Disclosing Machine Inputs and Outputs: The Vulnerability of Legal Technology in Civil Discovery

Smart technology has begun to infiltrate nearly every corner of society. While the legal profession managed to resist this intrusion relative to other industries for many years, it is now undeniable that machines frequently supplement lawyers and civil procedures such as discovery will need to adapt. As litigants, usually the well-resourced ones, increasingly utilize machine intelligence, concerns about accuracy and unfair advantage have sprung up on the other side of technology use. Information asymmetry is exacerbated when technology is accessible to only one party, and, consequently, curious litigants may seek discovery about the technology’s implementation in the context of the dispute. Thus, as law firms and corporate legal departments consider whether and how to integrate emerging technologies into their operations, it will be important to know their exposure to litigation. This paper provides suggestions for whether, and to what extent, parties should be able to obtain discovery about an opponent’s tools, including their machine inputs and outputs. After reviewing the discovery process broadly, this paper will walk through three of the most common and relevant technologies, including technology-assisted review in discovery productions, predictive analytics for forecasting outcomes, and document generation for creating legal documents. If a party demands to see the details behind the use of one of these technologies, should the court compel production? This paper offers several considerations for judges in exercising their discretion to answer this question

Key scientific issues relevant to the identification and characterisation of endocrine disrupting substances - Report of the Endocrine Disrupters Expert Advisory Group

The European Commission, under Directorate-General for Environment (DG ENV) as file leader of the Community Strategy on Endocrine Disrupters, In 2010, DG ENV created an ad hoc group of Commission Services and Member States on the EU Community Strategy on Endocrine Disrupters. The ad hoc group created the Endocrine Disrupters Expert Advisory Group (ED EAG) in November 2011 to provide scientific advice on the development of criteria for identification of EDs. The European Commission's Joint Research Centre was tasked with running the expert sub-group, consisting of around 40 experts nominated by Member State regulatory authorities, relevant industry associations and non-governmental consumer/environmental protection organisations. This report captures the experts' opinions on key scientific issues relevant to the identification and characterisation of endocrine disrupting substances (EDs). It provides one input to the Commission’s decisions on the establishment of horizontal criteria for the identification of EDs to be applied as appropriate across all relevant pieces of legislation concerning the control and risk management of chemicals substances (including pesticides, biocides, pharmaceuticals, industrial chemicals, controls on water quality, occupational exposure, etc).JRC.I.5-Systems Toxicolog

Applications of satellite and marine geodesy to operations in the ocean environment

The requirements for marine and satellite geodesy technology are assessed with emphasis on the development of marine geodesy. Various programs and missions for identification of the satellite geodesy technology applicable to marine geodesy are analyzed along with national and international marine programs to identify the roles of satellite/marine geodesy techniques for meeting the objectives of the programs and other objectives of national interest effectively. The case for marine geodesy is developed based on the extraction of requirements documented by authoritative technical industrial people, professional geodesists, government agency personnel, and applicable technology reports

Road User Charging – Pricing Structures.

This project considers the extent to which the public could cope with complex price or tariff structures such as those that might be considered in the context of a national congestion pricing scheme. The key elements of the brief were: • to review existing studies of road pricing schemes to assess what information and evidence already exists on the key issues; • to identify what can be learned about pricing structures from other transport modes and other industries and in particular what issues and conclusions might be transferable; • to improve the general understanding of the relationship between information and people’s ability to respond; and • to recommend what further research would be most valuable to fill evidence gaps and enable conclusions to be drawn about an effective structure

Armatures For Success: Advancing Racial Equity For Funeral Service Technology Students

The purpose of this descriptive, exploratory action research study, using both qualitative and quantitative methods, was to identify students at risk of failure on a post-graduate licensure exam and to develop and implement improvement models to improve exam performance. The participants were alumni of the funeral service technology program at Northwest Mississippi Community College. African American graduates of this vocational course failed at increasingly disparate rates above Caucasian graduates in the national board licensing examination, despite commensurate post-secondary scholastic achievement. The quantitative research portion of the study statistically analyzed student performance measures in funeral service classes to reveal areas of dissimilar performance divided by race. The focus of the qualitative research portion of the study included interviewing program graduates to reveal perceptions of former students, surveying course documents, and examining learning spaces, utilizing a contextual framework of critical race theory and culturally relevant pedagogy (Bell, 2002; Ladson-Billings, 1996). To improve learning outcomes, as information was gathered, practical techniques were garnered to improve learning outcomes and enhance favorable student results on the final standardized test

Meeting on BOBLME engagement in the International Indian Ocean Expedition 50th anniversary initiative (IIOE-2), Bangkok, Thailand, 17-18 March, 2015

Objectives included; a contribution to understanding large-scale processes affecting the Bay of Bengal Large Marine Ecosystem Project (BOBLME) and it's living resources; and to align with International Indian Ocean Expedition (IIOE-2) (2015-2020) which will extensively explore and study the Indian Ocean to improve understanding of the ocean and coupled climate processes

Detecting, Modeling, and Predicting User Temporal Intention

The content of social media has grown exponentially in the recent years and its role has evolved from narrating life events to actually shaping them. Unfortunately, content posted and shared in social networks is vulnerable and prone to loss or change, rendering the context associated with it (a tweet, post, status, or others) meaningless. There is an inherent value in maintaining the consistency of such social records as in some cases they take over the task of being the first draft of history as collections of these social posts narrate the pulse of the street during historic events, protest, riots, elections, war, disasters, and others as shown in this work. The user sharing the resource has an implicit temporal intent: either the state of the resource at the time of sharing, or the current state of the resource at the time of the reader \clicking . In this research, we propose a model to detect and predict the user\u27s temporal intention of the author upon sharing content in the social network and of the reader upon resolving this content. To build this model, we first examine the three aspects of the problem: the resource, time, and the user. For the resource we start by analyzing the content on the live web and its persistence. We noticed that a portion of the resources shared in social media disappear, and with further analysis we unraveled a relationship between this disappearance and time. We lose around 11% of the resources after one year of sharing and a steady 7% every following year. With this, we turn to the public archives and our analysis reveals that not all posted resources are archived and even they were an average 8% per year disappears from the archives and in some cases the archived content is heavily damaged. These observations prove that in regards to archives resources are not well-enough populated to consistently and reliably reconstruct the missing resource as it existed at the time of sharing. To analyze the concept of time we devised several experiments to estimate the creation date of the shared resources. We developed Carbon Date, a tool which successfully estimated the correct creation dates for 76% of the test sets. Since the resources\u27 creation we wanted to measure if and how they change with time. We conducted a longitudinal study on a data set of very recently-published tweet-resource pairs and recording observations hourly. We found that after just one hour, ~4% of the resources have changed by ≥30% while after a day the change rate slowed to be ~12% of the resources changed by ≥40%. In regards to the third and final component of the problem we conducted user behavioral analysis experiments and built a data set of 1,124 instances manually assigned by test subjects. Temporal intention proved to be a difficult concept for average users to understand. We developed our Temporal Intention Relevancy Model (TIRM) to transform the highly subjective temporal intention problem into the more easily understood idea of relevancy between a tweet and the resource it links to, and change of the resource through time. On our collected data set TIRM produced a significant 90.27% success rate. Furthermore, we extended TIRM and used it to build a time-based model to predict temporal intention change or steadiness at the time of posting with 77% accuracy. We built a service API around this model to provide predictions and a few prototypes. Future tools could implement TIRM to assist users in pushing copies of shared resources into public web archives to ensure the integrity of the historical record. Additional tools could be used to assist the mining of the existing social media corpus by derefrencing the intended version of the shared resource based on the intention strength and the time between the tweeting and mining