Fairness, Accountability, and Transparency in Machine Learning

Fairness, accountability, and transparency in machine learning are principles ensuring AI systems operate ethically and responsibly. Fairness means designing algorithms that treat all users equitably, avoiding bias and discrimination. Accountability involves holding creators and operators responsible for the AI's decisions, ensuring errors or harmful outcomes are addressed. Transparency refers to making the workings of AI understandable, so users and developers can see how decisions are made. Together, these principles promote trust, prevent harm, and ensure AI benefits society fairly and ethically.