Module 5: Virtualized Unbiasing Framework
Serving as a visual catalog, it facilitates exploration, comparison, and informed tool selection, thereby fostering a more effective approach to bias mitigation. Additionally, Bias Detector Toolkit is a part of VUF, where we are developing bias detection tools for specific contexts of use cases on the project, and will be presented in a later edition of MOOC.
The Virtualized Unbiasing Framework is a holistic application focused on explaining AI bias and equipping developers with an easy-to-navigate and visually organized catalog. It consists of the scrollytelling application, real life examples and the catalog of methods and tools for bias mitigation.
In Module 5, we cover:
Lesson 5.1: Scrollytelling Application
Lesson 5.2: Stages of AI Trainings
Lesson 5.3: Real Life Examples
Lesson 5.4: Catalog of Bias Detection and Mitigation Strategies
LESSON 5.4: CATALOG OF BIAS DETECTION AND MITIGATION STRATEGIES
The Catalogue builds upon training steps, providing tools and mitigation techniques for each of the steps of training AI models. The central idea is not to create another text heavy framework, but to provide a visual summary of existing bias detection and mitigation strategies in an approachable and easy-to-grasp format.
For the Bias Detector Catalogue, we have executed an extensive literature overview for bias mitigation techniques, that are collected in our Gitlab repo.They serve as the input for the interactive visual synthesis on the AI4gov platform.
Watch the Demo of the Bias Detector Catalog showcasing the examples of tools that can be utilized to detect or mitigate bias.
Congratulations on completing Module 5! Now you can advance to Module 6. Just one more to go!