- Fairness and Privacy in Machine Learning🔍
- Improving fairness generalization through a sample|robust ...🔍
- Differential Privacy and Fairness in Decisions and Learning Tasks🔍
- Using Artificial Intelligence to Improve the Fairness and Equity of ...🔍
- A Review on Fairness in Machine Learning🔍
- Fairness and Bias in Artificial Intelligence🔍
- The possibilities and limits of algorithmic fairness 🔍
- Improving Fairness in Machine Learning Systems🔍
Improving Fairness and Privacy in Selection Problems
Fairness and Privacy in Machine Learning - Michaël Perrot
Fairness and Privacy have been extensively studied as individual constraints. ... Improving fairness and privacy in selection problems. arXiv e-prints, pages ...
Improving fairness generalization through a sample-robust ...
A common solution to mitigate it is to integrate and optimize a statistical fairness metric along with accuracy during the training phase.
Differential Privacy and Fairness in Decisions and Learning Tasks
The survey reviews the conditions under which privacy and fairness may be aligned or contrasting goals, analyzes how and why DP exacerbates bias and ...
Unraveling the Gordian Knot of implicit bias in jury selection: The problems of judge- dominated voir dire, the failed promise of Batson, and proposed ...
A Review on Fairness in Machine Learning - ACM Digital Library
This article presents an overview of the main concepts of identifying, measuring, and improving algorithmic fairness when using ML algorithms.
Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources ...
These approaches include pre-processing data, model selection, and post-processing decisions. However, each approach has its limitations and challenges, such as ...
The possibilities and limits of algorithmic fairness (Part 2) - Office of ...
It is the ethical concept of fairness applied to the domain of AI / ML . This combination has resulted in the creation of a new discipline, ...
Improving Fairness in Machine Learning Systems: What Do Industry ...
We identify areas of alignment and disconnect be- tween the challenges faced by teams in practice and the solutions proposed in the fair ML ...
Fairness of artificial intelligence in healthcare: review and ...
We then outline strategies for addressing fairness, such as the importance of diverse and representative data and algorithm audits. Additionally ...
AI Fairness in Data Management and Analytics: A Review on ... - MDPI
Resampling techniques, such as oversampling and undersampling, adjust data distribution to alleviate bias by equalizing group representation. Reweighting ...
Improving fairness of artificial intelligence algorithms in Privileged ...
Improved adversarial learning for fair classification. arXiv preprint arXiv:1901.10443. Chapelle; Chawla, Special issue on learning from imbalanced data sets, ...
Xueru Zhang - Google Scholar
Improving Fairness and Privacy in Selection Problems. MM Khalili, X Zhang, M Abroshan, S Sojoudi. the 35th AAAI Conference on Artificial Intelligence (AAAI 2021) ...
Algorithmic Fairness - GitHub Pages
... privacy research since both fairness and privacy can be enhanced ... Improving Fairness in Semi-Supervised Problems with Privileged-Group Selection. Bias.
Ethical Use of Training Data: Ensuring Fairness & Data Protection in AI
These biases can disadvantage certain groups, resulting in unfair model outputs if data selection and cleaning are not performed with bias ...
Improving fairness of artificial intelligence algorithms in Privileged ...
We first demonstrate that such a selection bias can lead to a high algorithmic bias, even if privileged and unprivileged groups are treated ...
On the Privacy Risks of Algorithmic Fairness
This is shown in various applications from computer vision [1] to word embed- ding [2]. Fair machine learning aims at addressing this issue [3, 4, 5, 6, 7, 8, 9 ...
What about fairness, bias and discrimination? - ICO
Simply removing any protected characteristics from the inputs the model uses to make a prediction is unlikely to be enough, as there are often variables which ...
Ethics and discrimination in artificial intelligence-enabled ... - Nature
To mitigate this issue, it is recommended to implement technical measures, such as unbiased dataset frameworks and improved algorithmic ...
Examining Bias and Privacy Concerns in AI Image Recognition
Ethical AI development must incorporate inclusivity, transparency, and fairness to mitigate discriminatory practices. Introduction to AI Image ...
Privacy concerns affect what content users share, and, thus, the type of ... improving fairness simply by using machine learning best practices.