It's called Forbes 30 under 30

this is from a couple years ago. everyone is here thinking this is like minority report but it's not about individual behavior, this is just about using predictive models to self-justify racist policing patterns:

Fears of “The Thought Police” are probably running through your head right now, but Chattopadhyay is keen to stress that the focus isn’t on individuals, “We do not focus on predicting individual behavior, and do not suggest that anyone be charged with a crime that they didn’t commit, or be incarcerated for that. Our model learns from, and then predicts, event patterns in the urban space, for example, predicting that within a two block radius around the intersection of 67th Street and SW Avenue, there is a high risk of a homicide a week from now. It does not indicate who is going to be the victim or the perpetrator,” she says.

https://archive.ph/zgUjs

Which of course has a certain degree of success baked in, because if you focus policing in a particular place you will find crimes there because a) crimes happen everywhere and b) cops can just juke the stats / make shit up / make arrests without cause.
- exactly. it's amazing to me that these nerds can talk themselves into creating an ouroboros like this because they don't actually bother to understand how any of this shit works, but i guess whatever justifies their salary...
"using advanced AI, we have determined there will be more crime in the high crime area"
- it's even worse than that! they're treating crimes like they're forces of nature or fucking dice rolls to begin with and completely ignores the role police play in defining and creating crime and the construction of criminality!

With 90% accuracy it will successfully identify 90 out of 100 criminals and falsely accuse 90 out of 1000 innocent people.

It's better for ten innocent people be jailed than for one full time wage to be paid
- 10 innocent people may be jailed, but it’s a risk I’m willing to take
I see anywhere where prisons are a private thing being massively in favour of this.

Wow how innovative

The Torment Nexus is only when you do 1984, not Minority Report.

U Chicago continuing its proud reactionary legacy https://en.wikipedia.org/wiki/Chicago_Boys

 rust

    
pub fn predict_crime(suspect: Person) -> bool {
   if suspect.race() == Race::Black {
       return true;
   } else {
       return false;
   }
}

ew...

pub fn predict_crime(suspect: Person) -> bool { return suspect.race() == Race::Black }
- Good change but also why is race a getter method while Race::Black is a constant enum? Is race an impure function dependent on global state? Is it derived from some other internal immutable state?
- you dont need the return statement either
Nerds with a rudimentary understanding of undergrad stats do this all the time with extra steps by just building a simplistic model based on (racist) "crime data". Sometimes literally just a basic Bayesian model.
And they get hired by Palantir to do versions of that for $300k/year.

Predicts police behaviour not crime. And who can't do that.

Insider trading is probably very predictable, with enough data.

Can’t wait until in “freedomland” I get arrested not because I commit any crimes, but because I look like someone who might.

“Red always sus” but in real life.

That's been happening for a really really long time already. It's called racism, now they're teaching it to computers.
- Didn’t it come out early on that AI was racist?

Does it poop out cute little billard balls too?

We do not focus on predicting individual behavior, and do not suggest that anyone be charged with a crime that they didn’t commit, or be incarcerated for that. Our model learns from, and then predicts, event patterns in the urban space, for example, predicting that within a two block radius around the intersection of 67th Street and SW Avenue, there is a high risk of a homicide a week from now. It does not indicate who is going to be the victim or the perpetrator.
…
We found that when stressed, the law enforcement response is seemingly different in high socio-economic-status (SES) areas compared to their more disadvantaged neighboring communities. It is suggested in the paper, that when crime rates spike, the higher SES neighborhoods tend to get more attention at the cost of resources drawn away from poorer neighborhoods.

link

We found that when stressed, the law enforcement response is seemingly different in high socio-economic-status (SES) areas compared to their more disadvantaged neighboring communities.