The Law School

Artificial intelligentialization in judicial adjudication means machines can replace human judges to make certain legal decisions independently. There are two approaches to intelligentializing legal decision making, the first approach is legal expert systems which run on explicitly coded, closed-rule algorithms, and the second one is predictive analytics which develop through machine learning algorithms. Expert systems have developed over the years and relevant limitation have appeared; while big data algorithms are making robust progress, but they are unlikely to be successful as well. Firstly, the adjudication results cannot be predicted based on the regularity of big data in nature; secondly, machine adjudication destructs the traditional presumptions of administration of justice, dispels the human autonomy and disobeys the original intention of inventing artificial intelligence, and it is weaker to justify algorithm judgment for its promotion of similar cases being treated similarly or restriction of judicial discretion; lastly, as judicatory system has its particularity, it is difficult to satisfy the needs of learning algorithm technically. Therefore, artificial intelligence cannot and shall not be an adjudicator like a human judge, and what is more appropriate is to tap its potential as an assisting tool in judicatory.
Keywords: judicial adjudication; artificial intelligence; machine learning; big data; predictive theory of law