Ethical Use of AI Agents and Agentic AI

Overview

This course is designed for anyone who wants to gain a deeper understanding about the importance of trust and responsibility in agentic AI and AI agents. The content is especially geared to those who are making business decisions based on AI agents and agentic AI and those who are designing and training such systems. 1. Distinguish between traditional AI agents and agentic AI systems in terms of scope, autonomy, and decision-making. 2. Apply six core ethical principles to real-world predictive modeling workflows and agentic system design. 3. Evaluate ethical considerations across five industry domains using structured scenario analysis. 4. Utilize practical tools—including documentation templates, ethics checklists, and governance prompts—to design trustworthy systems. 5. Understand emerging regulatory frameworks including the EU AI Act, U.S. federal and state regulations, and global AI governance resources. Who Should Attend: Data consumers, IT professionals, managers, analysts, data scientists, and anyone else who uses, designs, consumes information from, or makes decisions based on data and AI Prerequisites: 1. Responsible Innovation and Trustworthy AI

Syllabus

Ethics of AI Agents and Agentic AI

Define and compare AI agents and agentic AI systems. Analyze how scope, autonomy, oversight, adaptability, and ethical complexity vary between system types. Identify ethical vulnerabilities linked to increasing autonomy.

Core Ethical Principles for Agentic AI

Apply the six principles of responsible innovation to agentic AI development. Apply each principle to a predictive modeling use case within a marketing campaign. Reflect on trade-offs and intervention points in applied settings.

Examples and Ethical Considerations

Identify ethical risks within predictive modeling across five industries. Analyze complex scenarios using principle-driven reasoning. Facilitate or participate in collaborative discussions with structured guidance.

Practical Tools to Enable Designing for Trust

Use checklists and prompts to evaluate ethical alignment. Complete guided documentation of a predictive model. Rate and revise models using embedded ethical criteria.

Emerging Challenges and Governance

Explain how ethical risks increase with autonomy in agentic AI. Know where to find information about key provisions of the regulatory landscape in different countries around the world. Access and interpret global regulatory sources.