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.

The 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.

only to find out it is censored enough I could have used DALL-E and MidJourney.

Last "censoring" of Stable Diffusion was done via the code and could've been turned off via 2 lines of code change. Was it done other way this time? 

Probably some people would have, if asked in advance, claimed that it was impossible for arbitrarily advanced superintelligences to decently compress real images into 320 bits

And it still is. 

This is really pushing the definition of what can be considered "image compression". Look, I can write a sentence "black cat on the chessboard" and most of you (except the people with aphantasia) will see an image in their mind eye. And that phrase is just 27 bytes! I have a better "image compression" than in the whitepaper! Of course everyone see different image, but that's just "high frequency details", not the core meaning.

First it was hands. Then it was text, and multi-element composition. What can we still not do with image generation?

Text generation is considerably better, but still limited to few words, maybe few sentences. Ask it to generate you a monitor with Python code on it and you'll see current limitations of this. It is an improvement for sure but in no way "solved" task.

Europeans... vastly less rich than they could be.

POSIWID. Metric being optimized is not "having the most money". It is debatable if it should be, as one of the "poor Europeans" my personal opinion is that we're doing just fine.

There are 2 topics mixed here.

1. Existence of the contrarians.
2. Side effects of their existence.

My own opinion on 1 is that they are necessary in moderation. They are doing the "exploration" part in the "exploration-exploitation dilemma". By the very fact of their existence they allow the society in general to check alternatives and find more optimal solutions to the problems comparing to already known "best practices". It's important to remember that almost everything that we know now started from some contrarian - once it was a well established truth that Monarchy is the best way to rule the people and democrats were dangerous radicals.

On the 2 - it is indeed a problem that contrarian opinions are more interesting on average, but the solution lies not in somehow making them less attractive - but by making more interesting and attractive conformist materials. That's why it is paramount to have highly professional science educators and communicators, not just academics. My own favorites are vlogbrothers (John and Hank Green) in particular and their team in Complexly in general.

Penicillin. Gemini tells me that the antibiotic effects of mold had been noted 30 years earlier, but nobody investigated it as a medicine in all that time.

Gemini is telling you a popular urban legend-level understanding of what happened. The creation of Penicillin as a random event, "by mistake", has at most tangential touch with reality. But it is a great story, so it spread like wildfire. 

In most cases when we read "nobody investigated" it actually means "nobody succeeded yet, so they weren't in a hurry to make it known", which isn't very informative point of data. No one ever succeeds, until they do. And in this case it's not even that - antibiotic properties of some molds were known and applied for centuries before that (well, obviously, before the theory of germs they weren't known as "antibiotic", just that they helped...), the great work of Fleming and later scientists was about finding the particularly effective type of mold and extracting the exact effective chemical as well as finding a way to produce that at scale.