This paper explores the challenges around fair information access when the limits of human attention require algorithmic assistance for 'finding the diamond in the coal mountain'. While often demanded by users, the seemingly intuitive concept of fairness has proven to be very difficult to operationalise for implementation in algorithms. Here we present two pilot studies aimed at getting a better understanding of the conceptualisation of algorithmic fairness by users. The first was a multi-stakeholder focus-group discussion, the second a user experiment/questionnaire. Based on our data we arrive at a picture of fairness that is highly dependent on context and informedness of users, and possibly inherently misleading due to the implied projec...
Recommender systems can strongly influence which information we see online, e.g, on social media, an...
Recent research claims that information cues and system attributes of algorithmic decision-making pr...
In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorith...
This paper explores the challenges around fair information access when the limits of human attention...
Algorithmic fairness (AF) has been framed as a newly emerging technology that mitigates systemic dis...
Recommendation, information retrieval, and other information access systems pose unique challenges f...
Algorithmic fairness research is currently receiving significant attention, aiming to ensure that al...
As algorithms are increasingly used to make important decisions that affect human lives, ranging fro...
Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes ba...
International audienceFairness of algorithms is the subject of a large body of literature, of guides...
Growing concerns about the fairness of algorithmic decision-making systems have prompted a prolifera...
In a world where the algorithm can control the lives of society, it is not surprising that specific ...
Abstract Recent advances in machine learning methods have created opportunities to el...
The combination of increased availability of large amounts of fine-grained human behavioral data and...
Nowadays, it is widely recognized that algorithms risk to reproduce and amplify human bias that hist...
Recommender systems can strongly influence which information we see online, e.g, on social media, an...
Recent research claims that information cues and system attributes of algorithmic decision-making pr...
In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorith...
This paper explores the challenges around fair information access when the limits of human attention...
Algorithmic fairness (AF) has been framed as a newly emerging technology that mitigates systemic dis...
Recommendation, information retrieval, and other information access systems pose unique challenges f...
Algorithmic fairness research is currently receiving significant attention, aiming to ensure that al...
As algorithms are increasingly used to make important decisions that affect human lives, ranging fro...
Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes ba...
International audienceFairness of algorithms is the subject of a large body of literature, of guides...
Growing concerns about the fairness of algorithmic decision-making systems have prompted a prolifera...
In a world where the algorithm can control the lives of society, it is not surprising that specific ...
Abstract Recent advances in machine learning methods have created opportunities to el...
The combination of increased availability of large amounts of fine-grained human behavioral data and...
Nowadays, it is widely recognized that algorithms risk to reproduce and amplify human bias that hist...
Recommender systems can strongly influence which information we see online, e.g, on social media, an...
Recent research claims that information cues and system attributes of algorithmic decision-making pr...
In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorith...