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AI Trust Calibration and Over-Automation Risks Fundamentals
"AI Trust Calibration and Over-Automation Risks Fundamentals" addresses how to build user confidence in AI without over-delegating authority. Learn to balance automation and human judgment while recognizing the limits of AI. Cybersecurity threats are discussed in the context of trust manipulation and over-automation leading to security blind spots. The course teaches how to build trustworthy, cyber-resilient AI systems that support informed human decision-making.
Provider Information
Tonex, Inc.
6275 W. Plano Parkway, Suite 500
Plano, TX 75093
Course Overview
None
Learning Objectives
- Understand the principles of AI trust calibration and over-automation risks.
- Analyze the factors that influence trust in AI systems.
- Evaluate the strategies for calibrating human trust in AI.
- Identify the risks associated with over-automation and reliance on AI.
- Discuss the ethical and operational implications of AI trust and over-automation.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.