Why Engineers Will Love AII know I am not the first person to take on the topic of AI of late. But the conversation on how it could affect engineering in the broadest sense has not, as far as I have witnessed, been explored as much as it could be. In this post, I am going to go over some recent experiences I have had with AI in engineering, and then, from that, talk about what we could expect.
Can AI do engineering? Recently I have been developing an AI agent to help people like you think of ways they can be better engineers. I have trained it on the knowledge I have documented on best engineering practice and given examples of how to reply in certain cases. The agent is called Ingeny. Try it out here. This is the first version, and it is still evolving. So if you take the time to explore it to see how it can help you with things like your engineering skill development, career progression and working with other engineers, then you will help make it better. I would appreciate you taking the time to help evolve it. By the way, the plan is to keep it free so engineers can always use it as they wish and need. In the process of training Ingeny, I needed to train it to respond differently depending upon whether questions are about improving engineering expertise or about actually doing engineering. In the former it does not need to provide a warning that it is not a qualified engineer. In the latter, it should let you know that while it has offered as much insight as it can, into say a design for EMC, it is still up to you to do the engineering work. This proved to be demanding. AI is not good with that kind of nuance: is it an engineering question or a question about engineering? If AI can’t easily deal with the subtle difference between doing engineering and talking about engineering, then it’s probably not going to do well with the subtle differences within engineering problems that can have huge effects upon the nature of the optimum outcome. It is also going to have difficulty assessing all the systemic issues present, the best way to apply first principles, or the best way to frame. This is because the AI that seems to reason is, at this time, based on Large Language Models - words - and engineering, as I have noted before, is very visual (it’s often in the “mind’s eye”). Does this mean engineers are safe? For now, I can’t see AI understanding the challenges of something like reviewing the landscape to determine (or create) the best approach to building a bridge to cross an expanse of deep water. However, I understand that AI is only getting better. It is therefore only a matter of time until AI can do such things. I remain unsure how long that will be. Until then, it will be the same for engineers as what has been said for writers, medical practitioners and others. The question of whether it will be engineers or AI is the wrong question. The premise is that it will be engineers and AI, so the question then becomes: how will engineers use AI? And it’s probably going to be pretty good. Be the engineer you wanted to be Anecdote time. When I was in academia, I would sometimes ask my students who of them wanted to be the type of engineer who understands the fundamentals of theory and first principles, but wants to be more an ideas person who then gets other engineers to make the ideas happen. Everyone would put their hand up. I did this to show my students that the chances of them getting such a job, given the popularity of such a job, is minimal. That means they were all going to have to make the ideas happen as well as coming up with the ideas. However, AI has probably proved me wrong. While I think it will be some time until AI can truly do engineering work, I can see it, fairly soon, doing a lot of the grunt work so that we can be the ideas engineer. How would this work? Software engineers are showing us how this could play out. They have felt the brunt of AI more than others, because, out of all the engineering disciplines, software engineering is the most language based. And a Large Language Model is ideal for that kind of work. But while software engineers have been hit the hardest, they have also shown that they are valuable when it comes to the initial idea and providing the right prompt. That’s what could very well be the case for the rest of us engineers. Consider the following:
The major challenge I see is that we will need to establish how we will train engineers to get to the level where they can be the ones providing the initial instructions. Maybe that is a post for another time. What will come after this? There is a chance that one day AI can do our work. I am not one of those people who naively says “AI can never do my job.” But I am not saying I know it can either. So the best thing is to be ready for what could come. And if AI can one day do all the engineering, including the ingenious stuff, then it has probably also become smarter than us. And If it is that smart, then, like other smart entities (us), it will likely have pets. So work on being adorable to AI so it wants to keep you as a pet and make you happy - not a bad life really. What are your concerns? Do you have any thoughts about AI in engineering or any concerns? Share them with me in the comments. And also let me know how you go with Ingeny. Note And so you know, while I do get AI to help check my articles, I do write them. Usually on a Sunday night. But I will use AI to often generate my images - if I can’t find a suitable one online - and I sometimes dictate the article content to be cleaned up and written (this one was typed though).
0 Comments
|
AuthorClint Steele is an expert in how engineering skills are influenced by your background and how you can enhance them once you understand yourself. He has written a book on the - The Global Engineer - and this blog delves further into the topic. Archives
June 2025
Categories
All
|