scholarly journals Peer Review #1 of "Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective (v0.2)"

2016 ◽  
Keyword(s):  
Human Rights ◽  
Natural Language Processing ◽  
Natural Language ◽  
Peer Review ◽  
Language Processing ◽  
Judicial Decisions ◽  
European Court

scholarly journals Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective

2016 ◽  
Vol 2 ◽  
pp. e93 ◽  
Author(s):  
Nikolaos Aletras ◽  
Dimitrios Tsarapatsanis ◽  
Daniel Preoţiuc-Pietro ◽  
Vasileios Lampos
Keyword(s):  
Human Rights ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Binary Classification ◽  
Classification Task ◽  
Judicial Decision Making ◽  
Judicial Decisions ◽  
European Court ◽  
Textual Content

Recent advances in Natural Language Processing and Machine Learning provide us with the tools to build predictive models that can be used to unveil patterns driving judicial decisions. This can be useful, for both lawyers and judges, as an assisting tool to rapidly identify cases and extract patterns which lead to certain decisions. This paper presents the first systematic study on predicting the outcome of cases tried by the European Court of Human Rights based solely on textual content. We formulate a binary classification task where the input of our classifiers is the textual content extracted from a case and the target output is the actual judgment as to whether there has been a violation of an article of the convention of human rights. Textual information is represented using contiguous word sequences, i.e., N-grams, and topics. Our models can predict the court’s decisions with a strong accuracy (79% on average). Our empirical analysis indicates that the formal facts of a case are the most important predictive factor. This is consistent with the theory of legal realism suggesting that judicial decision-making is significantly affected by the stimulus of the facts. We also observe that the topical content of a case is another important feature in this classification task and explore this relationship further by conducting a qualitative analysis.

A Matter of Perspective

2020 ◽  
pp. 182-202
Author(s):  
Katie Miller
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Human Rights ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Equal Opportunity ◽  
Facial Recognition ◽  
Phone Service

The challenge presented is an age when some decisions are made by humans, some are made by AI, and some are made by a combination of AI and humans. For the person refused housing, a phone service, or employment, the experience is the same, but the ability to understand what has happened and obtain a remedy may be very different if the discrimination is attributable to or contributed by an AI system. If we are to preserve the policy intentions of our discrimination, equal opportunity, and human rights laws, we need to understand how discrimination arises in AI systems; how design in AI systems can mitigate such discrimination; and whether our existing laws are adequate to address discrimination in AI. This chapter endeavours to provide this understanding. In doing so, it focuses on narrow but advanced forms of artificial intelligence, such as natural language processing, facial recognition, and cognitive neural networks.

scholarly journals Distributed peer review enhanced with natural language processing and machine learning

2020 ◽  
Vol 4 (7) ◽  
pp. 711-717 ◽  
Author(s):  
Wolfgang E. Kerzendorf ◽  
Ferdinando Patat ◽  
Dominic Bordelon ◽  
Glenn van de Ven ◽  
Tyler A. Pritchard
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Natural Language ◽  
Peer Review ◽  
Language Processing

scholarly journals The Potential of an Artificial Intelligence for Disability Advocacy: The WikiDisability Project

2021 ◽  
Author(s):  
Rachel Gorman ◽  
Pierre Maret ◽  
Alexandra Creighton ◽  
Bushra Kundi ◽  
Fabrice Muhlenbach ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
Natural Language Processing ◽  
Natural Language ◽  
Search Engine ◽  
Language Processing ◽  
People With Disabilities ◽  
Advocacy Groups ◽  
Related Data

Human rights monitoring for people with disabilities is in urgent need for disability data that is shared and available for local and international disability stakeholders (e.g., advocacy groups). Our aim is to use a Wikibase for editing, integrating, storing structured disability related data and to develop a Natural Language Processing (NLP) enabled multilingual search engine to tap into the wikibase data. In this paper, we explain the project first phase.

Sign in / Sign up

Export Citation Format

Share Document