Firstly, if the automation performs flawlessly, the overseers will become complacent, blindly trusting the instruments and failing to perform basic sanity checks. They will have far less procedural understanding of what’s actually going on, since they have no opportunity to exercise their knowledge.
There’s a related problem in manufacturing whose name I’ve forgotten, but basically, the less frequent defective parts are, the less likely it is human quality control people will notice defective parts, because their job is more boring and so they’re less likely to be paying attention when a defective part does happen. (Conditioned on the part being defective, of course.)
Right, one of the original solutions, though rarely implemented, is to add a steady stream of defective parts to guarantee optimal human attention. These artificially defective parts are marked in a way that lets them to be automatically separated and recycled later, should any slip by the human QA.
Surely they already do that. The trick is not knowing whether an abnormal input is a drill or not, or at least not knowing when a drill might happen. All these issues have been solved in the military a long time ago.
Knowing when a drill might happen improves alertness during the drill period only. Drills do develop and maintain the skills required to respond to a non-standard situation.
I’ve heard that when you play mouse-chasing-themed games with your cat, the maximal cat fun is achieved when there are between 1 and 2 successes for every 6 pounces.
Optimal performance may be maximized, but the output isn’t.
I would be surprised if there were less overall errors in the final product if it started at 2 per page, rather than say 1⁄4 per page.
This is also valid against the suggestion in the OP. Although humans will catch more errors if there are more to begin with, that doesn’t mean there will be less failures overall.
As I mentioned in my other comment, if some of the errors are injected to keep the attention at the optimal level, and then removed post-QA, the other errors are removed with better efficiency. As an added benefit, you get an automated and reliable metric of how attentive the proof-reader is.
There’s a related problem in manufacturing whose name I’ve forgotten, but basically, the less frequent defective parts are, the less likely it is human quality control people will notice defective parts, because their job is more boring and so they’re less likely to be paying attention when a defective part does happen. (Conditioned on the part being defective, of course.)
Right, one of the original solutions, though rarely implemented, is to add a steady stream of defective parts to guarantee optimal human attention. These artificially defective parts are marked in a way that lets them to be automatically separated and recycled later, should any slip by the human QA.
Wow. That’s an really cool example of careful design, taking humans into account as well as technical issues.
Yeah, I was equally impressed when one of my instructors at the uni explained the concept, some decades ago, as an aside while teaching CPU design.
They apparently do this in airport x-rays—inject an image of a bag with a gun, to see if the observer reacts.
But apparently not for keeping pilots alert in flight… A “Fuel pressure drop in engine 3!” drill exercise would probably not, umm, fly.
There might be other ways—you could at least do it on simulators, or even on training flights (with no passengers).
Surely they already do that. The trick is not knowing whether an abnormal input is a drill or not, or at least not knowing when a drill might happen. All these issues have been solved in the military a long time ago.
Knowing when a drill might happen improves alertness during the drill period only. Drills do develop and maintain the skills required to respond to a non-standard situation.
I’ve heard that in proof-reading, optimal performance is achieved when there are about 2 errors per page.
I’ve heard that when you play mouse-chasing-themed games with your cat, the maximal cat fun is achieved when there are between 1 and 2 successes for every 6 pounces.
Optimal performance may be maximized, but the output isn’t.
I would be surprised if there were less overall errors in the final product if it started at 2 per page, rather than say 1⁄4 per page.
This is also valid against the suggestion in the OP. Although humans will catch more errors if there are more to begin with, that doesn’t mean there will be less failures overall.
As I mentioned in my other comment, if some of the errors are injected to keep the attention at the optimal level, and then removed post-QA, the other errors are removed with better efficiency. As an added benefit, you get an automated and reliable metric of how attentive the proof-reader is.