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Ethical Use of AI Agents and Agentic AI

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Ethical Use of AI Agents and Agentic AI

This course is part of AI Literacy: Responsible, Trustworthy, Effective Specialization

Instructor: Catherine Truxillo

Included with

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5 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Agentic Workflows

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the AI Literacy: Responsible, Trustworthy, Effective Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

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

Module details

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.

What's included

15 videos2 readings4 assignments

15 videosTotal 15 minutes

Course Overview1 minute
Objectives1 minute
Module Overview0 minutes
Objectives0 minutes
What is an AI Agent?0 minutes
What is Agentic AI?1 minute
Comparison: AI Agent vs. Agentic AI1 minute
Scope of Action2 minutes
Autonomy Level1 minute
Example: Loan Application Approval2 minutes
Example: Medical Diagnostic Tests1 minute
Human Oversight1 minute
Adaptability1 minute
Example: Reward Hacking2 minutes
Ethical Complexity1 minute

2 readingsTotal 20 minutes

Course Syllabus10 minutes
Historical Timeline10 minutes

4 assignmentsTotal 120 minutes

Knowledge Check: Traditional AI Agent30 minutes
Knowledge Check: Agentic AI30 minutes
Knowledge Check: Human Oversight30 minutes
Knowledge Check: Ethical Challenges30 minutes

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.

What's included

11 videos

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.

What's included

8 videos

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

What's included

9 videos

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.