Impact Score 2.81
Today, the Legal Informatics (LI) is rapidly emerging as a new research area at the juncture of Computer Science (CS), Information Technology (IT) and Law. More recently, it has drawn some attention of the computational and legal communities with the intent and goal to improve and advance the existing jurisprudence/legal procedure/legal justice system/civil justice system by applying the modern computational technologies such as Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP). Although, the usage of general AI in law research is not new, but has largely remained very thin, which can be dubbed as Infant LI; however, its intensity has increased since organizations' massive digitalization, including the legal institutions and administrations. Legal studies deal with some common concerns as AI in revealing hiding patterns, representing complex knowledge sets, mapping causality between events, predicting profiles behaviors, and so forth. These shared concerns show the high potential in making AI interrelating with legal studies. Moreover, the foremost need for practitioners and academics in law comes from the side of decision-making. With the integration of ML and DL algorithms in processes, the automation in decision-making brings flexibility and speed to treat the legal cases. Many research scientists go beyond simple AI applications in law; they claim that some specific ML approaches are the most suitable to law studies because they are mostly based on accurate estimation of symbolic computing and formal-based abstracting for decision-making than biased judgments. Examples are Decision trees and random forest algorithms.
Besides, research in court cases and jurisprudence commonly uses relationships and causality mapping to detect hidden patterns shared with DL approaches. Academics in jurisprudence theories try to determine the law terms with the reasoning in connection with the society, which is the same purpose of Knowledge and Representation (KR) in ontologies, one of the main prolific sub-fields of AI. On one hand, the most common feature that makes AI close to legal and law studies is "reasoning," the essence of AI algorithms, particularly in Expert Systems (ES), optimization meta-heuristics. On the other hand, the need for legal procedure and legal justice system in "reasoning" is predominant. Moreover, the tokenization techniques play an essential role in textual interpreting research, representing the backbone of NLP, one of the most fertile AI branches in Legal Studies. In addition to the rise of Automatic Text Generation (ATG) techniques of NLP in preparing training and simulation of legal cases. Likewise, Speech-to-Text (STT) technologies and (Text-to-Speech) resulting from NLP approaches invade the law applications today in the justice administrations. An example is the automated examination of legal terms contracts for lawsuits and litigation cases. Furthermore, smart-contracts are systems that are entirely automated with AI-based processing engines. They are becoming today a real market opportunity in the so-called Legal-tech market. Emerging academic studies also increase the use of individuals' socio and psycho profiling in complex justice cases by the automated and semi-automated techniques of smart Sentiment and Emotional Analyzers (SEA) and clustering algorithms.
Given the scope of improvements, tremendous efforts are needed to explore the possibilities to develop the state-of-the-art infant LI into a mature LI. Therefore, more and more legal scholars and practitioners and the computer and data scientists and engineers are teaming up to converge their expertise and knowledges to transform the existing jurisprudence into the smart and intelligent justice system, with the intent to advancing the mature LI into “sustainable LI” in near to medium term.
We define the term “sustainable LI” as an effective legal system, which is enriched and equipped with the best computing and informatics techniques and technologies and consequently is faster, fair, tractable, democratic, economically feasible and accessible even to the last person of the underrepresented, underprivileged, and marginalized sections of society. This special issue (SI) invites the original unpublished scholarly work related to LI.
The topics of interest include, but are not limited to:
General information and instructions for submitting papers to SUSCOM can be found at the journal website: https://www.journals.elsevier.com/sustainable-computing-informatics-and-systems. Please see the “Guide for Authors” and “Submit Your Paper” links. When submitting a paper to this special issue, please make sure to select the “Special Issue: Legalics” option when prompted for “Select Article Type” during the submission process.
All submissions must be original and may not be under review by another publication. A submission based on one or more papers that appeared elsewhere has to comprise major value-added extensions over what appeared previously (at least 30% new material). Authors are requested to clearly identify prior submissions/papers and attach to the submitted paper their relevant, previously published articles with a summary explanation documenting the enhancements made in the journal submission. All submitted papers will be peer reviewed using the normal standards of SUSCOM. By submitting a paper to this issue, the authors agree to referee at least one paper if requested by SUSCOM editors.
Special Issue Guest Editors: