1. Introduction to Trustworthy AI

In this chapter, we will go through an introduction to trustworthy AI. We begin by evaluating the scope of what qualifies as trustworthy AI, how it extends beyond performance metrics, and how it integrates ethics. As AI is becoming a vital part of all industries, the discussion around fairness, transparency, and safety has become a significant area of focus. Furthermore, we review the definitions and foundational principles established by the European Commission, which are based on three pillars: lawfulness, ethical alignment, and robustness. We also briefly discuss the NIST definitions of trustworthy AI and the characteristics outlined by it. The chapter further explores the concept of the trust imperative, discussing the widespread skepticism and suspicion prevalent with AI. Discussing key characteristics for building trustworthy AI systems, and then concluding with technical implementations. Technical implementations that focus on AI safety, bias mitigation, and privacy protection of user data. This chapter aims to outline a guide on how to develop AI systems that are considered trustworthy by focusing on ethics, transparency, and the benefit of society.