7 ms·

AI ‘judge’ can predict court verdicts with 79 per cent accuracy

mtgx 10y ago
I'm always amused by people who see these headlines like "AI does X with 80% accuracy" and think that's high. That's terrible accuracy. Imagine this algorithm would then be refitted to replace the judge (or augment judges in a way that judges mostly rely on the tool to make a decision, which is already starting to happen [1]) and automatically put people in prison - with only 80% accuracy. Does that number still seem high now? [1] - https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing https://www.propublica.org/article/machine-bias-risk-assessm...
- CapitalistCartr 10y ago
  They only get better, never worse. And the use is not for actual judging, but to estimate different approaches to a case. Tactical analysis, basically. Both sides plus the media have a serious use for this, so money will flow.
  - logfromblammo 10y ago
    This will certainly be used by professional legal counsel to help determine whether they should take your case, and how best to charge you for their services. Cases predicted to win might be taken on contingency, for a fraction of the judgment award. Cases predicted to lose might be pay-as-you-go for each appearance or filing.
- josaka 10y ago
  It's tough to evaluate the usefulness of the 80% claim without a baseline. If a simple heuristic of "plaintiff wins" is correct 85% of the time, the model isn't that impressive. In the long run, such a model would likely be confounded by the parties, who'd model and adapt their arguments to drive the model to a favorable result or settle cases where the model provides a strong signal to which they can't adapt. (Which is not to suggest that this wouldn't be a very socially valuable result.)
- arcanus 10y ago
  I generally agree with your skepticism of \% as a meaningful metric for AI accuracy or technological prowess. However, do we have any reason to believe that a collection of random, qualified judges would be able to predict the outcome of a court verdict with 80% accuracy? I would be surprised if judicial decisions are not stochastic. Also, we should consider a substitution effect. According to a cursory internet search, 'As of 2012, the pay for federal district judges was $174,000 per year'. If this system is substantially less expensive to purchase and maintain, then there is an argument to be made that it is more efficient, and provides better value, even with a perpetually reduced accuracy.
  - notahacker 10y ago
    I suspect a collection of random, unqualified members of the public could predict the outcome with 100% accuracy using the written judgement as the basis for their evaluation, as appears to be the case in this study...
  - tpm 10y ago
    Even if it was cheaper to purchase and maintain, it wouldn't be more efficient, because money spent is not necessarily the measure of the efficiency of the justice system. That could be, for example, lower criminality. If a system fails to jail enough criminals to do that, even if it's cheap, it's not working. And also, false positives (e.g. jailed innocent people) are especially troubling and can be very expensive in a justice system.
  - rayiner 10y ago
    Most cases are quite routine and easily predictable.
  - dragonwriter 10y ago
    > However, do we have any reason to believe that a collection of random, qualified judges would be able to predict the outcome of a court verdict with 80% accuracy? I think a random selection of second-year law students could probably beat 80% (by about 19 percentage points) predicting the outcome of a court decision from the facts and law sections of the same decision.
- falcolas 10y ago
  I think it's the 80/20 problem. I've heard of a lot of algorithms which hit the 80% mark, but getting hire than that is too cost ineffective. So ineffective that it's usually cheaper to hire low skill workers to validate the output of the algorithms, especially when accuracy matters. I've heard of it at Google and Bing for popular searches. I've seen it firsthand at a company applying classifiers to twitter posts. Microsoft took how long to go from "80%" voice recognition to their stated 96% (with generous assertions about the environment and language)? Apple/Google/et.al. still rely on humans to act as validators for the training of thir personal assistants. I have trouble seeing for-profit companies ever truly getting higher than the 80%; it's just too expensive when cheap labor also exists.
- empath75 10y ago
  > I'm always amused by people who see these headlines like "AI does X with 80% accuracy" and think that's high. "High" is a relative term. At one point, a chess program beating any human was an impressive feat. Today, any human beating a chess program is an impressive feat.
- dragonwriter 10y ago
  It doesn't really make sense to talk about replacing the judge (judges, really, since this is specific to the European Court of Human Rights) with this AI, anyway, since this AI "predicts" based on portions of the document written by the Court to explain the decision it has made. It's like replacing a playright with an AI that predicts Act III from the content of Acts I and II.
thecolorblue 10y ago
What cases are misses? Did those cases get overturned later?
Grue3 10y ago
There are countries where more than 90% of court cases result in "guilty" verdict. My AI judge that always says "guilty" has very high accuracy in these jurisdictions.
- libeclipse 10y ago
  Therein lies the problem of the accuracy of predictions. If there's three AI judges, one gives a court case a 35% chance of being guilty, the other a 40%, and the last a 45%. The case was a guilty. Were the predictions correct?
  - kgwgk 10y ago
    Measuring the accuracy of a single prediction is difficult, but there are reasonable ways to measure the accuracy of a set of predictions. For example, https://en.wikipedia.org/wiki/Brier_score https://en.wikipedia.org/wiki/Brier_score
- binalpatel 10y ago
  This is the imbalanced class problem that comes up often in the real world. You can't optimize for overall accuracy, otherwise you'd have classifiers that always just predict guilty (or not sick, or not fradulent, and so on) because they'd achieve 95%+ accuracy.
  - hammock 10y ago
    So what is the metric to optimize?
    - binalpatel 10y ago
      I use AUC often, and always look at the confusion matrix. Metrics based off of it (recall, precision) are both useful to use as well. In the end the probability cutoffs you choose are more often than not based on business context and costs associated with various actions. For example - if we're trying to predict whether a customer is going to leave or not, I'd choose a different threshold based on whether we're mass e-mailing people, or if we're having customer service reps call people, since the underlying costs for each action are so different. In the first case it's fine to cast a wide net, and e-mail lots of people who we're less certain about, in the second we'd optimize to target people we're most sure are going to leave, since it costs so much more to reach out to them.
raverbashing 10y ago
This is one case where something much higher above this value would be an indicative of overfitting. This is not like classifying pictures between obvious classes, but something more complex
denzil_correa 10y ago
Full Paper : https://peerj.com/articles/cs-93/ https://peerj.com/articles/cs-93/ I think the authors list down the "Accuracy" but I would be really interested to see "Precision, Recall and F1" scores for this classification task.
norswap 10y ago
Another question is whether a human could have predicted as well or better. If not, it does not help with the actual difficult case of predicting the outcome of a case that isn't clear-cut for a human.
h4nkoslo 10y ago
It sounds like they effectively built a rhetoric detector. "The team found that judgements by the European Court of Human Rights are often based on non-legal facts rather than directly legal arguments, suggesting that judges are often swayed by moral considerations father than simply sticking strictly to the legal framework."
danvoell 10y ago
I assume that inputting historical judgements by the judge ruling over the case would improve the results but could also prove whether bias was involved.
ppereira 10y ago
It should be noted that these predictions are not based on the lawyers' pleadings, but on the facts and law sections from the judges' decisions.[1] There is definitely a possibility of bias in the characterization of the facts. The authors state that for their appellate court, the facts section is uncontested by the parties and derived from the lower court's findings. Even so, it is not clear whether the court's reversal rate is high or low. If low, it could be that the lower court's presentation of the facts was equally varnished. With some judges, it is possible to predict the outcome of the case from the very first sentence laying out the facts and circumstances. In a famous dissenting judgement by Lord Denning, in which he attempts to save a cricket field, the judge begins as follows:[2] In summertime village cricket is the delight of everyone. Nearly every village has its own cricket field where the young men play and the old men watch. In the village of Lintz in County Durham they have their own ground, where they have played these last 70 years. They tend it well. The wicket area is well rolled and mown. The outfield is kept short. It has a good club house for the players and seats for the onlookers. The village team play there on Saturdays and Sundays. They belong to a league, competing with the neighbouring villages. On other evenings after work they practise while the light lasts. Yet now after these 70 years a judge of the High Court has ordered that they must not play there any more. Even with this critique, I think that this research is an excellent first step. It would be great to use pleadings, which are available with effort from some appellate courts. It would likely be necessary to OCR some PDF files. I doubt that this textual approach would work for the more technical parts of the law. Many cases are in areas with very few preceding cases from which to train an n-gram based algorithm. While the author's approach worked for certain human rights cases, it would likely fail for cases turning on an obscure tax provision. [1] Original paper: https://peerj.com/articles/cs-93/ https://peerj.com/articles/cs-93/ [2] Miller v Jackson [1977] QB 966, see: https://en.wikipedia.org/wiki/Miller_v_Jackson https://en.wikipedia.org/wiki/Miller_v_Jackson
visarga 10y ago
With under 600 training examples I doubt it would be able to generalize well on unseen data.
dragonwriter 10y ago
Predicting the outcome of a case from the text of the decision in the case (even if only the facts and law sections) isn't that impressive, since that material is selected from all the facts and law that has been presented and considered to focus on what is relevant to and determinative of the outcome.
Iv 10y ago
Compared to which score for a layperson?

mtgx 10y ago

I'm always amused by people who see these headlines like "AI does X with 80% accuracy" and think that's high. That's terrible accuracy. Imagine this algorithm would then be refitted to replace the judge (or augment judges in a way that judges mostly rely on the tool to make a decision, which is already starting to happen [1]) and automatically put people in prison - with only 80% accuracy. Does that number still seem high now? [1] - https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing https://www.propublica.org/article/machine-bias-risk-assessm...

CapitalistCartr 10y ago
They only get better, never worse. And the use is not for actual judging, but to estimate different approaches to a case. Tactical analysis, basically. Both sides plus the media have a serious use for this, so money will flow.
- logfromblammo 10y ago
  This will certainly be used by professional legal counsel to help determine whether they should take your case, and how best to charge you for their services. Cases predicted to win might be taken on contingency, for a fraction of the judgment award. Cases predicted to lose might be pay-as-you-go for each appearance or filing.
josaka 10y ago
It's tough to evaluate the usefulness of the 80% claim without a baseline. If a simple heuristic of "plaintiff wins" is correct 85% of the time, the model isn't that impressive. In the long run, such a model would likely be confounded by the parties, who'd model and adapt their arguments to drive the model to a favorable result or settle cases where the model provides a strong signal to which they can't adapt. (Which is not to suggest that this wouldn't be a very socially valuable result.)
arcanus 10y ago
I generally agree with your skepticism of \% as a meaningful metric for AI accuracy or technological prowess. However, do we have any reason to believe that a collection of random, qualified judges would be able to predict the outcome of a court verdict with 80% accuracy? I would be surprised if judicial decisions are not stochastic. Also, we should consider a substitution effect. According to a cursory internet search, 'As of 2012, the pay for federal district judges was $174,000 per year'. If this system is substantially less expensive to purchase and maintain, then there is an argument to be made that it is more efficient, and provides better value, even with a perpetually reduced accuracy.
- notahacker 10y ago
  I suspect a collection of random, unqualified members of the public could predict the outcome with 100% accuracy using the written judgement as the basis for their evaluation, as appears to be the case in this study...
- tpm 10y ago
  Even if it was cheaper to purchase and maintain, it wouldn't be more efficient, because money spent is not necessarily the measure of the efficiency of the justice system. That could be, for example, lower criminality. If a system fails to jail enough criminals to do that, even if it's cheap, it's not working. And also, false positives (e.g. jailed innocent people) are especially troubling and can be very expensive in a justice system.
- rayiner 10y ago
  Most cases are quite routine and easily predictable.
- dragonwriter 10y ago
  > However, do we have any reason to believe that a collection of random, qualified judges would be able to predict the outcome of a court verdict with 80% accuracy? I think a random selection of second-year law students could probably beat 80% (by about 19 percentage points) predicting the outcome of a court decision from the facts and law sections of the same decision.
falcolas 10y ago
I think it's the 80/20 problem. I've heard of a lot of algorithms which hit the 80% mark, but getting hire than that is too cost ineffective. So ineffective that it's usually cheaper to hire low skill workers to validate the output of the algorithms, especially when accuracy matters. I've heard of it at Google and Bing for popular searches. I've seen it firsthand at a company applying classifiers to twitter posts. Microsoft took how long to go from "80%" voice recognition to their stated 96% (with generous assertions about the environment and language)? Apple/Google/et.al. still rely on humans to act as validators for the training of thir personal assistants. I have trouble seeing for-profit companies ever truly getting higher than the 80%; it's just too expensive when cheap labor also exists.
empath75 10y ago
> I'm always amused by people who see these headlines like "AI does X with 80% accuracy" and think that's high. "High" is a relative term. At one point, a chess program beating any human was an impressive feat. Today, any human beating a chess program is an impressive feat.
dragonwriter 10y ago
It doesn't really make sense to talk about replacing the judge (judges, really, since this is specific to the European Court of Human Rights) with this AI, anyway, since this AI "predicts" based on portions of the document written by the Court to explain the decision it has made. It's like replacing a playright with an AI that predicts Act III from the content of Acts I and II.

thecolorblue 10y ago

What cases are misses? Did those cases get overturned later?

Grue3 10y ago

There are countries where more than 90% of court cases result in "guilty" verdict. My AI judge that always says "guilty" has very high accuracy in these jurisdictions.

libeclipse 10y ago
Therein lies the problem of the accuracy of predictions. If there's three AI judges, one gives a court case a 35% chance of being guilty, the other a 40%, and the last a 45%. The case was a guilty. Were the predictions correct?
- kgwgk 10y ago
  Measuring the accuracy of a single prediction is difficult, but there are reasonable ways to measure the accuracy of a set of predictions. For example, https://en.wikipedia.org/wiki/Brier_score https://en.wikipedia.org/wiki/Brier_score
binalpatel 10y ago
This is the imbalanced class problem that comes up often in the real world. You can't optimize for overall accuracy, otherwise you'd have classifiers that always just predict guilty (or not sick, or not fradulent, and so on) because they'd achieve 95%+ accuracy.
- hammock 10y ago
  So what is the metric to optimize?
  - binalpatel 10y ago
    I use AUC often, and always look at the confusion matrix. Metrics based off of it (recall, precision) are both useful to use as well. In the end the probability cutoffs you choose are more often than not based on business context and costs associated with various actions. For example - if we're trying to predict whether a customer is going to leave or not, I'd choose a different threshold based on whether we're mass e-mailing people, or if we're having customer service reps call people, since the underlying costs for each action are so different. In the first case it's fine to cast a wide net, and e-mail lots of people who we're less certain about, in the second we'd optimize to target people we're most sure are going to leave, since it costs so much more to reach out to them.

raverbashing 10y ago

This is one case where something much higher above this value would be an indicative of overfitting. This is not like classifying pictures between obvious classes, but something more complex

denzil_correa 10y ago

Full Paper : https://peerj.com/articles/cs-93/ https://peerj.com/articles/cs-93/ I think the authors list down the "Accuracy" but I would be really interested to see "Precision, Recall and F1" scores for this classification task.

norswap 10y ago

Another question is whether a human could have predicted as well or better. If not, it does not help with the actual difficult case of predicting the outcome of a case that isn't clear-cut for a human.

h4nkoslo 10y ago

It sounds like they effectively built a rhetoric detector. "The team found that judgements by the European Court of Human Rights are often based on non-legal facts rather than directly legal arguments, suggesting that judges are often swayed by moral considerations father than simply sticking strictly to the legal framework."

danvoell 10y ago

I assume that inputting historical judgements by the judge ruling over the case would improve the results but could also prove whether bias was involved.

ppereira 10y ago

It should be noted that these predictions are not based on the lawyers' pleadings, but on the facts and law sections from the judges' decisions.[1] There is definitely a possibility of bias in the characterization of the facts. The authors state that for their appellate court, the facts section is uncontested by the parties and derived from the lower court's findings. Even so, it is not clear whether the court's reversal rate is high or low. If low, it could be that the lower court's presentation of the facts was equally varnished. With some judges, it is possible to predict the outcome of the case from the very first sentence laying out the facts and circumstances. In a famous dissenting judgement by Lord Denning, in which he attempts to save a cricket field, the judge begins as follows:[2] In summertime village cricket is the delight of everyone. Nearly every village has its own cricket field where the young men play and the old men watch. In the village of Lintz in County Durham they have their own ground, where they have played these last 70 years. They tend it well. The wicket area is well rolled and mown. The outfield is kept short. It has a good club house for the players and seats for the onlookers. The village team play there on Saturdays and Sundays. They belong to a league, competing with the neighbouring villages. On other evenings after work they practise while the light lasts. Yet now after these 70 years a judge of the High Court has ordered that they must not play there any more. Even with this critique, I think that this research is an excellent first step. It would be great to use pleadings, which are available with effort from some appellate courts. It would likely be necessary to OCR some PDF files. I doubt that this textual approach would work for the more technical parts of the law. Many cases are in areas with very few preceding cases from which to train an n-gram based algorithm. While the author's approach worked for certain human rights cases, it would likely fail for cases turning on an obscure tax provision. [1] Original paper: https://peerj.com/articles/cs-93/ https://peerj.com/articles/cs-93/ [2] Miller v Jackson [1977] QB 966, see: https://en.wikipedia.org/wiki/Miller_v_Jackson https://en.wikipedia.org/wiki/Miller_v_Jackson

visarga 10y ago

With under 600 training examples I doubt it would be able to generalize well on unseen data.

dragonwriter 10y ago

Predicting the outcome of a case from the text of the decision in the case (even if only the facts and law sections) isn't that impressive, since that material is selected from all the facts and law that has been presented and considered to focus on what is relevant to and determinative of the outcome.

Iv 10y ago

Compared to which score for a layperson?