There is a curious thing that happens when you start using artificial intelligence for engineering jobs. You begin, quite innocently, by asking it a question about a GT6, a Ford Galaxy, a ride-on mower, or one of the boys’ motorcycles, and before long you realise you have not summoned the Oracle of Delphi.
You have summoned Dave.
Or, as Hayley has now christened it, Chatty Petey, which is perhaps even worse, because it sounds like a bloke in a fleece who has opinions about fuel pressure, has once owned a soldering iron, and is absolutely certain your problem is an earth fault.
Not useless Dave. Not pub bore Dave. More like helpful Dave from down the road, who has once changed a clutch cable, owns a multimeter, and says things like, “Have you checked the earth?” with the calm authority of a man who has absolutely not checked the earth.
And, to be fair, ChatGPT is often extremely useful. It can explain the principle, suggest a logical sequence, remind you not to set fire to yourself, and point out that perhaps before stripping half the front end off a mower you might first check whether there is a circlip under several decades of congealed grease.
This is good advice. This is the sort of advice that prevents a man in late middle age from lying on the gravel muttering darkly at a machine designed by someone who clearly hated both gardeners and access panels.
But ChatGPT is not always right.
Sometimes it is confidently wrong, which is worse than being uncertain. Uncertain is at least honest. Confidently wrong is the chap who says, “That’ll just pull off,” three seconds before you discover that the thing in question is held on by a hidden grub screw, a tapered spline, two spring clips, and the accumulated spite of a previous owner.
This is where Bard comes in. Or Gemini, or whatever Google is calling it this week, though it remains Bard on my browser tab because I annotated it that way and I refuse to be bullied by a rebrand.
Bard is, in my experience, slightly better at diagnosing mechanical problems. Not always. Let’s not get carried away. It is not Fred Dibnah in a server farm. But it often has a slightly different instinct. It will say, “That sounds more like fuel starvation than ignition,” or “Before replacing the regulator, test voltage at the battery and at the rectifier output,” and suddenly one begins to feel less like a man randomly buying parts and more like a proper troubleshooter.
Unfortunately, if you ask Bard for a diagram, you may as well ask the dog.
ChatGPT, by contrast, will have a decent stab at describing one. Sometimes it will even organise the parts in a way that makes sense, which is helpful when you are trying to understand why a 1990s Mercedes fuel system has apparently been designed as a joint venture between Stuttgart engineering and a medieval puzzle box.
So the trick, I have discovered, is not to treat either of them as an expert. The trick is to treat them as two useful mates standing in the garage.
One is leaning over the wing, saying, “I reckon it’s the return feed.”
The other is sitting on an upturned bucket, saying, “No, no, look at the symptoms. It’s more likely a blocked breather or a collapsing hose.”
And I am in the middle, holding a spanner, slightly oily, quietly wondering whether either of them has noticed the small pipe hanging loose behind the carb.
That is the useful bit. Not the answer itself, but the argument. ChatGPT says one thing, Bard says another, and I feed each answer into the other like a small domestic version of the Chilcot Inquiry, only with more jubilee clips. One spots a weakness. The other revises the theory. I ask a sharper question. One of them remembers a common fault. The other points out an assumption. Gradually, through a process of digital bickering, something approaching a sensible diagnosis emerges.
Occasionally I take the output from one, feed it straight into the other, and ask for an assessment. Then I take that assessment and feed it back again. It becomes a little feedback loop, which is something I used to do in my programming days, when the computer would either do exactly what I had told it to do rather than what I meant, or sit there producing error messages with the emotional warmth of a parking ticket.
There is something pleasingly old-fashioned about it. Not the technology, obviously. The method. Thesis, criticism, revision, further criticism, slightly better thesis. It is basically a garage argument, but without anyone saying, “My brother-in-law had one of those.”
This is not artificial intelligence replacing human judgement. This is artificial intelligence requiring it.
AI does not remove the need to think. It increases the number of thoughts available, some of which are useful, some of which are twaddle, and some of which sound useful until you look at the actual machine and realise the component it is describing is not there, was never there, and would only be there if the mower had been designed by NASA.
The advantage, of course, is that these two mates are available at any hour and do not require tea. They do not suck air through their teeth and say, “That’s going to cost you.” They do not wander off halfway through the job because their wife has texted. They do not stand there telling you about the time they had a Capri with exactly the same problem, which turns out not to be the same problem, a Capri, or relevant.
But they do share one vital quality with human garage advisers. They need managing.
You have to know when to listen, when to question, and when to say, “Hang on, that makes no sense.” You have to spot when a theory explains one symptom but ignores three others. You have to ask whether the proposed fix matches the physical layout in front of you. You have to remember that a wiring diagram is not the same as the wiring on a 20-year-old motorcycle that has been previously visited by someone with insulation tape and spiritual confidence.
In other words, you still have to be the grown-up in the room.
That is fine by me. I rather enjoy it. There is something oddly satisfying about playing one machine off against another, like a tiny workshop version of the House of Lords. ChatGPT proposes. Bard objects. ChatGPT amends. Bard concedes a point but raises a further issue. I sit there with dirty hands and the faint air of a man chairing a select committee on why the bloody thing still will not start.
And now, of course, I want No.1 Son to make it worse.
He is a programmer, and understands AI properly, which is dangerous because it means he can probably build what I am now imagining. What I want is a little system that automates this whole process. ChatGPT says something. Bard assesses it. ChatGPT assesses Bard’s assessment. Bard questions the revised answer. Round and round they go, without me having to copy and paste things like a retired man operating a very small intelligence agency from the kitchen table.
In theory, this would be marvellous. A self-improving diagnostic loop. A pair of digital mechanics arguing endlessly until they converge on a well-reasoned answer. In practice, I suspect it would either produce something extremely good mechanically, or design a GT6 that does 300 mph and needs three software updates before you can open the bonnet.
Still, that is progress, apparently.
And often, between them, they get me there. Not because either one is infallible. They are not. But because two fallible perspectives, properly interrogated, can be more useful than one confident answer. Especially when the third participant is the idiot actually looking at the machine.
Which is me, obviously.
And that, I think, is the real lesson. AI is not a magic expert. It is not a replacement for experience, judgement, or noticing that the tyre bead is still stuck on the wrong side of the rim. It is a pair of clever, flawed, tireless, slightly overconfident mates in the garage.
Very useful. Occasionally brilliant. Sometimes wrong. Best kept under supervision.
And still no help at all when the 10mm socket has vanished.