AI Fundamentals – Unit III: Bias and Fairness in AI Systems

nit III – Bias and Fairness in AI Systems is an Open Educational Resource (OER) presentation developed for the undergraduate AI Fundamentals course. This presentation introduces the key concepts required to understand and evaluate AI systems from the perspective of ethics, fairness, transparency, accountability, security, privacy, inclusivity, sustainability, robustness, and reliability. The PPT explains how bias can arise in AI systems, why fairness is important, and how transparency and accountability contribute to trustworthy AI. It also discusses important considerations related to privacy, security, inclusivity, sustainability, robustness, and reliability, using simple explanations, real-world examples, diagrams, flowcharts, comparison tables, case studies, and visual learning approaches. Topics Covered Ethics in AI Bias in AI Systems Fairness in AI Systems Sources and effects of AI bias Transparency in AI Systems Accountability in AI Security in AI Systems Privacy and AI Inclusivity in AI Sustainability in AI Robustness of AI Systems Reliability of AI Systems Trustworthy and Responsible AI Real-world case studies Responsible AI lifecycle Learning Outcomes After studying this unit, learners will be able to: Explain ethical issues related to Artificial Intelligence. Identify different sources and effects of bias in AI systems. Explain the importance of fairness and transparency. Understand accountability in AI systems. Describe security and privacy considerations. Explain the importance of inclusivity and sustainability. Understand robustness and reliability in AI systems. Evaluate AI systems from a responsible and trustworthy AI perspective. Target Audience: Undergraduate students, particularly students studying Computer Science and related disciplines. Educational Use: This resource is intended for classroom teaching, self-learning, revision, examination preparation, and educational reuse in accordance with the OER license specified for the resource. Author:Dr C V KrishnaveniLecturer in Computer ScienceSKR & SKR Government College for Women (Autonomous)Kadapa, Andhra Pradesh, India