Countering the 'Plagiarism Slot Machine': Protecting Creators and Businesses from AI Copyright Infringement

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Bibliographic Details
Title: Countering the 'Plagiarism Slot Machine': Protecting Creators and Businesses from AI Copyright Infringement
Language: English
Authors: Christine Ladwig, Dana Schwieger, Reshmi Mitra
Source: Information Systems Education Journal. 2025 23(5):53-61.
Availability: Information Systems and Computing Academic Professionals. Box 488, Wrightsville Beach, NC 28480. e-mail: publisher@isedj.org; Web site: http://isedj.org
Peer Reviewed: Y
Page Count: 9
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Copyrights, Plagiarism, Intellectual Property, Computer Software, Computer Science Education, Artificial Intelligence, Programming, Meta Analysis, Laws, Court Litigation, Periodicals, Journalism, Music, Artists, Musicians, Photography, Legal Problems, Art, Teaching Methods
ISSN: 1545-679X
Abstract: The rapid rise of AI use is creating some very serious legal and ethical issues such as bias, discrimination, inequity, privacy violations, and--as creators everywhere fear--theft of protected intellectual property. Because AI platforms "learn" by scraping training materials available online or what is provided to them through their human programmers, these systems can easily capture copyrighted expressions, such as song lyrics, computer code, stories, or images, and use them to generate new works without attribution. This rise in AI use of protected material is spawning an array of legal actions as artists, programmers, writers, photographers and other creative individuals witness the erosion of their value in the marketplace and the world. As students prepare to enter the field, they need to be aware of legal issues and concerns that they may face and methods for addressing them. This case focuses on the problem of AI copyright infringement of art and includes an exploratory exercise that introduces students to the act of "scraping"--a primary AI training method by which copyrighted works may be vulnerable to potential infringement.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1471463
Database: ERIC
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