Language model AI and international commercial arbitration

This thesis dives deep into the world of a specific type of artificial intelligence (AI), Large Language Models (LLMs), and how they might impact international business disputes, or more specifically, international commercial arbitration. In an age where rapid advancement in technology is quickly reshaping our world, the legal field isn't immune to this transformation. Among the game-changers, language model AI could, due to its promising capacity of data-processing and outcome prediction, potentially make international arbitration quicker and less expensive, thereby providing easier access to justice for the commercial sector across the globe. However, it's not all smooth sailing. The study also identifies legal limitations regarding the use of LLMs in arbitration - issues related to bias, maintaining fair processes, keeping data private, and determining who is accountable when AI is involved. Overcoming these obstacles is crucial before AI can be confidently incorporated into arbitration. While LLMs hold exciting potential for international commercial arbitration, careful implementation is important. We need comprehensive rules and guidelines to ensure language model AI operates effectively and ethically in this arena. The use of AI should be a considered decision, keeping in mind the potential hurdles and working towards mitigating them.This thesis dives deep into the world of a specific type of artificial intelligence (AI), Large Language Models (LLMs), and how they might impact international business disputes, or more specifically, international commercial arbitration. In an age where rapid advancement in technology is quickly reshaping our world, the legal field isn't immune to this transformation. Among the game-changers, language model AI could, due to its promising capacity of data-processing and outcome prediction, potentially make international arbitration quicker and less expensive, thereby providing easier access to justice for the commercial sector across the globe. However, it's not all smooth sailing. The study also identifies legal limitations regarding the use of LLMs in arbitration - issues related to bias, maintaining fair processes, keeping data private, and determining who is accountable when AI is involved. Overcoming these obstacles is crucial before AI can be confidently incorporated into arbitration. While LLMs hold exciting potential for international commercial arbitration, careful implementation is important. We need comprehensive rules and guidelines to ensure language model AI operates effectively and ethically in this arena. The use of AI should be a considered decision, keeping in mind the potential hurdles and working towards mitigating them

The impact of text presentation on translator performance

Widely used computer-aided translation (CAT) tools divide documents into segments, such as sentences, and arrange them side-by-side in a spreadsheet-like view. We present the first controlled evaluation of these design choices on translator performance, measuring speed and accuracy in three experimental text-processing tasks. We find significant evidence that sentence-by-sentence presentation enables faster text reproduction and within-sentence error identification compared to unsegmented text, and that a top-and-bottom arrangement of source and target sentences enables faster text reproduction compared to a side-by-side arrangement. For revision, on the other hand, we find that presenting unsegmented text results in the highest accuracy and time efficiency. Our findings have direct implications for best practices in designing CAT tools

Working Papers as Federal Records: The Need for New Legislation to Preserve the History of National Policy

This article deals with policy records at the front end of their lives; that is, preserving them from destruction by federal agencies in the decades immediately after their creation. It does not deal with the destruction of archived documents by Archives officials themselves. It discusses only in passing the related question of how long a policy record should be sealed off from public inspection; the literature includes a variety of opinions on that subject. The author is content to leave to others the problem of just where to draw the balance between making historical documentation available soon enough so that it can offer relevant lessons to citizens, but not so soon as to discourage officials from putting their candid thoughts and recommendations on paper or disk, for fear of public exposure and pressure. He focuses, instead, on the preservation of governmental records, and particularly of drafts, comments, and other working papers. Of course the issues of preservation and access are intimately linked: if records are routinely destroyed as soon as they are no longer needed by their creators, public access-even much delayed public access-becomes altogether impossible

Undergraduate Student Catalog 2011-2012

The contents of this document highlight the central pillars of Qatar University’s mission, namely the provision of high-quality education and the pursuit of an active role in the development of Qatari society. The courses described here have been designed, reviewed and assessed to meet the highest educational standards, with a strong focus on the knowledge- and skill-bases needed for a graduate to be competitive in today’s labor market or in higher education pursuits

Where's the Liability in Harmful AI Speech?

Generative AI, in particular text-based "foundation models" (large models trained on a huge variety of information including the internet), can generate speech that could be problematic under a wide range of liability regimes. Machine learning practitioners regularly "red team" models to identify and mitigate such problematic speech: from "hallucinations" falsely accusing people of serious misconduct to recipes for constructing an atomic bomb. A key question is whether these red-teamed behaviors actually present any liability risk for model creators and deployers under U.S. law, incentivizing investments in safety mechanisms. We examine three liability regimes, tying them to common examples of red-teamed model behaviors: defamation, speech integral to criminal conduct, and wrongful death. We find that any Section 230 immunity analysis or downstream liability analysis is intimately wrapped up in the technical details of algorithm design. And there are many roadblocks to truly finding models (and their associated parties) liable for generated speech. We argue that AI should not be categorically immune from liability in these scenarios and that as courts grapple with the already fine-grained complexities of platform algorithms, the technical details of generative AI loom above with thornier questions. Courts and policymakers should think carefully about what technical design incentives they create as they evaluate these issues.Comment: Published in the Journal of Free Speech Law (2023

Undergraduate and Graduate Course Descriptions, 2007 Fall

Wright State University undergraduate and graduate course descriptions from Fall 2007

Undergraduate Student Catalog 2012-2013

The contents of this document highlight the central pillars of Qatar University’s mission, namely the provision of high-quality education and the pursuit of an active role in the development of Qatari society. The courses described here have been designed, reviewed and assessed to meet the highest educational standards, with a strong focus on the knowledge- and skill-bases needed for a graduate to be competitive in today’s labor market or in higher education pursuits

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management