Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges. Accenture: Fairness in algorithmic decision-making We were tasked with evaluating fairness in its myriad forms, and mapping the various expressions of fairness to the data science workflow. Accenture challenged us to aggregate and organise the elements of the fairness literature into a manageable structure, and to provide meaningful visualisations that facilitate productive discussions around fairness in an analytical project. In this study, we focus on financial services and, in particular, on credit allowance in ...
The utility of machine learning in evaluating the creditworthiness of loan applicants has been proof...
The SHARC (SHAring Reward & Credit) interest group (IG) is an interdisciplinary group set up in the ...
International audienceIssues of responsible data analysis and use are coming to the forefront of the...
The data science era is characterized by data-driven automated decision systems (ADS) enabling,...
Data-driven algorithms are studied in diverse domains to support critical decisions, directly impact...
This dataset presents the description and the references for the datasets used in the fairness liter...
Artificial intelligence is based, in part, on learning algorithms that can continually monitor and e...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
A growing community of researchers has been investigating the equity of algorithms, advancing the un...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
Automated decision systems are increasingly used to take consequential decisions in problems such as...
Machine learning is still one of the most rapidly growing fields, and is used in a variety of differ...
Group fairness means that different groups have an equal probability of being predicted for one aspe...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
The importance of this work lays primarily in that, while others have looked into how the end users ...
The utility of machine learning in evaluating the creditworthiness of loan applicants has been proof...
The SHARC (SHAring Reward & Credit) interest group (IG) is an interdisciplinary group set up in the ...
International audienceIssues of responsible data analysis and use are coming to the forefront of the...
The data science era is characterized by data-driven automated decision systems (ADS) enabling,...
Data-driven algorithms are studied in diverse domains to support critical decisions, directly impact...
This dataset presents the description and the references for the datasets used in the fairness liter...
Artificial intelligence is based, in part, on learning algorithms that can continually monitor and e...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
A growing community of researchers has been investigating the equity of algorithms, advancing the un...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
Automated decision systems are increasingly used to take consequential decisions in problems such as...
Machine learning is still one of the most rapidly growing fields, and is used in a variety of differ...
Group fairness means that different groups have an equal probability of being predicted for one aspe...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
The importance of this work lays primarily in that, while others have looked into how the end users ...
The utility of machine learning in evaluating the creditworthiness of loan applicants has been proof...
The SHARC (SHAring Reward & Credit) interest group (IG) is an interdisciplinary group set up in the ...
International audienceIssues of responsible data analysis and use are coming to the forefront of the...