This beginner-friendly course explores the ethical and legal foundations of using Generative AI in software engineering. Learn key ethical frameworks, understand common types of bias in AI-generated code, and explore their real-world impact on development. Delve into legal considerations like data privacy, transparency, explainability, and compliance. Through real case studies including racial bias in facial recognition and data breaches discover strategies to build fair, responsible, and legally compliant AI systems. No prior AI ethics or legal knowledge is required. A basic understanding of software development is recommended. By the end of this course, you will be able to: - Explain core ethical frameworks guiding Generative AI development - Identify and mitigate bias in AI-generated software code - Understand legal risks around AI, including data privacy and licensing - Apply best practices to ensure transparency and regulatory compliance - Learn from real-world case studies to design trustworthy AI systems Ideal for software engineers, developers, and AI practitioners seeking to build ethical, bias-aware, and legally compliant GenAI applications.
What you'll learn
Explain core ethical frameworks guiding Generative AI development
Identify and mitigate bias in AI-generated software code
Understand legal risks around AI, including data privacy and licensing
Apply best practices to ensure transparency and regulatory compliance
Course objectives
Explore ethical and legal foundations of Generative AI
Delve into common types of bias and their impact
Learn from real case studies on ethical AI development