Engineering and IT

Disciplinary considerations of generative AI

• Always independently verify information generated by the AI, using trusted and reliable sources.

• Use it as a tool to deepen your understanding of the theory, and develop thought processes to solve problems yourself. 

• Brainstorm an approach or a design to a solution first, and build off of your understanding of the problem statement. Use it as a companion to bounce ideas off!

• You will almost always have a better understanding of the overall scope of the project, and how each module of code fits together. AI may tend to not provide the best design in the larger scope of the task - use it as a tool to cross-check your own design, understand where bugs occur, etc.

• The AI may not be aware of all real-world constraints your problem might include. Whether it is available manufacturing methods, reliability of structural designs, or safety of any chemical processes. 

• Remember to filter out any sensitive or private data from anything you input into the AI, especially if it involves client information or proprietary data!

Real-world examples of generative AI in the discipline

 Some prompts to help in the discipline

• For programming, refer to the coding page

• Learning through analogies helps to unpack some of the more abstract concepts in engineering

• Exploring scenarios through guided case studies allows you to apply theory to practice

• Assisting with creative problem solving helps you connect different ideas and concepts

• Conducting market research explores practical implementations and applications