COURSE OUTLINE

Day 1: Ethical Foundations of AI

Focus: Building a moral compass for GenAI deployment.

• Introduction to AI Ethics: Defining the ethical stakes of Generative AI; why LLMs require unique moral scrutiny.
• The Problem of Bias & Fairness:
• Identifying historical bias in training datasets.
• Strategies for achieving "Fairness by Design" in Google Gemini applications.
• Transparency & Explainability:
• Bridging the gap between complex neural networks and stakeholder understanding.
• Using Google’s Interpretability Tools to explain model decision-making.
• Responsible AI Principles: Deep dive into Google’s 7 AI Principles—from "Socially Beneficial" to "Privacy-Forward."
• Data Privacy & Sovereign AI:
• Managing PII (Personally Identifiable Information) during model fine-tuning.
• The role of Confidential Computing in protecting sensitive datasets.
• Societal Impacts: Analyzing the effect of AI on labor, misinformation (Deepfakes), and digital equity.
• Hands-on Workshop: Developing an Ethical Decision-Making Framework for a high-stakes AI use case (e.g., Automated Loan Approvals).

Day 2: AI Governance and Compliance

Focus: Turning ethics into enforceable organizational policy.

• AI Governance Frameworks: Introduction to the Google Secure AI Framework (SAIF) and its application in 2026.
• Regulatory Landscapes:
• Navigating the EU AI Act and emerging global AI mandates.
• Preparing for mandatory audits and technical documentation requirements.
• AI Risk Management:
• Conducting Impact Assessments for Generative AI projects.
• Red-teaming models to discover vulnerabilities and "hallucination" triggers.
• Security, Trust, & Watermarking:
• Leveraging SynthID for content authenticity.
• Ensuring trust through model versioning and lineage tracking.
• Organizational Models: Establishing an "AI Ethics Board" and defining the roles of the Chief AI Officer vs. Compliance.
• Human Oversight: Designing effective "Human-in-the-loop" (HITL) workflows to prevent autonomous model failure.
• Building Responsible AI Policies: Crafting an internal "Acceptable Use Policy" for employee interaction with Gemini.
• Future Trends: Preparing for Agentic Governance—how to manage AI agents that act autonomously.
• Final Project: Drafting a Corporate AI Governance Roadmap that balances rapid innovation with regulatory safety.