Fairium — Responsible AI Platform

Overview

Fairium is a Responsible AI platform developed by Mohitrajsinh Jadeja for evaluating model fairness, generating explainability metrics (XAI), and detecting demographic bias across machine learning datasets and models.

The Problem

Machine learning algorithms often inadvertently amplify historical biases in training data, resulting in discriminatory automated decision-making and lack of transparency for end-users.

The Solution

Fairium provides automated metrics for disparate impact, equalized odds, and feature importance attribution, equipping AI engineers with actionable recommendations for debiasing machine learning workflows.

Key Features

• Fairness Metrics Evaluation: Automated measurement of statistical parity and demographic parity.
• Explainable AI (XAI): Model feature attribution heatmaps and local feature importance explanations.
• Automated Bias Detection: Data auditing for protected attribute disparities prior to model deployment.
• Ethical Governance Reporting: PDF and interactive summary reports for AI compliance.

Technical Stack & Architecture

Role & Technical Decisions

• AI Systems Engineer: Built mathematical fairness metric routines and debiasing transformations.
• Ethical Framework Implementation: Focused on practical algorithmic auditing tools accessible to data science teams.