
Swiss police automated crime predictions but has little to show for it - jusbraun
https://algorithmwatch.org/en/story/swiss-predictive-policing/
======
raxxorrax
A case where Germany has sold crapware to the Swiss. I mean geographic
analysis of crime can certainly be helpful, but I doubt it can be more
accurate than your average fortune teller if the rate of crime is as low as it
is.

The the software is named precobs in reference to minority reports precogs
let's me believe their marketing team is hired from people selling penis
enlargement on the internet. Perhaps they are just smarter because they know
how often people are inclined to buy bullshit.

~~~
elchin
This. We need to keep in mind crimes rates in Switzerland are extremely low.

~~~
BurningFrog
Which maybe means the Swiss cops know what they're doing, and we shouldn't be
quick to mock this scheme.

~~~
Thlom
Crime rate have very little to do with how society is policed. If you want to
find explanations look at wealth distribution, poverty rates, the school
system, job market and so on.

~~~
BurningFrog
Bad/non existent policing definitely skyrockets the crime rate.

But once you have decent policing, I can believe other factors dominate.

~~~
nix23
No, that count maybe for cities but not for villages.

------
lordnacho
This is an education failure on the part of the purchasers. They should know
what you can and cannot do with data. Think about the dataset you'd need to
make the burglary prediction. Cops would have some priors about where/when it
might happen, but is the data actually collected?

You'd need to know a lot of things about a large number of homes in order to
see how the characteristics are distributed. Has the house been left empty for
a while? Has someone posted about their holiday on FB? Is there something of
value in the house? What security measures are there? Are known house-burglary
gangs in action in the area?

Those are the kind of things you'd think cops might have priors on. I'm sure
one can chime in on this. But they're also the kinds of things that you might
have problems collecting data for. And even if you had it, your false positive
rate needs to be pushed pretty low for it to be useful. Plus your false
negative (place is burgled but system didn't say) needs to be really low, in a
country where there isn't that much crime to begin with.

For the second system, as the article says, you can just say everyone is a
risk. It's like saying everyone has Covid, you'll correctly find all the
carriers. This is an obvious issue with ML systems that a purchaser needs to
understand.

The last system, with the recidivism, is maybe the most concerning. It seems
to suggest that people's paroles are decided based on this system? Then you'd
better have good evidence that the system works, in the
sensitivity/specificity sense.

[https://en.wikipedia.org/wiki/Sensitivity_and_specificity](https://en.wikipedia.org/wiki/Sensitivity_and_specificity)

~~~
0xdeadbeefbabe
What about the seller?

~~~
lordnacho
You mean is it a bit naughty to sell something as if it's more than it really
is?

I think you could make that case.

~~~
nix23
Don't try to destroy the Finance Industry please ;)

------
Spooky23
This is the same as any other (ab)use of statistics. Forecasting is a valid
and useful practice for managing your people and process. Maybe you redeploy
resources to improve response time or schedule shifts to match forecasted
incidents, etc. Data collection is pretty awful with this type of data, so
good luck doing much more.

But the problem is that the public hears something different when they hear
"automated crime prediction". People hear something novel that could prevent
crime. After all, if rain is predicted, you grab an umbrella.

The reality is that cops on the street already know where crimes are likely to
happen. You'll get some tools to reduce workload on police sergeants doing
scheduling and things like data presentation are probably the primary benefit.
Not as sexy as minority report.

~~~
clairity
you could simply write a geographic correlation function on income/wealth and
race/ethnicity and do just as well at this kind of forecasting, since police
find crime where they look, and they tend to look in poorer and non-white
areas.

further, we need to disabuse ourselves of the idea that we can predict crimes
to any degree beyond random (vs. aggregate stats, like crime rates), because
it's tantalizing ideas like that which leads to the slide into surveillance
and totalitarianism without any real, positive return to society as a whole.

~~~
valvar
I don't believe anyone on HN is so naïve that they think that the main reason
crime rates vary between areas is that police presence varies. Your post makes
it sound like you are, but I assume that you only think varying presence skews
the numbers rather than generates them?

~~~
clairity
i would hope no adult is naïve enough to believe police magically appear only
where crime is and only addresses clear and existing crime, rather than being
embedded in a complicated sociopolitical system overwhelmed by legal pitfalls.
those are stories we tell children to comfort them for sleep.

~~~
JoeSmithson
The vast majority of frontline policing is in response to an emergency call,
so they have no control over where it is.

HN seems to think police spend their shift waiting for crimes to happen in
front of them.

~~~
clairity
that's a misdirection. most crimes are not emergencies, and policing
encompasses much more than emergency response.

if policing were just, we'd see many more white-collar crimes like corruption,
bribery, embezzlement, fraud, extortion, etc. being busted, because those
crimes have much larger impact and wider fallout on communities and wider
societies.

~~~
Nasrudith
White collar crime isn't a task for police any more than tax evasion is -
those just plain aren't tasks they are meant for as opposed to public safety
tasks. Which also explains why they are less funded, even without any
conflicts of interest they aren't "sexy" crimes that grab attention, they all
also lack urgency and thus are easily "procrastinated". Digging through
records can uncover many of them and there are a lot of them.

The police in their current role only show up at the behest of warrants in
those situations to search or arrest.

------
nitwit005
> It tries to predicts burglaries from past data, based on the assumption that
> burglars often operate in small areas. If a cluster of burglaries is
> detected in a neighborhood, the police should patrol that neighborhood more
> often to put an end to it, the theory goes.

Heaven forbid they just put pins in a map.

------
jusbraun
A review of 3 automated systems in use by the Swiss police and judiciary
reveals serious issues. Real-world effects are impossible to assess due to a
lack of transparency.

------
duxup
I guess it depends on what we would want from crime predictions.

Do we want a Minority Report type system where someone shows up right before
the crime and prevents it?

They mention burglary. I'm guessing most buglers aren't seasoned professional
buglers and rather it is a crime of opportunity. So if a cop is on the street
they won't do it ... but maybe they'll do it the next street over, 20 minutes
later?

Even if somehow there was better prediction, there really aren't enough police
to patrol the target street, and the next one over, and the next one ...
predictions may suppose infinite police resources would prevent it, but that's
not a thing.

This might be a topic where 'prevention' isn't really possible.

~~~
smoe
I don't have numbers, but I don't think there is much home burglary as a crime
of opportunity in Switzerland. The places worth entering, usually have good
enough security measures, that you need to come prepared and it is going to
take you some time. What you usually hear is certain neighboorhoods being
scouted for lights being off for longer time, indicating the people are on
vaccation. But I don't know in what regards crime predictions systems are
useful for that, what value they add.

~~~
duxup
Interesting.

In the US break ins very much are more likely in less affluent areas.

~~~
cerebellum42
In Germany it's very much not like that, organized groups (often coming from
and returning to eastern european countries) make up a big chunk of burglaries
and they are careful to choose areas with a high effort/reward ratio, which
are rarely the low income areas.

------
infinity0
TBF this is because there is no crime in Switzerland.

The guys I work for are based in Zug ("Crypto Valley"). One time I was there,
I went to a supermarket to buy some beers in the evening. At the self-checkout
machine, as I was trying to pay, the machine asked me in German, "how old are
you", with three options, 16-, 17, 18+. The 16- and 17 was in red and the 18+
was in green, and you just had to press the green button. No ID check or staff
member coming around to look at you or anything.

------
dqpb
Predicting crime is great. It means you're working to understand the state of
your society.

Using it for policing is idiotic. You can't arrest a statistic.

Instead, it should be used for public policy, to understand what communities
are at risk, direct efforts to understand why they are risk, and engineer
better systems to support those communities.

------
t0mmel
There simply isn’t enough data to base predictions on. It will be close to
random wether or not this system will “predict” a crime, to a similar degree
that a clairvoyant can guess where the next crime will happen.

It seems like the law of small numbers at play here - or a snake-oil salesman
doing a thorough job.

------
motohagiography
I tell people, the main use case for ML is to obfuscate and launder decision
authority and accountability away from people and up into abstract
organizations where nobody is accountable. If there is ever a question as to
why the police made a decision, they can say it was their prediction model,
which is so complex nobody could reasonably expect to understand it or be
responsible for its outcomes.

It's as though artificial intelligence itself were a cryptological problem
where it's only real when it becomes sufficiently complex that information
about who is accountable for it is destroyed.

~~~
vorpalhex
I think one of the most important things we can do is to establish liability
for prediction models to the people using the model.

At the end of the day if you falsely arrest someone, fire them on bad grounds,
etc then you're the responsible party. The excuse "Well but someone told me
to!" doesn't work any better when you're blaming a machine instead of a person
- it's still bunk.

If the model is broken, well then that's on you. A vendor sold you a magical
model saying it was perfect and you got in trouble anyways? Well, you can go
on and try to sue the vendor and hash that out - after you pay for your
mistake.

It's critically important we don't allow models to become get out of jail free
cards.

~~~
progval
Other people who should be liable, at least as much as those using the model:

1\. sellers/providers of the model, if they lied about the efficiency

2\. buyers/deciders, who not necessarily the same as those using the model
(usually their bosses)

~~~
vorpalhex
You can still go after a seller for making false claims, but you are liable
for your actions - full stop. Unless the seller forced you to fire someone or
arrest someone based on the model, you executed the action.

Someone who writes your legal contract isn't liable if you badly enforce it.

------
aaron695
I think this is more government departments are easy to get money out of by
convincing them your fancy computer words are better than their Excel
spreadsheet.

Why we should treat violence like an epidemic -
[https://www.bbc.com/future/article/20180723-why-we-should-
tr...](https://www.bbc.com/future/article/20180723-why-we-should-treat-
violence-like-an-epidemic)

------
NVHacker
Not a surprise, is it ? Even I could have predicted that ;-).

------
shmerl
Reminds me Watchbird.

------
jriddle567
at least they created some jerbs

------
thoraway1010
Ha.

The swiss had something like 50 murders TOTAL of which only 3 were unsolved.
That's something like 0.5 per 100,000?

The USA is probably an ORDER OF MAGNITUDE higher?

The solve rates for crimes in the USA is horrendous - something like 35% in
places like Baltimore.

Before we talk about how little the swiss have to show for their approach,
perhaps we should allow them a touch of credit for creating a system that has
reduced homicides AND led to the identification and conviction of those who
commit them?

And maybe do something about the 15,000+ people killed per year in the US?

~~~
oh_sigh
The story is about how a specific technology doesn't move the needle much, not
about where the needle started off at.

~~~
thoraway1010
But it misses the larger context which is that Swiss are proactive in trying
to reduce crime through many approaches. They use many automated tools,
hotspot mapping etc. The article even mentions they use something like 20
tools.

As a result of this larger effort, they have kept crime low and solve lots of
serious crime.

The US has really moved to what I might call the critique approach in this
area. No one is willing to propose actual solutions, but everyone likes to
complain and critique. This creates somewhat of a do nothing or can't do
effect in govt especially and I think also reduces attractiveness of
professions like policing or working in govt (you can't ever actually do or
even try things without folks eagerly slamming you).

Pretty pathetic - and doesn't bode well for our covid testing / tracing
response either.

------
ExcavateGrandMa
Police is there for ascertainment... nothing much...

If someone wanna split the shell from the kernel...

You'll get splitted... unless you are as crazy than the splitter :)

Take it easy... it just an imaging of the real reality...

