Ethical Use of Agentic and Generative AI in Engineering

In Ethical Use of Agentic and Generative AI in Engineering, you'll learn ...

• The ethical principles governing the use of agentic and generative AI in engineering practice
• The distinctions between generative AI systems and agentic AI systems and their implications for professional responsibility
• The application of engineering codes of ethics, responsible charge requirements, and public safety obligations to AI-assisted work
• How to integrate AI technologies into engineering projects while maintaining accountability, transparency, and professional judgment

Overview

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Credit: 1 PDH

Length: 13 pages

This course provides engineers with a practical introduction to the ethical use of agentic and generative artificial intelligence across engineering practice. Participants learn the fundamental differences between generative AI systems, which create content and design alternatives, and agentic AI systems, which can autonomously make decisions and perform actions.

The course examines how these technologies are being applied in civil, structural, mechanical, aerospace, electrical, software, chemical, biomedical, and environmental engineering disciplines. Special emphasis is placed on professional responsibilities under engineering codes of ethics, including public safety, competence, transparency, confidentiality, accountability, and responsible charge.

Through real-world examples and discipline-specific applications, engineers explore the ethical risks associated with AI-generated designs, autonomous decision-making, bias, cybersecurity, intellectual property, and data privacy. The course also presents practical guidelines and best practices for validating AI outputs, maintaining human oversight, protecting sensitive information, and ensuring compliance with professional standards.

By the end of the course, participants will understand how to responsibly integrate AI technologies into engineering workflows while maintaining their ethical obligations to clients, employers, regulators, and the public.

Specific Knowledge or Skill Obtained

This course teaches the following specific knowledge and skills:

• The definitions, capabilities, and limitations of generative and agentic artificial intelligence technologies
• The ethical responsibilities associated with protecting public health, safety, and welfare when using AI tools
• The concept of responsible charge and its application to AI-generated engineering work products
• The evaluation and validation of AI-generated designs, calculations, reports, and recommendations
• The identification and mitigation of bias, fairness concerns, and data quality issues in AI systems
• The protection of confidential, proprietary, and personal information when using AI platforms
• The cybersecurity considerations associated with AI-enabled engineering systems and critical infrastructure
• The ethical challenges and opportunities of AI applications in civil, mechanical, electrical, chemical, software, and environmental engineering
• The implementation of human oversight, fail-safe mechanisms, and accountability controls for agentic AI systems
• How to develop organizational and professional best practices for ethical AI adoption and continuous learning in engineering practice

Certificate of Completion

You will be able to immediately print a certificate of completion after passing a multiple-choice quiz consisting of 10 questions. PDH credits are not awarded until the course is completed and quiz is passed.