Ethics in Generative AI for Software Engineering

Generative AI is transforming how we write code, but it also introduces complex questions about intellectual property, bias, and data privacy. Understanding how to use these tools responsibly is no longer optional for modern software professionals. This text-based course guides you through the essential ethical and legal frameworks needed to integrate generative AI tools into your daily development workflow safely. You will transition from simply using AI tools to evaluating their output for security, compliance, and fairness. What you'll learn: Understand the fundamental ethical principles and legal foundations of generative AI in software development; Analyze licensing, copyright, and intellectual property risks associated with AI-generated code; Identify and mitigate bias, security vulnerabilities, and privacy risks in AI outputs; Apply responsible AI frameworks and best practices to your daily coding workflows; Navigate modern data privacy standards and compliance requirements when prompting AI models. Starting with foundational definitions and ethical concepts, the course moves into practical scenarios, analyzing licensing dilemmas and code security audits through clear, written explanations and code examples. This course is designed for software engineers, developers, and tech leads of all levels who want to use AI tools responsibly, with no prior experience in AI ethics required. Start learning today to build a responsible, compliant, and future-proof development practice.