If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This master's thesis discusses an important issue regarding how algorithmic decision making (ADM) is used in crime forecasting. In America forecasting tools are widely used by judiciary systems for making decisions about risk offenders based on criminal justice for risk offenders. By making use of such tools, the judiciary relies on ADM in order to make error free judgement on offenders. For this purpose, one of the quality measures for machine learning techniques which is widly used, the $AUC$ (area under curve), is compared to and contrasted for results with the $PPV_k$ (positive predictive value). Keeping in view the criticality of judgement along with a high dependency on tools offering ADM, it is necessary to evaluate risk tools that aid in decision making based on algorithms. In this methodology, such an evaluation is conducted by implementing a common machine learning approach called binary classifier, as it determines the binary outcome of the underlying juristic question. This thesis showed that the $PPV_k$ (positive predictive value) technique models the decision of judges much better than the $AUC$. Therefore, this research has investigated whether there exists a classifier for which the $PPV_k$ deviates from $AUC$ by a large proportion. It could be shown that the deviation can rise up to 0.75. In order to test this deviation on an already in used Classifier, data from the fourth generation risk assement tool COMPAS was used. The result were were quite alarming as the two measures derivate from each other by 0.48. In this study, the risk assessment evaluation of the forecasting tools was successfully conducted, carefully reviewed and examined. Additionally, it is also discussed whether such systems used for the purpose of making decisions should be socially accepted or not.
But many technologies that later came to be considered essential parts of modern life began their life as unnecessary technical baubles. For example, in 1970, the first consumer VCR prototype was unveiled at CES, a technology previously only needed by television studios. The home VCR then started the home-viewing and -recording revolution, leading to a critical U.S. Supreme Court decision regarding copyright, and laying the groundwork for YouTube and Netflix. Even when a technology goes nowhere--3D TV glasses anyone?--looking at widgets, gizmos, and novelties can still provide a unique window into larger technological and cultural trends.
As per the National Judicial Data Grid, over 26 Mn cases are pending across all the Local, District and High Courts and the Hon'ble Supreme Court of India and close to 9% of these cases are pending over 10 years or more. On average 30,000 cases are filed every day and roughly 28,000 cases are adjudicated daily.
This post was originally published on The Business Insider. Robots are coming for your job. That may sound vaguely dystopian, but it's on the horizon. A 2013 study from Oxford University found that a whopping 47% of US jobs could be automatized in 20 years. Jobcase CEO and founder Fred Goff has seen fears about this trend crop up among some of the 70 million users of his blue-collar-friendly job site.
Is it possible to predict the outcomes of legal cases – such as Supreme Court decisions – using Artificial Intelligence (AI)? I recently had the opportunity to consider this point at a talk that I gave entitled "Machine Learning Within Law" at Stanford. The general idea behind such approaches is to use computer-based analysis of existing data (e.g. The approach to using data to inform legal predictions (as opposed to pure lawyerly analysis) has been largely championed by Prof. Katz – something that he has dubbed "Quantitative Legal Prediction" in recent work.
A home once built by Texas Gov. Greg Abbott is seen in Austin, Texas, Thursday, Aug. 10, 2017. While serving as state attorney general in 2011, Abbott tore down his Austin home and built the new one. City records show Abbott was allowed to do so as long as he didn't damage the root systems of two large pecan trees, though roots were eventually damaged in the renovations. As governor, Abbott has called tree ordinances like Austin's "socialistic."