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Questions about authorship and originality have become urgent in an era where artificial intelligence (AI) and Large Language Models can write essays, generate images, and mimic human creativity. This authoritative book explores the intersection between plagiarism and forms of artificial intelligence that can generate written content copied from human-written texts.
This works discusses the legal and ethical history of plagiarism and shows how the rise of AI is changing how scholars define and measure plagiarism. The book also explores how AI could be used to discover plagiarism and highlights the risks of using AI when working with data and images.
Written by an established thinker on the topic of AI and plagiarism, Plagiarism and Artificial Intelligence will help librarians and researchers to understand the relationship between AI and plagiarism as well as those who seek solutions to the problems caused by using artificial intelligence systems.
Michael Seadle has been a Professor at the Berlin School of Library and Information Science at Humboldt-Universität zu Berlin, was Dean of Humanities, and was Executive Director of the international iSchools organisation. His most recent publication is Information Science: History, Ideas and Applications. He has previously published The Measurement of Information Integrity, Quantifying Research Integrity and Educating the Profession: 40 Years of the IFLA Section on Education and Training.
Introduction: Understanding Plagiarism in the Era of Artificial Intelligence
Chapter 1: Context
Chapter 2: Training
Chapter 3: Risks
Chapter 4: Scholarly Purposes
Chapter 5: Reference Assistance
Chapter 6: What is Plagiarism?
Chapter 7: Detecting Plagiarism
Chapter 8: Measuring Plagiarism
Chapter 9: Avoiding Plagiarism with an LLM
Chapter 10: AI and Plagiarism Case Studies
Chapter 11: Tools for Detecting Plagiarism
Chapter 12: Embedded AI
Chapter 13: AI’s Effect on Trust
Chapter 14: Data Falsification
Chapter 15: Image and Sound Falsification
Conclusion