This blog explores the myth of fairness in AI-based decision-making. It highlights how algorithms used in courts, hiring, and welfare systems can replicate social biases, lack context, and remain opaque. True fairness requires more than good code — it demands ethical oversight, diverse perspectives, and critical questioning.
Artificial intelligence learns not through memorization but by identifying patterns in data. This module explores the three main types of machine learning—supervised, unsupervised, and reinforcement—and explains how each allows AI systems to improve over time. Understanding these methods helps us grasp both AI’s power and its ethical challenges.
Artificial Intelligence (AI) is the science of building machines and systems that can think, learn, and make decisions like humans — or sometimes even better. From virtual assistants to self-driving cars, AI is transforming how we live, work, and connect. But it’s not just about speed or automation; it’s about teaching machines to understand, reason, and adapt. This module will guide you through what AI really is, how it works, and why it matters.