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Scientists Create AI Program That Can Predict Human Rights Trials With 79 Percent Accuracy (theverge.com)
An anonymous reader quotes a report from The Verge: Computer scientists have created an AI program capable of predicting the outcome of human rights trials. The program was trained on data from nearly 600 cases brought before the European Court of Human Rights (ECHR), and was able to predict the court's final judgement with 79 percent accuracy. Its creators say it could be useful in identifying common patterns in court cases, but stress that they do not believe AI will be able to replace human judgement. As described in a study published in the journal PeerJ Computer Science, the AI program worked by analyzing descriptions of court cases submitted to the ECHR. These descriptions included summaries of legal arguments, a brief case history, and an outline of the relevant legislation. The cases were grouped into three main violations of human rights law, including the prohibition on torture and degrading treatment; the right to a fair trial; and the right to "respect for private and family life." (Used in a wide range of cases including illegal searches and surveillance.) The AI program then looked for patterns in this data, correlating the courts' final judgements with, for example, the type of evidence submitted, and the exact part of the European Convention on Human Rights the case was alleged to violate. Aletras says a number of patterns emerged. For example, cases concerning detention conditions (eg access to food, legal support, etc.) were more likely to end in a positive judgement that an individual's human rights had been violated; while cases involving sentencing issues (i.e., how long someone had been imprisoned) were more likely to end in acquittal. The researchers also found that the judgements of the court were more dependent on the facts of the case itself (that is to say, its history and its particulars) than the legal arguments (i.e., how exactly the Convention on Human Rights had or had not been violated).
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Scientist to replace AI with much cheaper coin based rechnology.
How about some tits now
Here I am, only weeks away from completing my graduate degree in Predictive Human Rights Jurisprudence, and some jerkhead has built an artificial intelligence to take away my job!
I knew I should have stayed with medicine... we could have a cure for diabetic mice by now, if I hadn't listened to my advisor.
call it MVP
... implemented in shell:
while :; do echo 'Fuck human rights!'; done
(NSF, you can just mail me the check.)
why do people slap "AI" label on unnecessarily? publicity?
"The AI program then looked for patterns in this data, correlating the courts' final judgements with, for example, the type of evidence submitted ...a number of patterns emerged ...For example, cases concerning detention conditions ... more likely ...cases involving sentencing ...more likely"
this is mere data analysis. or is that what so called "AI" amount to?
and this,
"judgements of the court were more dependent on the facts of the case itself "
duh?!
how smart of so called "AI" to find that out?
God, not another "AI Program". We used to just call them programs.
You can't even tell if it's better than a coin toss. For this statistic to have any meaning at all you need to know the frequency the plaintiff wins. For example, let is suppose that the plaintiff wins in 79% of cases. Then an "AI" that merely always guess the plaintiff won would be correct in 79% of cases.
In fact given that it's unlikely the outcome is 50:50, then one would expect that such a dumb algorithm would be correct more often than not just by always guessing one side. It would therefore take very little extra "intelligence" so boost it over the top. In particular such intelligence could be simply an artifact of the data set. As an example suppost the data set contained 10% of plaintiffs whose names started with R. If this group of people won more often than the avergage, then simply learing to guess "win" anytime there was a plaintiff with an "R" name would improve the test. This is true even if you split the data up into cross validation sets, as the bias for "R" will persist on any randomly Chosen subset as well.
thus the results probably are meaningless. Certainly the article is.
Some drink at the fountain of knowledge. Others just gargle.
From the goddamn dictionary:
Artificial Intelligence:
1: a branch of computer science dealing with the simulation of intelligent behavior in computers
2: the capability of a machine to imitate intelligent human behavior ...so, looking through data and predicting an outcome sounds a damn lot like "simulating intelligent behavior."
Why is this so damn hard to understand? This is what AI is.
Another Improbable program.
Some drink at the fountain of knowledge. Others just gargle.
If defendant=African dictator then verdict=guilty.
Most of them never come to trial
Terrorist like IISIS and Boko Haram will die rather than be captured
The leaders of large countries (eg Putin, GWB and the chinese) never submit to international tribunal
...humans were wrong.
Slashdot, fix the reply notifications... You won't get away with it...
Seriously, what is the endgame here? Having robots adjudicate human rights? How in the world does that seem like progress to anyone?
Most of them never come to trial
Terrorist like IISIS and Boko Haram will die rather than be captured
The leaders of large countries (eg Putin, GWB and the chinese) never submit to international tribunal. US officials like Clinton use blackmail and political clout to avoid prosecution.
The USA has become no different than Russia or China, we don't prosecute our criminals in public office either. Welcome to the USSA.
"The most predictive topics for Article 3 decisions. Most predictive topics for Article 3, represented by the 20 most frequent words, listed in order of their SVM weight."
Oh dear, word analysis frequency as predictor of court outcome, a new low.
Look, data doesn't follow trends, trends are fitted to data and thus trends follow the changes in that data. So you analyse the word frequency and that's a function of the people in the court doing the judgements, and perhaps their biases and social situation and language and ethic background. The words frequency doesn't DRIVE the decision it REFLECTS the people making the decision.
And as those parameters shift, so will the outcome. Perhaps a judge leaves and another takes his place, or a prosecutor moves office, and his speech patterns are different, and thus the word count for that court is different. There's no reason for that new word count to now match the prosecution record.
We're seeing similar joke data mining going on in government (and science) all the time. Some of the classic faults:
1. They fail to identify the key causal driver, so they're data-mining for some transient metric. e.g. word count.
2. Overlapping data and test data. Train it on 600 case, now test it on 400 cases from the same courts (which have the same judges and prosecutors and thus the same speech patterns and similar word count at the moment).
3. Feedback loops, e.g. police predictive system says "go police in black areas", which leads to more black arrests which leads to more policing in black areas and so on. Yet the crimes are reported all over the city, not just the black areas, its that they've filtered the crime reports in a way that backs up their prediction and are updating their metrics in response to their filtered crime data.
4. The loop in 3 is often hidden, e.g. grab the results from the busiest courts as representative, which deal with the black areas which deal with the most cases because that's where the program sent the police last year.
5. A machine makes 2 widgets at a time, the machine has independent properties, and imparts those properties to the parts it makes. The properties are not connected in any way in reality. If I filter such that I only pick two widgets made at the same time, and test one property, I can predict the state of the other properties. e.g. Judge Fred takes the decision, Judge Fred is heavy on the word "violent" and "banana", so a mechanism that picks filters for Judge Fred will tend to score well on violent bananas. It makes no difference that "violent" and "bananas" are independent, I created the dependency by my choices, a la QM.
predicts that the /. forum will stay as shitty as it is. 100%
And shit. There are too many possible nuances here to even apply a model of 'predictability'. And fuck whoever it was that posted the initial 'on topic' nonsense. This is insanity, plain and simple.
Now make that program a mandatory control in all other AI programs so no one can order an AI to violate human rights.
You misunderstand. This is an "Al" program, as in Al Gore or Al Franklin, extremely liberal and so sure of its view on human rights that it is wrong 21% of the time. A.I. would never make that mistake.
I'm an American. I love this country and the freedoms that we used to have.
That AI would have a tough time in the US. After all, various courts have ruled that serving disgusting food on purpose as punishment and/or cost savings is A-OK, even if it's so terrible it typically results in malnourishment due to inmates choosing not to eat it.
I'm talking about nutraloaf here, not cheap mystery meat sandwiches. A "meal" purposely designed to taste inedible, but yet actually be edible.
I am very glad on Scientist's this invention, but I want to ask you something as I don't know, is this a recent invention, I think this is an old research. What you say?
I'll write you an algorithm to do this right now:
If country == islamic {
victim = screwed
}
Tada! Human rights trial outcome predictor 1.0 is now complete!
Not to be pissy or anything but let's face it. By the time a human rights violation has case has 'come to trial' it is nearly a forgone conclusion. Were 10K people massacred ? Was an entire countryside gassed ? Did the members of an entire tribe suddenly disappear ? Was a mushroom cloud, and nerve gas involved ? It doesn't take much of an AI or computer to come to a conclusion in those kinds of cases.
errr....umm...*whooosh* *whoosh* Is this thing on ?
In fact we shouldn't expect these to be too predictable. This is why they go all the way to the ECtHR in the first place
if (plaintiff = well known SJW) then trial = success
If this system is based on previous trial outcomes then the AI would not be "intelligent" enough to recognize massive human rights violations that are perpetually committed by the state of Israel in occupied Palestine and elsewhere.
Great news for Israel. Terrible for the rest of the world.
The outcome of Bush, Obama, Cheney and Yoo's trials.
So they like facts more than legal arguments? Thats great, we have lots of those. Drone strikes targeted by cell phone data killing innocent people. A whole system of assasination based on paid informants and lies. A torture program that was swept under the rug rather than exposed and prosecuted....
Lots and lots of facts for them.
"I opened my eyes, and everything went dark again"
but how well does it do with cases not in the training data set?
I can predict Egyptian and Russian human rights trials with 100% accuracy with a simple shell script.
echo "Guilty!"
So I coin toss could predict it with 50% accuracy. How well can a human being perform the same task? Not sure that 20% better then a coin toss makes your AI very intelligent. Of coarse I'm sure it is just the beginning of a lot of cool work.
âoeTolerance applies only to persons, but never to truth. Intolerance applies only to truth, but never to persons.
Using a machine to predict human behavior.
We humans still need the ability to correctly predict machine behavior. Like what day your car will break down on the freeway in rush hour, when you're late to work.
If you don't, you have no rights.
BTW, there is no right to "standing" or for the government to reveal that you even potentially have "standing.
Prove anything by multiplying Huge Number times Tiny Number