AI Got You Spooked? Here’s How My Old F150 Helped Me

I drive a 12-year-old Ford, F150 pick up. It’s a great truck. I have about 250,000 km (150,000 miles) on it now, and it rides as good as it ever did. It’s a nice “in-between” truck – it’s not so modern that I can’t do repairs on it myself, but it’s new enough that it has many of the new features and bells and whistles I want.

Recently, an interior light would come on and stay on, and a dashboard indicator informed me that the rear passenger door was open. But it wasn’t. The door was closed, but the dashboard indicator wouldn’t extinguish and the interior light stayed on.

So, I googled it, and without me asking specifically for AI help, AI jumped into the fray and offered me its diagnosis. It identified several easy suggestions (low battery) but in its summation, it suggested the most probable cause was likely a broken wire where a harness bundle exits the frame and enters the door.

I had to start somewhere, so I figured that was as good a place as any to start. It was easy to peel back the accordion style cover to expose the factory wrapped bundle. I paused for a moment (second thoughts) before cutting a six-inch slit into the harness wrap with an Exacto knife, cutting parallel to the wires, so I could tug on each wire individually. I’d give each wire a gentle pull in one direction, and then the other.

The fourth wire I pulled on was only connected on one end; the other end (coming from the door post) came free. I carefully pulled back the bottom of the cover on that door post to find the other end of that wire following the same process, and then with proper soldering and double heat shrink tubing, I spliced in a 3-inch piece that reconnected the circuit.

It was a satisfying moment as all my old electronic technician skills were back in play! But I had to also give credit to where it was due; it was Google’s AI that directed me to the most likely problem and exact location the break was likely to be, and it gave sufficient supporting data to give me the confidence to undertake the operation.

So, I took on a few other automotive challenges. My wife’s car has some issues with the back up camera, the touch screen on the dashboard, and the parking brake light. My granddaughter’s car had issues with the ABS and traction control. AI would list out all the possible causes, the most probable, and the easiest things to check first. Yes, I know that advanced diagnostics are built into most cars these days and that the dealers have great software tools that leverage them, but what AI has done is make it accessible to me, “the average guy”.  

I work with manufacturing companies all over North America and help them identify and adopt new technologies effectively in their plants. I start by asking what problems they want to solve. If they give me general answers like “we want to adopt Industry 4.0”, or “we want to use AI”, the chance of a achieving a satisfying result is very small. However, if they have a specific problem (or set of problems) they want to resolve, AI can become an extremely useful tool.

In my F150 example, I wasn’t using AI to design a better F150 for me (although it probably could), I identified a very specific issue that I needed to address, and it delivered a very high value, low-cost result, quickly. With that experience (and confidence) under my belt, I took on the next one, and the next one, and then the next one after that. It wasn’t 100% on all the problems, and it didn’t do all the work for me, but I can say it made me – the person doing the work – 2 times, 3 times, or even 10 times better.

It’s the same with applying AI technology in the plant. What’s the problem you want to address? Too much scrap? Not enough production flow? Too many interruptions due to equipment issues? Too much work-in-process? No product traceability? Too much paperwork?

Speaking from my own experience, the effective application of AI in the plant correlates directly with the clear identification of problems that need to be solved.

There are many moral and social questions still to be answered about AI. Where is it going, what will be its intended purpose, (and what might be its unintended consequence), and how will it be used? Those are all things to keep a watchful (weary?) eye on, but when technology is intended to make us better at we ourselves do for a living, I view it more pragmatically. Does it make you better at what you do? Does it make your team better? Does it make your plant better?

If AI has you spooked, or intrigued, or you’re not sure how to start, send me a note to paul@tpi-3.ca and I’d be happy to have a real, person-to-person conversation. With technology, it’s all about use and application, and ultimately, it still has to be about people.