⚖️ Ethical AI: Bias Mitigation and Trust Architecture

Analysis of ethical AI, moving beyond theoretical discussions to explore its practical implementation and governance. It outlines core principles for trustworthy AI, such as fairness, transparency, and accountability, emphasizing that ethical considerations must be integrated throughout the AI lifecycle, not merely as an afterthought. The document categorizes various sources and types of algorithmic bias, from data collection to deployment, providing real-world examples in high-stakes domains...