CAREER: Large-Scale Exploration and Interpretation of Consumer-Oriented Legal Documents
职业:面向消费者的法律文件的大规模探索和解读
基本信息
- 批准号:2237574
- 负责人:
- 金额:$ 55.64万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-08-01 至 2028-07-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
People face large volumes of text in their everyday lives, and they must choose what to read and what to leave unread. To function in our information society, consumers must read and accept terms of service agreements, financial agreements, health care agreements, rental agreements, privacy policies, and other varieties of "fine print" to receive essential goods and services. These consumer-oriented legal documents (COLDs, for brevity) specify requirements, penalties, boundaries of acceptable use, options for recourse if something goes wrong, privacy practices, intellectual property stipulations, and many other important topics. People tend to accept COLDs without reading or understanding them, and the lack of understanding disempowers individuals and affects them unequally. This project will answer three related questions: (1) What recurring information structures and types of knowledge exist in COLDs?; (2) What are the capabilities and limitations of text mining applied to automating extraction of information from COLDs?; and (3) To what extent do the contents of COLDs intersect with the interests and needs of consumers? Toward answering these questions, the project will develop natural language processing methods that support user engagement with typically unengaging but important text. Additionally, this project will introduce first-year undergraduates to research and encourage them to pursue STEM careers.The project will advance knowledge by focusing on the following goals. First, the project will discover the availability and characteristics of common types of COLDs by creating large-scale corpora of them from online sources. These corpora will enable studying issues in availability, accessibility, navigation, and readability. Second, the project will develop methods for automated extraction of two particularly salient features of COLD text: choice points (statements in text that describe actions a reader can take potentially for their benefit) and outlier statements (statements that deviate from what is typical for the relevant type of COLD, differentiating a COLD from its peers and motivating acute attention). Third, the project will build browser extensions to explore how choice points and outlier statements affect people's engagement with COLDs' contents. To support further research, the project also will produce and disseminate an array of corpora, language models, and other tools for researchers in natural language processing and public policy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
人们在日常生活中面对大量的文本,他们必须选择读什么和不读什么。为了在我们的信息社会中发挥作用,消费者必须阅读并接受服务协议、财务协议、医疗保健协议、租赁协议、隐私政策和其他各种“细则”的条款,以获得基本的商品和服务。这些面向消费者的法律的文档(COLD,为简洁起见)指定了要求、处罚、可接受使用的界限、出错时的追索权、隐私惯例、知识产权规定以及许多其他重要主题。人们倾向于在没有阅读或理解它们的情况下接受寒冷,缺乏理解会使个人失去能力,并对他们产生不平等的影响。本研究将回答三个相关的问题:(1)在COLD中存在什么样的重复信息结构和知识类型?(2)文本挖掘应用于从COLD自动提取信息的能力和局限性是什么?(3)消费者权益保护令的内容与消费者的利益和需要有多大程度的交叉?为了回答这些问题,该项目将开发自然语言处理方法,支持用户参与通常不吸引人但重要的文本。此外,该项目将引入一年级本科生进行研究,并鼓励他们从事STEM职业。该项目将通过关注以下目标来推进知识。首先,该项目将通过从在线资源创建大规模语料库来发现常见类型COLD的可用性和特征。这些语料库将使研究的可用性,可访问性,导航和可读性的问题。其次,该项目将开发自动提取COLD文本两个特别突出的特征的方法:选择点(文本中描述读者可能为其利益采取的行动的陈述)和离群值陈述(偏离相关类型COLD的典型陈述,将COLD与其同行区分开来并激发敏锐的注意力)。第三,该项目将构建浏览器扩展,以探索选择点和离群值语句如何影响人们对COLD内容的参与。为了支持进一步的研究,该项目还将为自然语言处理和公共政策领域的研究人员制作和传播一系列语料库、语言模型和其他工具。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)
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Shomir Wilson其他文献
Creation and Analysis of an International Corpus of Privacy Laws
国际隐私法语料库的创建和分析
- DOI:
10.48550/arxiv.2206.14169 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Sonu Gupta;Ellen Poplavska;Nora O'Toole;Siddhant Arora;Thomas B. Norton;N. Sadeh;Shomir Wilson - 通讯作者:
Shomir Wilson
This Table is Different: A WordNet-Based Approach to Identifying References to Document Entities
该表有所不同:基于 WordNet 的方法来识别对文档实体的引用
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Shomir Wilson;A. Black;J. Oberlander - 通讯作者:
J. Oberlander
The Role of Metacognition in Robust AI Systems
元认知在鲁棒人工智能系统中的作用
- DOI:
- 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
M. Schmill;T. Oates;Michael L. Anderson;D. Josyula;D. Perlis;Shomir Wilson;Scott Fults - 通讯作者:
Scott Fults
Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles
揭露国籍偏见:人工智能生成文章中人类对国籍的认知研究
- DOI:
10.1145/3600211.3604667 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Pranav Narayanan Venkit;Sanjana Gautam;Ruchi Panchanadikar;Tingting Huang;Shomir Wilson - 通讯作者:
Shomir Wilson
Privacy Lost and Found: An Investigation at Scale of Web Privacy Policy Availability
隐私失而复得:网络隐私政策可用性的大规模调查
- DOI:
10.1145/3573128.3604902 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Mukund Srinath;S. Sundareswara;Pranav Narayanan Venkit;C. Giles;Shomir Wilson - 通讯作者:
Shomir Wilson
Shomir Wilson的其他文献
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{{ truncateString('Shomir Wilson', 18)}}的其他基金
Collaborative Research: SaTC: CORE: Medium: A Large-Scale, Longitudinal Resource to Advance Technical and Legal Understanding of Textual Privacy Information
协作研究:SaTC:核心:中:促进对文本隐私信息的技术和法律理解的大规模纵向资源
- 批准号:
2105736 - 财政年份:2021
- 资助金额:
$ 55.64万 - 项目类别:
Standard Grant
SaTC: CORE: Medium: Collaborative: Automatically Answering People's Privacy Questions
SaTC:核心:媒介:协作:自动回答人们的隐私问题
- 批准号:
1914444 - 财政年份:2019
- 资助金额:
$ 55.64万 - 项目类别:
Standard Grant
IRFP: Metalanguage Identification for Interactive Language Technologies
IRFP:交互式语言技术的元语言识别
- 批准号:
1159236 - 财政年份:2013
- 资助金额:
$ 55.64万 - 项目类别:
Fellowship Award
EAPSI: Parsing Metalanguage and the Use-Mention Distinction
EAPSI:解析元语言和使用提及的区别
- 批准号:
1015666 - 财政年份:2010
- 资助金额:
$ 55.64万 - 项目类别:
Fellowship Award
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