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Gerry O'Brien's avatar

In the past, I authored several technical books. Topics focused on computer hardware and software configuration, computer networks, and software development. AI did not exist at that time. I dealt with copy editors and technical editors, along with technical reviewers.

I argued consistently with copy editors because they understood US English, but not technology. Their constant need to massage wording to fit the grammatical rules collided with the jargon and terminology used in the computing industry.

I argued consistently with technical editors who wanted to rewrite my phrasing because it was somehow different than how they would "portray" it. I had to constantly remind them that I was the author of the book and it needed to have my "signature" on it. That meant, my writing style. I even penned a chapter in a book on connecting Windows XP to Linux and vice versa. The main author of the book, in his feedback, noted that the content did not "sound like him". Well DUH!

As for AI, I have been teaching AI concepts since 2020. It started with what Microsoft called Cognitive Services. I worked at Microsoft back then. I was asked to author a module for a course that included the ability to make a conversation bot and have it perform some unique AI functionality. I chose to write about using a chat bot where a politician or a product manager at a company, could ask the bot how the world of Twitter perceived them or their product. It let them enter terms, then searched Twitter for related hash tags, returned the tweets from the platform,, and finally used sentiment analysis to display a neat little table showing the sentiment that people felt. This was the start of some truly interesting things with AI.

As I began teaching generative AI, which is the most common usage today among the general public, I found myself having to spend time helping the students understand the concepts and limitations of generative AI. The feedback you got, is a prime example of where AI still needs work.

We must remember that whatever LLM or SLM that the AI is using, is limited by the data it was trained on. The critical piece to understand is that the AI model is only able to generate a response based on the data it was trained on. This data could be old, it might not match your specific topic domain, and it can hallucinate.

I give students an example. I open Microsoft Word and use Copilot. This is the first prompt I give it.

"Please draft a cover letter for me. I am applying to Boeing for a job posting for an aerospace engineer. Use my 10 year's of experience at Bombardier as an aerospace engineer."

That is all I give it.

What is returned, starts out ok. Basically stating simple things like the role I am applying for and that I believe my tenure at Bombardier positions me well for this role.

Then, it goes off the rails. It begins to state things like:

"In my tenure at Bombardier, I gained valuable experience in composite wing design.......

WTH? Where did that come from?

It came from a mathematical algorithm that is designed to find relationships between words. It found, in its training data, references of what an aerospace engineer might do. Sure, some design wings, most, likely do not.

It's almost like giving a toddler three pictures of a bicycle and expecting them to be able to pick out bicycles from any other picture, or differentiate bicycles from tricycles and motorcycles.

My students then ask me. "Ok, so what do you use generative AI for?"

I simply use it as a thought generator. If I am stuck on coming up with an idea, I ask it to give me suggestions. It can spark my creativity.

But more importantly, if I need it for serious stuff, like work related activities, I use the concept of grounding. I provide it with relevant information that has factual accuracies related to the topic at hand. In my cover letter example, I use an actual resume for someone who was an aerospace engineer. I give the AI access to the document and tell it to use that as a reference for my experience. The output is considerably better.

What users fail to understand, when it comes to using generative AI, or AI in general, is a simple concept. Trust, but verify. I think that "consulting company" just passed along some output without any real scrutiny behind it.

And there I go again, writing a novel. Sorry.......

Gregory Brown - PM's avatar

In my 3 years of Active Guard Reserve Duty at 98th Division Training HQ in Rochester NY, I was asked to write "White papers" on policy items, that 1st Army could use (after revision). These were to be one page about "Strength Management", at 8th grade reading level.

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