Artificial Intelligence, Copyright, and the Doctrine of Fair Use

White, Enid

doi:10.21949/1531004

i

Artificial Intelligence, Copyright, and the Doctrine of Fair Use

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2024-04-11
By White, Enid

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English

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Creators:

White, Enid
Corporate Creators:

Wyoming. Department of Transportation. Research Center
Corporate Contributors:

American Association of State Highway and Transportation Officials (AASHTO) ; National Transportation Knowledge Network (NTKN) (U.S.)
Subject/TRT Terms:

Artificial Intelligence Copyright Data Mining Data Quality Doctrine Of Fair Use Information Management Intellectual Property Laws And Legislation Legal Rights Licensing Machine Learning
DOI:

https://doi.org/10.21949/1531004
Resource Type:

Presentations
Geographical Coverage:

United States
Corporate Publisher:

United States. Department of Transportation. National Transportation Library
Abstract:

Wyoming Department of Transportation Research Manager Enid White’s presentation covers copyright issues related to artificial intelligence (AI). There are differing perspectives as well as many lawsuits underway in this area of copyright law. Generative AI companies and Large Language Models mine data from the internet to train AI. Authors, researchers, and other creators want credit and compensation for their original works when used to train AI. While some AI companies obtain consent when they use data scraping tools, others do not, claiming that the use of AI does not trigger the rights protected by the Copyright Act and if it did it would fall under the Doctrine of Fair Use. White provides an overview of Fair Use, Copyright, text and data mining, and responses from the U.S. Government and AI companies pertaining to intellectual property.
Content Notes:

Recording length: 1h 00m 32s
Format:

MPEG
Collection(s):

Transportation Librarians Roundtable
Main Document Checksum:

urn:sha-512:54f31f2bbb2a80c8ba068b63217a26b5dde9fec795c45d6f2bb120f3c9eaded1073d1ccca24e40fa796c6c207dc7be99e990af974aa779444712acf54767031e
Download URL:

https://rosap.ntl.bts.gov/view/dot/74563/dot_74563_DS1.mp4
File Type:

[MP4 - 469.40 MB ]

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File Language:

English

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