{"id":190706,"date":"2017-05-02T23:03:25","date_gmt":"2017-05-03T03:03:25","guid":{"rendered":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/artificial-intelligence-prevails-at-predicting-supreme-court-decisions-science-magazine\/"},"modified":"2017-05-02T23:03:25","modified_gmt":"2017-05-03T03:03:25","slug":"artificial-intelligence-prevails-at-predicting-supreme-court-decisions-science-magazine","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/artificial-intelligence\/artificial-intelligence-prevails-at-predicting-supreme-court-decisions-science-magazine\/","title":{"rendered":"Artificial intelligence prevails at predicting Supreme Court decisions &#8211; Science Magazine"},"content":{"rendered":"<p><p>        Artificial intelligence can predict Supreme Court decisions        better than some experts.      <\/p>\n<p>      davidevison\/iStockphoto    <\/p>\n<p>    By Matthew HutsonMay. 2,    2017 , 1:45 PM  <\/p>\n<p>    See you in the Supreme Court! President Donald Trump tweeted    last week, responding to lower court holds on his national    security policies. But is taking cases all the way to the    highest court in the land a good idea? Artificial intelligence    may soon have the answer. A new study shows that computers can    do a better job than legal scholarsat predicting Supreme    Court decisions, even with less information.  <\/p>\n<p>    Several other studies have guessed at justices behavior with    algorithms. A 2011 project, for example, used the votes of any    eight justices from 1953 to 2004 to predict the vote of the    ninth in those same cases,     with 83% accuracy. A 2004 paper tried seeing into the    future, by using decisions from the nine justices whod been on    the court since 1994 to predict the outcomes of cases in the    2002 term. That    method had an accuracy of 75%.  <\/p>\n<p>    The new study draws on a much richer set of data to predict the    behavior of any set of justices at any time. Researchers used    the Supreme Court    Database, which contains information on cases dating back    to 1791, to build a general algorithm for predicting any    justices vote at any time. They drew on 16 features of each    vote, including the justice, the term, the issue, and the court    of origin. Researchers also added other factors, such as    whether oral arguments were heard.  <\/p>\n<p>    For each year from 1816 to 2015, the team created a    machine-learning statistical model called a random forest. It    looked at all prior years and found associations between case    features and decision outcomes. Decision outcomes included    whether the court reversed a lower courts decision and how    each justice voted. The model then looked at the features of    each case for that year and predicted decision outcomes.    Finally, the algorithm was fed information about the outcomes,    which allowed it to update its strategy and move on to the next    year.  <\/p>\n<p>    From 1816 until 2015,     the algorithm correctly predicted 70.2% of the courts 28,000    decisions and 71.9% of the justices 240,000 votes, the    authors report in PLOS ONE. That bests the popular    betting strategy of always guess reverse, which has been the    case in 63% of Supreme Court cases over the last 35 terms. Its    also better than another strategy that uses rulings from the    previous 10 years to automatically go with a reverse or an    affirm prediction. Even knowledgeable legal experts are only about 66%    accurate at predicting cases, the 2004 study found. Every    time weve kept score, it hasnt been a terribly pretty picture    for humans, says the studys lead author, Daniel Katz, a law    professor at Illinois Institute of Technology in Chicago.  <\/p>\n<p>    Roger Guimer, a physicist at Rovira i Virgili University in    Tarragona, Spain, and lead author of the 2011 study, says the    new algorithm is rigorous and well done. Andrew Martin, a    political scientist at the University of Michigan in Ann Arbor    and an author of the 2004 study, commends the new team for    producing an algorithm that works well over 2 centuries.    Theyre curating really large data sets and using    state-of-the-art methods, he says. Thats scientifically    really important.  <\/p>\n<p>    Outside the lab, bankers and lawyers might put the new    algorithm to practical use. Investors could bet on companies    that might benefit from a likely ruling. And appellants could    decide whether to take a case to the Supreme Court based on    their chances of winning. The lawyers who typically argue    these cases are not exactly bargain basement priced, Katz    says.  <\/p>\n<p>    Attorneys might also plug different variables into the model to    forge their best path to a Supreme Court victory, including    which lower court circuits are likely to rule in their favor,    or the best type of plaintiff for a case. Michael Bommarito, a    researcher at Chicago-Kent College of Law and study co-author,    offers a real example in National Federation of Independent    Business v. Sebelius, in which the Affordable    Care Act was on the line: One of the things that made that    really interesting was: Was it about free speech, was it about    taxation, was it about some kind of health rights issues? The    algorithm might have helped the plaintiffs decide which issue    to highlight.  <\/p>\n<p>    Future extensions of the algorithm could include the full text    of oral arguments or even expert predictions. Says Katz: We    believe the blend of experts, crowds, and algorithms is the    secret sauce for the whole thing.  <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>Read more here:<\/p>\n<p><a target=\"_blank\" rel=\"nofollow\" href=\"http:\/\/www.sciencemag.org\/news\/2017\/05\/artificial-intelligence-prevails-predicting-supreme-court-decisions\" title=\"Artificial intelligence prevails at predicting Supreme Court decisions - Science Magazine\">Artificial intelligence prevails at predicting Supreme Court decisions - Science Magazine<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> Artificial intelligence can predict Supreme Court decisions better than some experts. davidevison\/iStockphoto By Matthew HutsonMay <a href=\"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/artificial-intelligence\/artificial-intelligence-prevails-at-predicting-supreme-court-decisions-science-magazine\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[187742],"tags":[],"class_list":["post-190706","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/posts\/190706"}],"collection":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/comments?post=190706"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/posts\/190706\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/media?parent=190706"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/categories?post=190706"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/tags?post=190706"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}