning to ad
blockers to avoid “bad” ads. Recent evidence suggests that today's ads contain potentially …
blockers to avoid “bad” ads. Recent evidence suggests that today's ads contain potentially …
Measuring non-expert comprehension of machine learning fairness metrics
Bias in machine learning has manifested injustice in several areas, such as medicine, hiring,
and criminal justice. In response, computer scientists have developed myriad definitions of …
and criminal justice. In response, computer scientists have developed myriad definitions of …