BOTH screwed up. The system shouldn't have made the match and the human should have done a better job seeing that the match was wrong. I'll go one larger and say the people who created the procedures screwed up because they didn't make allowances for the possibility of the first two screw-ups.

Even on a phone, if you're playing an album, you're playing an album. You search for it once, not over and over. A 15% increase in fatalities, if this isn't just noise that will regress to the mean after more data comes in, would point to people being distracted for an extended period of time... you know... by actually listening to the music and paying attention to that instead of to their driving.

You're right, they'll run the numbers and take whichever path maximizes their net profit -- but shuttering (or even heavily modifying) a facility that they've just invested $$$$ into is unlikely to be found to be their most profitable option. More likely they'll try to sell memory chips at a profit of +$.25 per chip in large volumes, because when you've got is a giant hammer, hammering lots of nails is what you can do best.

I wonder if anyone will start selling home systems capable of using cast-off data center RAM? It might be worthwhile if there's lots of that sort of RAM floating around for cheap.

Faces are way less unique than fingerprints unless you are using a camera with such high resolution that you can see the individual hairs, pimples, birthmarks, moles, freckles, and other tiny details, and even then, only if you are analyzing it at that level of detail after using fixed points to unwrap the image into a flat UV map for comparison.

Statistically, no two people have the same fingerprint, so it's just a matter of comparing enough points to achieve the desired confidence level. At a shape/structural level, lots of pairs of unrelated people have faces that are too much alike to reliably detect the difference, likely because there's not as much genetic diversity as one might assume.

Compounding this is the fact that a fingerprint is detected by being pressed flat against something, whereas face shape has to be recognized from arbitrary angles.

Any approach that does not stitch together multiple camera angles to get a complete image of the entire face and then unwrap it into a high-res UV map and then use the result as a secondary filter pass after structural comparison is doomed to fail frequently when presented with an adequately large number of people. There are simply too many people that look far too much alike even within a fairly small geographical area like a state or small country, much less the entire world.

Accuracy is the wrong number to give. Accuracy is right answers over wrong answers, without any info about whether they were false positives or false negatives. What you really want is a relationship between the number of false positives and by total positives, or perhaps the relationship between false positives and total negatives. The latter is called specificity (true_negatives/ (true_negatives + false_positives)), and gives you an indication of how likely people are to be falsely accused. This needs to be incredibly low.

But the better number would be false_positives / (false_positives + true_positives), because that would tell you how likely it is that someone flagged is really the person in question.

Either way, for this purpose, the only rational way to use the tech is to watch flagged people more carefully. Trying to escort them out of the store is going to be a disaster of false positives, for all the reasons previously mentioned (look-alikes, limitations caused by camera perspective, etc.).

The problem is, people have been over-trusting technology since technology was invented. Consider the '70s when corporate representatives were so fond on the phrase "But the computer says...". Yes, you could hear the bold italics in their voice, as if it was the infallible final word on everything.

If THE COMPUTER says you shoplifted, rest assured, some dolt in a suit will treat that like God's own word booming from the clouds.

But every person who sets foot in that store probably "kinda" looks like someone who has shoplifted. And since shoplifters look like everybody else, everyone COULD be a shoplifter.

For me the visualization of direct collapse black hole formation is that there's still a huge mass of gas falling in, at the boundary of the new black hole nearly dense enough to direct collapse itself. The blowback would compress the inflow over the density edge and you get a whole cloud of black holes.

Many have voted with hairspray and a sawzall.

It's worse, they don't have to go sentient at all. The black death wasn't sentient but it wiped out whole towns anyway.

Rogue agents with no awareness have already demonstrated that they will act against any entity with a conflicting goal, including humans.

IIRC, more than one lawyer has gotten in to hot water because of AI hallucinations in legal briefs. They sign their name to those, they are responsible.

The legal process is adversarial but it is not anything goes. Fabricating evidence and perjury are out of bounds for example.

I think this falls into that category.

OTOH, if the court DID use AI to make decisions, the whole court would invalidate itself, so there is some ethical wiggle room.

AI should have no agency at all. It should only advise the human in the loop who is actually responsible for what happens.

It's pretty cool that they're seeing where the supermassive black holes come from. The models of what's happening in there must be amazing.

Sure, a company could use an increase in productivity to allow their workers to work fewer hours while getting the same amount accomplished... but capitalism doesn't work that way. Instead, the company will use the increase in productivity to get more work done in the same amount of hours as before... or if they don't, their competitor will, and thereby obtain a competitive advantage over them.

This is especially true for salaried employees, where the cost of the employee to the company is the same regardless of how many hours the employee works, and it is therefore in the company's financial interest to maximize the return on its salary "investment" by getting as much output from the employee as possible in any given pay period.