Growing concerns regarding algorithmic fairness have led to a surge in
m...
In recent years, the CHI community has seen significant growth in resear...
Algorithmic bias often arises as a result of differential subgroup valid...
Human-AI complementarity is important when neither the algorithm nor the...
Explanations have been framed as an essential feature for better and fai...
In many real world contexts, successful human-AI collaboration requires
...
The extensive adoption of business analytics (BA) has brought financial ...
An increased awareness concerning risks of algorithmic bias has driven a...
Effective human-AI collaboration requires a system design that provides
...
Faced with the scale and surge of misinformation on social media, many
p...
It is known that recommendations of AI-based systems can be incorrect or...
Many modern learning algorithms mitigate bias by enforcing fairness acro...
There has been a surge of recent interest in sociocultural diversity in
...
Human-machine complementarity is important when neither the algorithm no...
Police departments around the world have been experimenting with forms o...
Due to their promise of superior predictive power relative to human
asse...
The increased use of algorithmic predictions in sensitive domains has be...
This is the proceedings of the 3rd ML4D workshop which was help in Vanco...
After the peace agreement of 2016 with FARC, the killings of social lead...
There is a growing body of work that proposes methods for mitigating bia...
We present a large-scale study of gender bias in occupation classificati...
This is the Proceedings of NeurIPS 2018 Workshop on Machine Learning for...
This paper presents an algorithm for enumerating biases in word embeddin...
We explore the problem of learning under selective labels in the context...
This is the Proceedings of NIPS 2017 Workshop on Machine Learning for th...
When sexual violence is a product of organized crime or social imaginary...
We present an extension of sparse Canonical Correlation Analysis (CCA)
d...
We compute approximate solutions to L0 regularized linear regression usi...