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Information systems generate copious trace data about what individuals do and when they do it. Trace data may affect the resolution of lawsuits by, for example, changing the time needed for legal discovery. Trace data might speed resolution by clarifying what events happened when, or they might slow resolution by generating volumes of new and potentially irrelevant data that must be analyzed. To investigate this, we analyze the effect of electronic medical records (EMRs) on malpractice claim resolution time. Use of EMRs within hospitals at the time of the alleged malpractice is associated with a four-month (12%) reduction in resolution time. Because unresolved malpractice claims impose substantial costs on the entire healthcare system, our finding that EMRs are associated with faster resolution has broad welfare implications. Furthermore, as we increasingly digitize society, the ramifications of trace data on legal outcomes matter beyond the medical context. This paper was accepted by Teck Ho, information systems.

A good investigator, whether it be in the context of an audit or a forensic investigation, recognizes the evidentiary value of digital evidence and can harness its power. The following instructional case introduces students to how digital evidence is incorporated into a forensic accounting investigation and challenges them to learn electronic discovery (eDiscovery) tools and techniques. While performing the early stages of the investigation at Enron, students gain exposure to the electronic discovery reference model (EDRM), learn the differences between structured and unstructured data, and deploy various digital search strategies. After performing their preliminary investigation, students are asked to “scope” the remainder of the investigation by creating a detailed workplan. At the conclusion of the case, students are encouraged to reflect upon their own methods of electronic communication. This encourages students to think before digitizing (and therefore memorializing) their next thought, statement, or action.

Purpose This paper aims to examine the situation of organizational information governance (IG) and its relationship with e-discovery in China. Design/methodology/approach This study collects laws, court opinions, cases and relevant literature as data and analyzes their content under the guidance of the framework of Information Governance Reference Model of the Electronic Discovery Reference Model (EDRM). Findings Inspired by discussions on the challenges of e-discovery and, in particular, the relationships between organizational IG and e-discovery in English literature, the present study attempts an examination of the relevant situations in China. It is the belief of the study that the connection between IG and the legal risk as framed in the EDRM is a necessary one for China as the country is opening its door wider and continues to seek multilateral cooperation. The study found out, through observations and analyses, the following distinctions of e-discovery and its relationship with IG in China. Despite the very similar US and Chinese digital technological environments and the similar acceptance of electronic evidence into litigations, the situations with e-discovery/electronically stored information (ESI) and IG are different within a Chinese context. Legal provisions regarding electronic evidence are brief and vague, litigating procedures rely on the explanations of the Supreme Court and the Supreme Procuratorate and, most relevantly, there is only a small portion of litigations that features a large quantity of ESI in the context of dramatically increased cases involving electronic evidence. The evidentiary qualifications of ESI, e.g. authenticity and reliability, are discussed intensively in academic writings, which, however, was done in a rather isolated manner, without referring to the relationships between and among them. The concept of proportionality, which was one of the key constructions in e-discovery discussions in English literature, was not found in these writings. As a result, organizational IG in China is not discussed in relation to e-discovery or electronic evidence, raising the question as to how e-discovery of a large quantity of ESI will be handled, should such cases emerge. Research limitations/implications Extracted mainly from available literature in legal and information fields, this study is necessarily neither exhaustive nor definitive. However, it can be used to further strengthen other empirical data studies. It could be extended within a Chinese context with interviews with legal and IG professionals. In this regard, the reasons that lead to the distinctions as exhibited in the findings could be explored in future investigations. This study does serve as a marker of the position in China compared to the USA. This research suggests that there is an opportunity for comparable studies at a national level, thus generating complementary knowledge for the IG and e-discovery community internationally. Practical implications The findings of the study may be instructive to countries with similar situations, that is, a weak linkage between IG and e-discovery. It may serve as a call for more comparable studies, thus generating complementary knowledge for the IG and e-discovery community internationally. Originality/value The study reported in this paper is the first of its kind in terms of exploring the relationships between IG and e-discovery in the Chinese context.

In the military literature, the word "electronic warfare" is very much seen and different countries, based on their knowledge, and considering the threats, design the proper models for electronic warfare. The present study aims to review and present the model of electronic support system in the 2025 horizon. The statistical population of the study was NEZAJA Electronic Warfare System. In order to collect data, by interviewing experts and studying resources, reviewing the current situation and analyzing the gap between the current and the desired situation, actual operational demands were determined in the 2025 perspective. Then, data obtained from documents and interviews with experts were analyzed by descriptive (case) and qualitative analysis approach. The results showed that various countries, drawing on their knowledge and with regard to the threats, design their own appropriate models with emphasis on the design of multiple and mobile systems and the prediction of headquarters structures at different levels for electronic warfare. Today, the widespread use of electronic warfare will definitely increase its use in the future. The use by other countries of advanced communication and non-communication systems suggests that the current system of electronic warfare to meet the current and future operational and educational demands needs to be promoted.

This paper examines how predictive coding, an artificial intelligence (AI) technology, can effectively and efficiently complement the work of lawyers in the area of electronic discovery document review in civil litigation. It begins with a general overview of AI, and how machine learning can be used to automate the document review process in civil litigation. It then proceeds to a comprehensive overview of predictive coding technology and a discussion of legal issues related to the use of predictive coding technology in civil litigation. The legal issues are whether the use of artificial intelligence technology (as opposed to human intelligence) in document review complies with the rules of the court relating to documentary disclosure; and whether litigation privilege applies to seed sets (or training sets) used in training the predictive coding algorithm. Adopting a comparative law methodology, the paper seeks to address these issues. The paper concludes with a brief consideration of legal professionalism issues arising from the adoption of predictive coding technology in civil litigation in the context of Rule 3.1 of the Model Code of Professional Conduct dealing with competency. The paper argues that successful adoption of AI technology in civil litigation will extend the lawyer’s duty of competence to include knowledge of the relevant legal technology.

It is not uncommon that a legal case consists of hundreds to thou-sands of related documents, which a lawyer needs to scan through to understand a case and find useful information, potentially a shred of evidence. Therefore, many automated tools have emerged that are specifically designed to help in the Electronic Discovery process. The most basic ones enable more or less advanced full-text search, which is a we studied field called Information Retrieval. Another field, frequently applied in the legal domain, is the Artificial Intelligence, which has delivered numerous purposeful tools that are trying to substitute a lawyer in var tasks. The tool presented in this thesis belongs to this category the goal of this research is to study, design and evaluate a mechanism that is able to highlight legal documents with valuable information and filter out the irrelevant.

Law Clerk to Chief Judge Joy Flowers Conti, United States District Court for the Western District of Pennsylvania; J.D. magna cum laude 2015, University of Pittsburgh (Lead Executive Editor, University of Pittsburgh Law Review); B.A. 2009, University of North Florida. Thank you Professor Rhonda Wasserman for your advice and assistance on this paper and for an enlightening class on electronic discovery. Faculty for the University of Pittsburgh School of Law awarded this paper the William H. Eckert Prize.

Often framed as a relatively new and controversial phenomenon, the application of machine learning (ML) techniques to legal analysis and decision-making in the US justice system has a rich yet under examined history. My research examines how ML came to be adopted as a standard tool for automating fact discovery for high-stakes civil litigation. By analyzing the key controversies and consensuses that emerge during the experimentation and early adoption phase of this technology (2008-2015), a useful case study presents itself in which an expert professional field wrestled with the challenges of integrating ML into sensitive decision-making workflows.

The fact that lawyers lack the knowledge to challenge the reliability of technical sources of frequently used kinds of evidence, and the tolerating of its impact upon the ability to “do justice,” is due to the under-performance of a number of institutions within the justice system. As a result, law and the rules of practice and procedure applicable to such evidence are moving in one direction, but the reality of what are now the main sources of evidence is moving in the opposite direction. That is the theme of this article. The justice system must be seen as one now having several defective parts, which cumulatively create its major problems, including the inability of lawyers to challenge electronic sources of evidence. A comprehensive view of the system is necessary to reveal all of the causes of its major problems and also their needed solutions. Providing lawyers with sufficient knowledge of technology is now a major problem because most of the evidence used for legal proceedings and legal services now comes from complex electronic systems and devices, including the data that is the basis of expert opinion evidence. Examples of such technology dealt with, that produce very commonly used evidence are: (1) the electronic records management systems that produce electronic records — now the most frequently used kind of evidence; (2) mobile phone tracking evidence; (3) breathalyzer/intoxilyzer devices; and, (4) TAR devices (technology assisted review devices) that are used to conduct the “records review stage” of electronic discovery proceedings. Therefore, this article deals in detail with the factors affecting the relationship between such technology and the rules of procedure affecting legal proceedings such as, electronic discovery, disclosure, preliminary inquiries, the admissibility of evidence, and the application of presumptions and inferences. But the technical literature warns that we trust the software by which they operate far too much. It warns that software errors and vulnerabilities are very prevalent and costly — error rates in the many complex applications of electronic technology. The application of procedural rules for such proceedings should therefore have regard to, for example: (1) the kind of evidence and witnesses the proponent of “the admissibility of evidence” should be required to produce in order to establish, “circumstantial guarantees of trustworthiness”; (2) at which point “the onus of proof” should be transferred to the opponent of admissibility to provide “evidence to the contrary”; (3) how the obtaining, preservation, and production of such “evidence to the contrary” can be achieved by the opposing party; and, (4) how difficult and costly will it be to do so. The answers to these issues should be seen to be interdependent, e.g., the nature of the technology that produces the evidence in question, should not be allowed to provide the proponent of admissibility an advantage that imposes an unfair onus and burden of proof upon the opponent. For example, the proponent of admissibility being required to call as witnesses the engineers and technicians responsible for the operation of the technology that produces the evidence in question, makes available to the opponent of admissibility, for cross-examination, the key witnesses who can be knowledgeably questioned about the existence of any such “evidence to the contrary.” Thus, can be avoided, the expense and time required by: (1) the opponent’s having to prepare and present arguments justifying a court order for access to the system that produced the evidence; (2) overcoming the objections of the owner/operator of the technology as to: (a) violations of the confidentiality of business information; (b) protecting intellectual property; and, (c) the expense and time lost due to disruptions caused by such outsiders intruding to conduct various examinations; plus, (3) the cost of retaining the necessary experts who would conduct such an examination of that system. What is new to such application of the rules of evidence and procedure is introducing a requirement of “fairness” when answering each of the above four questions, such that a particular answer to one of them does not to impact unfairly upon the answer forced upon one of the other questions. Therefore a “proportionate balancing of difficulties and costs” analysis is necessary, e.g., what is fair to the proponent of admissibility must also be equally fair to the opponent of admissibility. And such a “proportionality analysis” is required not only for such adjunct proceedings as discovery, and voir dires, and preliminary inquiries, but also to ensure that there will be a sufficient “opportunity to make full answer and defence” within the trial itself, as is required by Canadian Charter of Rights and Freedoms ss. 7 and 11(d). But such decisions require a sufficient knowledge of the technology that produces the evidence so as to be able to assess such factors as the difficulty and cost of producing the necessary proof of “circumstantial guarantees of reliability” and “evidence to the contrary,” and what will constitute a sufficient “opportunity to make full answer and defence” at trial. The rules of evidence and procedure should be altered, or made sufficiently flexible so that different technologies can produce different answers for each of those issues. The weaknesses of the justice system that result in lawyers’ inadequate knowledge of technology, and inadequate procedures by which to challenge technology’s reliability to produce such commonly used evidence, concern its institutions such as: governments, law societies, the courts system, law schools, and those institutions that produce standards that concern the manufacturing, use, and maintenance of such technology. If because of the above factors and circumstances, sources of evidence cannot be adequately challenged, conclusions as to the reliability of the evidence produced by technology are a pretence, and a justice system that produces fair and adequate legal proceedings is an illusion.

Protecting privileged communications and data from disclosure is paramount for legal teams. Unrestricted legal advice, such as attorney-client communications or litigation strategy. are vital to the legal process and are exempt from disclosure in litigations or regulatory events. To protect this information from being disclosed, companies and outside counsel must review vast amounts of documents to determine those that contain privileged material. This process is extremely costly and time consuming. As data volumes increase, legal counsel employ methods to reduce the number of documents requiring review while balancing the need to ensure the protection of privileged information. Keyword searching is relied upon as a method to target privileged information and reduce document review populations. Keyword searches are effective at casting a wide net but return over inclusive results -- most of which do not contain privileged information -- and without detailed knowledge of the data, keyword lists cannot be crafted to find all privilege material. Overly-inclusive keyword searching can also be problematic, because even while it drives up costs, it also can cast `too far of a net' and thus produce unreliable results.To overcome these weaknesses of keyword searching, legal teams are using a new method to target privileged information called predictive modeling. Predictive modeling can successfully identify privileged material but little research has been published to confirm its effectiveness when compared to keyword searching. This paper summarizes a study of the effectiveness of keyword searching and predictive modeling when applied to real-world data. With this study, this group of collaborators wanted to examine and understand the benefits and weaknesses of both approaches to legal teams with identifying privilege material in document populations., Comment: 2018 IEEE International Conference on Big Data (Big Data)

The objective of high-recall information retrieval (HRIR) is to identify substantially all information relevant to an information need, where the consequences of missing or untimely results may have serious legal, policy, health, social, safety, defence, or financial implications. To find acceptance in practice, HRIR technologies must be more effective---and must be shown to be more effective---than current practice, according to the legal, statutory, regulatory, ethical, or professional standards governing the application domain. Such domains include, but are not limited to, electronic discovery in legal proceedings; distinguishing between public and non-public records in the curation of government archives; systematic review for meta-analysis in evidence-based medicine; separating irregularities and intentional misstatements from unintentional errors in accounting restatements; performing "due diligence" in connection with pending mergers, acquisitions, and financing transactions; and surveillance and compliance activities involving massive datasets. HRIR differs from ad hoc information retrieval where the objective is to identify the best, rather than all relevant information, and from classification or categorization where the objective is to separate relevant from non-relevant information based on previously labeled training examples. HRIR is further differentiated from established information retrieval applications by the need to quantify "substantially all relevant information"; an objective for which existing evaluation strategies and measures, such as precision and recall, are not particularly well suited.

Electronic evidence was introduced in the Bulgarian legislation for the first time during the period 2016-2017. In this article Alexandra Tsvetkova presents these recent developments in Bulgaria and focuses on the specific organizational, technological and legal requirements for handling and storing electronic evidence and evidentiary means. The article further explores the implementation levels of these requirements and gives recommendations with respect to identified gaps and needs. Alexandra Tsvetkova is an expert in IT and legal issues related to new technologies and director of LIBRe Foundation, Bulgaria. Since 2008, her practice is focused on the legal aspects in the use of ICT in the work of the government and the judiciary and a number of strategic and legislative initiatives have been implemented with her participation Index words: Evidence law, civil procedure, Electronic evidence law and legislation, Electronic discovery, Electronic records, Bulgaria, European Union

The rise and development of digital technology has profound effect on legal concepts and rules in many legal systems. In the field of evidence, the widespread use of modern technologies in our daily lives has created and generated materials that are considered evidence in courts. As a result, the outcome of civil and criminal trials increasingly hinges around the production of digital evidence in legal proceedings. This article casts light on the standards of admission and authentication of electronic evidence in courts under the new Zanzibar Evidence Act 2016, which came into force on 18 January 2017. Index words: Evidence law, civil procedure, Electronic evidence law and legislation, Electronic discovery, Electronic records, Zanzibar