Artificial Intelligence: Application Today and Implications Tomorrow

This paper analyzes the applications of artificial intelligence to the legal industry, specifically in the fields of legal research and contract drafting. First, it will look at the implications of artificial intelligence (A.I.) for the current practice of law. Second, it will delve into the future implications of A.I. on law firms and the possible regulatory challenges that come with A.I. The proliferation of A.I. in the legal sphere will give laymen (clients) access to the information and services traditionally provided exclusively by attorneys. With an increase in access to these services will come a change in the role that lawyers must play. A.I. is a tool that will increase access to cheaper and more efficient services, but non-lawyers lack the training to analyze and understand information it puts out. The role of lawyers will change to fill this role, namely utilizing these tools to create a better work product with greater efficiency for their clients

Artificial Intelligence: Application Today and Implications Tomorrow

This paper analyzes the applications of artificial intelligence to the legal industry, specifically in the fields of legal research and contract drafting. First, it will look at the implications of artificial intelligence (A.I.) for the current practice of law. Second, it will delve into the future implications of A.I. on law firms and the possible regulatory challenges that come with A.I. The proliferation of A.I. in the legal sphere will give laymen (clients) access to the information and services traditionally provided exclusively by attorneys. With an increase in access to these services will come a change in the role that lawyers must play. A.I. is a tool that will increase access to cheaper and more efficient services, but non-lawyers lack the training to analyze and understand information it puts out. The role of lawyers will change to fill this role, namely utilizing these tools to create a better work product with greater efficiency for their clients

Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective

Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as ‘A.I. neuroprediction,’ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed

O.R.,Statistics,A.I.- the potential for interdisciplinary progress

This paper examines the need for O.R. workers to become more involved in the development of A.I. A brief outline of A.I. is provided noting problems, techniques and objectives similar to those found in O.R. This outline gives an indication of how interdisciplinary development might proceed and indicates the direction in which O.R. training should be progressin

VELOS : a VR platform for ship-evacuation analysis

Virtual Environment for Life On Ships (VELOS) is a multi-user Virtual Reality (VR) system that aims to support designers to assess (early in the design process) passenger and crew activities on a ship for both normal and hectic conditions of operations and to improve ship design accordingly. This article focuses on presenting the novel features of VELOS related to both its VR and evacuation-specific functionalities. These features include: (i) capability of multiple users’ immersion and active participation in the evacuation process, (ii) real-time interactivity and capability for making on-the-fly alterations of environment events and crowd-behavior parameters, (iii) capability of agents and avatars to move continuously on decks, (iv) integrated framework for both the simplified and advanced method of analysis according to the IMO/MSC 1033 Circular, (v) enrichment of the ship geometrical model with a topological model suitable for evacuation analysis, (vi) efficient interfaces for the dynamic specification and handling of the required heterogeneous input data, and (vii) post-processing of the calculated agent trajectories for extracting useful information for the evacuation process. VELOS evacuation functionality is illustrated using three evacuation test cases for a ro–ro passenger ship

Human factors in space telepresence

The problems of interfacing a human with a teleoperation system, for work in space are discussed. Much of the information presented here is the result of experience gained by the M.I.T. Space Systems Laboratory during the past two years of work on the ARAMIS (Automation, Robotics, and Machine Intelligence Systems) project. Many factors impact the design of the man-machine interface for a teleoperator. The effects of each are described in turn. An annotated bibliography gives the key references that were used. No conclusions are presented as a best design, since much depends on the particular application desired, and the relevant technology is swiftly changing

The management of intelligence-assisted finite element analysis technology

Artificial Intelligence (AI) approaches to Finite Element Analysis (FEA), have had tentative degrees of success over the last few years and some authors have argued that effective FEA can help in the manufacture reliability and safety aspects of engineered artefacts. The author of this paper reviews how such AI techniques have been applied and in this light, the author then uses a Fuzzy Cognitive Mapping (FCM), to develop a framework for the management of intelligence-assisted FEA

On certain non-unique solutions of the Stieltjes moment problem

We construct explicit solutions of a number of Stieltjes moment problems based on moments of the form (2rn)! and [(rn)!]2. It is shown using criteria for uniqueness and non-uniqueness (Carleman, Krein, Berg, Pakes, Stoyanov) that for r > 1 both forms give rise to non-unique solutions. Examples of such solutions are constructed using the technique of the inverse Mellin transform supplemented by a Mellin convolution. We outline a general method of generating non-unique solutions for moment problems