this post was submitted on 18 May 2026
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Same can be said for the output of most interns, and even more senior employees. This is why we have "Quality Systems" safety audits, design controls, and the rest of the regulations which basically set us all up checking each others' work all day long. No AI required, these systems were shown to improve both safety AND efficiency of industry back in the 1980s, which is why they were rolled out as law for industries like aviation, medical, automotive and finance in the 1990s long before anyone would have claimed that AI of the day was doing anything.
The reason studies say those "measure twice cut once" practices increase efficiency is because mistakes are expensive, extremely expensive when you get to problems like Boeing has, it's not just the lives lost or cost of crash damage/loss, it's the reputational impact to the company, public perception diminishing the real value of their products.
ALL those same quality practices apply to AI. People are complaining because AI output is so much faster than people output, leaving people holding the review bag, but... newsflash: AI does quality review too. Imperfectly, incompletely, just like people, except AI does the quality reviews much faster than people. Will AI as author, editor, publisher and critic work? Maybe not as a complete closed loop system today, but the individual functions of AI acting within those systems have all improved dramatically in the past 12 months.
What hasn't changed? The broad public's perceptions and growing anxiety. Justifiable concerns about how the powerful owners/directors of AI companies will abuse their influence.
I suppose that depends on how we define improvement, because from where I'm sitting, it's reasonable to be apprehensive about LLM's and their output when we see spectacular failure after spectacular failure.
Whether it's bombing a school in Iran because Claude fucked up the targeting, or an AI agent deleting your email inbox or your production database, or creating a court case out of thin air, or stats in a SCOTUS ruling that are fictitious, over and over and over again the extravagant promises they keep telling us are just around the corner appear to be decidedly half-baked.
And if you use Teams or Windows and pieces of functionality that worked for two decades are no longer working as designed in a dependable way, I guess I just don't know what to tell you.
It makes perfect sense not to trust this technology, and the speed it promises is often mitigated by the fact that you can't and shouldn't trust its output, because if you're the unlucky SOB that doesn't check a reference, you can literally become national news.
Further, being that it's already been trained on the entirety of recorded human knowledge, I'm not sure how it gets better either. You can make it faster, but it's just going to spit out slop at a faster rate.
I'm going to call user error on that, and I don't think it matters what system they were using - they were going to make mistakes.
The real error there? Conducting risky operations without backups.
That's just big silicon-brass balls. Interns do it too, but you don't hear about them. On the other hand, trusting the AI or the intern, that's disbarment levels of reckless.
Or any technology, until we have figured out what it is, and isn't, capable of doing reliably.
But, plenty of people still play Russian Roulette, for one reason or another. Is that the revolver manufacturer's fault?
Better editing.
Yes, you can mitigate any risk you can think of with the right planning, but these are new risks of arbitrary severity, from trivial to devastating, that did not exist at all before. Previous systems had risks, but they were different, more limited in scope, and accounted for.
It may be true that some of these systems are worth those new risks and the planning necessary to find and mitigate them all, but we have to do that hard work and be real with ourselves, rather than hand-wave them away because of the potentially thrilling prospects.