How can we ensure that Ubiquitous Computing (UbiComp) research outcomes are both ethical and fair? While fairness in machine learning (ML) has gained traction in recent years, fairness in UbiComp remains unexplored. This workshop aims to discuss fairness in UbiComp research and its social, technical, and legal implications. From a social perspective, we will examine the relationship between fairness and UbiComp research and identify pathways to ensure that ubiquitous technologies do not cause harm or infringe on individual rights. From a technical perspective, we will initiate a discussion on data practices to develop bias mitigation approaches tailored to UbiComp research. From a legal perspective, we will examine how new policies shape ou...
Frameworks for fair machine learning are envisioned to play an important practical role in the evalu...
Many machine learning systems make extensive use of large amounts of data regarding human behaviors....
Thesis (Master's)--University of Washington, 2018Machine learning plays an increasingly important ro...
The field of mobile, wearable, and ubiquitous computing (UbiComp) is undergoing a revolutionary inte...
Machine learning is part of the daily life of people and companies worldwide. Unfortunately, machine...
Over the last years, a wide spread of Machine Learning in increasingly more, especially sensitive ar...
Recent years have seen the development of many open-source ML fairness toolkits aimed at helping ML ...
Machine learning is part of the daily life of people and companies worldwide. Unfortunately, bias in...
With the growing prevalence of AI algorithms and their use to prepare and even execute decisions, th...
The problem of fair machine learning has drawn much attention over the last few years and the bulk o...
The ability to identify and mitigate various risks and harms of using Machine Learning models in ind...
The increasing dangers of unfairness in machine learning (ML) are becoming a frequent subject of dis...
To encourage ethical thinking in Machine Learning (ML) development, fairness researchers have create...
As the complexity and capabilities of AI technologies continue to increase, they will continue to po...
International audienceFairness emerged as an important requirement to guarantee that Machine Learnin...
Frameworks for fair machine learning are envisioned to play an important practical role in the evalu...
Many machine learning systems make extensive use of large amounts of data regarding human behaviors....
Thesis (Master's)--University of Washington, 2018Machine learning plays an increasingly important ro...
The field of mobile, wearable, and ubiquitous computing (UbiComp) is undergoing a revolutionary inte...
Machine learning is part of the daily life of people and companies worldwide. Unfortunately, machine...
Over the last years, a wide spread of Machine Learning in increasingly more, especially sensitive ar...
Recent years have seen the development of many open-source ML fairness toolkits aimed at helping ML ...
Machine learning is part of the daily life of people and companies worldwide. Unfortunately, bias in...
With the growing prevalence of AI algorithms and their use to prepare and even execute decisions, th...
The problem of fair machine learning has drawn much attention over the last few years and the bulk o...
The ability to identify and mitigate various risks and harms of using Machine Learning models in ind...
The increasing dangers of unfairness in machine learning (ML) are becoming a frequent subject of dis...
To encourage ethical thinking in Machine Learning (ML) development, fairness researchers have create...
As the complexity and capabilities of AI technologies continue to increase, they will continue to po...
International audienceFairness emerged as an important requirement to guarantee that Machine Learnin...
Frameworks for fair machine learning are envisioned to play an important practical role in the evalu...
Many machine learning systems make extensive use of large amounts of data regarding human behaviors....
Thesis (Master's)--University of Washington, 2018Machine learning plays an increasingly important ro...