Artificial Intelligence Ethics for Engineers

In Artificial Intelligence Ethics for Engineers, you'll learn ...

• The fundamental concepts, capabilities, and limitations of artificial intelligence in engineering practice
• The ethical responsibilities of licensed professional engineers when using AI tools
• The practical application of the NSPE Code of Ethics to artificial intelligence-assisted engineering work
• How to responsibly integrate AI into engineering practice while protecting public safety and maintaining professional accountability

Overview

Preview a portion of this course before purchasing it.

Credit: 2 PDH

Length: 18 pages

This course provides professional engineers with a practical framework for understanding, evaluating, and ethically applying artificial intelligence in engineering practice. The course explains the fundamentals of artificial intelligence, machine learning, and generative AI while distinguishing their capabilities from human engineering judgment. It examines how AI is transforming engineering workflows, design optimization, predictive maintenance, analysis, and decision-making across multiple engineering disciplines. Particular emphasis is placed on the ethical responsibilities of professional engineers under the National Society of Professional Engineers (NSPE) Code of Ethics, including competence, responsible charge, public safety, confidentiality, transparency, and truthful reporting.

Through real-world examples and disciplinary case studies, participants learn the professional and legal consequences of relying on unverified AI-generated information. The course concludes with best practices for verification, documentation, governance, confidentiality, and continuous professional development, reinforcing that AI is a powerful engineering tool but can never replace the judgment, accountability, and ethical responsibilities of the licensed professional engineer.

Specific Knowledge or Skill Obtained

This course teaches the following specific knowledge and skills:

• The differences between artificial intelligence, machine learning, generative AI, and traditional engineering software
• The opportunities and limitations of AI across engineering design, analysis, maintenance, and project workflows
• The identification of AI risks including hallucinations, bias, black-box decision making, and data quality issues
• The ethical application of the NSPE Code of Ethics to AI-assisted engineering decisions
• The importance of responsible charge, professional competence, and independent engineering judgment when using AI
• The protection of confidential and proprietary client information when utilizing AI platforms
• The implementation of verification procedures for AI-generated calculations, reports, citations, and technical recommendations
• The legal, disciplinary, and professional consequences of improper AI use through engineering and legal case studies
• The development of governance, documentation, and accountability practices for responsible AI implementation
• How to maintain professional competence as AI technologies continue to evolve within engineering practice

Certificate of Completion

You will be able to immediately print a certificate of completion after passing a multiple-choice quiz consisting of 12 questions. PDH credits are not awarded until the course is completed and quiz is passed.