Welcome to EthAIAuditHub - An Automated, Collaborative, ethical Bias Auditing Platform for ML models.This platform is designed to help ethically biased communities,developers, data scientists, policy makers and all the relavant stakeholders to assess and mitigate algorithmic biases in machine learning models effectively. By leveraging cutting-edge technologies and methodologies, this platform aims to uphold integrity, fairness in ML models which then automatically eliminate the ethical bias.
This repository contains a comprehensive Automated Auditing Framework for AI systems, designed to ensure transparency, fairness, and accountability in the development and deployment of ML models. By developing a meaningful automated platform with an AI assistant for addressing biases in algorithmic models, the developer aims at mitigating ethical bias which are not just technical glitches; but are societal challenges that necessitate collective attention and thoughtful solutions.
Engage with key stakeholders, including developers, data scientists, legal experts, and end-users. Maintain open communication channels to gather feedback and ensure a collaborative approach.File sharing, discussion forums, communities and real-time collaboration tools promote inclusivity and diverse contributions.
Utilization of IBM AIF 360, a framework with the highest accuracy in bias detection.Align the framework with relevant legal and ethical standards, emphasizing principles such as fairness, transparency, and accountability.
Execute Bias Mitigation Automation Workflow and EthAIAuditHub Experiment Workflow to have an automated experience in executing ipynb files leveraging github actions
Use in built AI assistance which is a GPT based platform that can streamline the process of bias detection, auditing your ipynb files and fixing bugs in executing ML models.
Experience a better UX with automatically executed log reports