Software engineer and small time DS/ML practitioner.
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If the answer is yes to all of the above
Point 2 needs rephrasing.
"Does it sound exciting or boring?" "Yes"
Most Importantly Missing
Where's my "Babylon 5"? Honestly, risking to get the anger of trekkies here, but it's "DS9 but better"
Does the Nobel Prize sabotage future work?
My first thought was "regression to the mean" and judging from a lot of comments in the original post I'm not the only one. If you're on the top of the world, the only way to go is down.
Except there should also be an understanding what constitutes a constructive "questioning the science". There can be no debate between quantum physicists and cobbler about quantum physics. Questioning the science isn't "I decided I know better" and isn't "I don't want to beleive in your results" (by itself). You question the science by checking, double-checking, finding weaknesses in the previous science. And by making new, better, more rigorous science.
People tend to forget this part even more often than the part about questioning being the integral part of science.
Compared to how much carbon a human coder would have used? Huge improvement.
JSON formatting? That's literally millisecond in dedicated tool. And contrary to LLM will not make mistakes you need to control for. Someone using LLM for this is just someone too lazy to turn on the brain.
That said, it's not like people not using their brain isn't frequent occurence, but still... not something to praise.
I'm not implying, I'm saying it outright. Depending on the way you measure and the source for the data police only solves between 5% and 50% of the crime. And that only takes into account reported crime, so actual fraction, even measured in the most police-friendly way, is lower. At the very least the same amount of criminals are walking free as being caught.
Criminals are found in places police check for criminals. And those become stats, sociological profiles and training data for AI to pick up patterns from.
On the topic of "why?" reaction - that is just how supervised machine learning works. Model learns the patterns in the training data (and interpolate between data points with the found patterns). And the training data only contains the information about prosecutions, not actual crime. If (purely theoretical) people called Adam were found in the training data guilty 100% of the time - this pattern will be noticed. Even though the name has nothing to do with the crime.
It's really difficult to get truly unbiased training data. There are bias mitigation algorithms that can be applied after the fact on the model trained on biased data but they have their own problems. First of all their efficiency in bias mitigation itself usually varies from "bad" to "meh" at best. And more importantly most of them work by introducing counter-bias that can infuriate people that one will be biased against now and that counter-bias will have its own detrimental secondary effects. And this correction usually makes the model in general less accurate.
Giving physical analogy to attempts to fix the model "after the fact"... If one of the blades of the helicopter get chipped and become 10cm shorter - you don't want to fly on this unbalanced heavy rotating murder shuriken now. You can "balance" it by chipping the opposite blade the same way or all the blades the same way, but while solving the balance now you have less thrust and smaller weight of the component and you need to update everything else in the helicopter to accommodate etc etc. So in reality you just throw away chipped blade and get a new one.
Unfortunately sometimes you can't get unbiased data because it doesn't exist.
virtually all the violent crime in the city was caused by a few hundred people
virtually all the violent crime prosecutions was caused by a few hundred people. Which is very much not the same. That's the real reason why EU "pretend that we do not know such things". If the goal is to continue prosecute who we always prosecuted - we can use AI all the way. If we want to do better... we can't.
1The situation is that there is a new drug that is helping people without hurting anyone, so they write an article about how it is increasing ‘health disparities.’
Isn't "solving for the equilibrium" a big thing in this community? That's what articles like this do - count not only first order effects, but also what those lead to.
Specifically - people with money and resources gobbling up all the available "miracle" drug, making people with less resources unable to get one even for the established medical use. So yeah, I really don't see a problem with the article title (specifically title, hadn't read the content!), it's stating the facts. Finding new usage for limited resource makes poor people access to it even worse than before.
Of course, "let's make less miracle drugs" isn't a solution, solution is to make more of them, so that everyone who need one can get one. Finding new cures isn't the problem, terrible distribution pipelines is.
Honestly, at this point one with some self-awareness would start to suspect that the problem may not be on the cities side. Nothing wrong with the search for the better place for themself, everyone is entitled to it, but when literally nothing fits...