Generative Artificial Intelligence and Copyright Law. By Christopher T. Zirpoli. Publication Date: 05-11-2023
An instructive Legal Sidebar in The Congressional Research Service lays out emerging challenges in the copyright protection of materials involving generative AI.
Guidelines/Policies
"Using an A.I. program is not 'plagiarism' in the traditional sense—there’s no previous work for the student to copy, and thus no original for teachers’ plagiarism detectors to catch."
Clear guidelines on the use of generative AI is a necessary first step in laying ethical policies for what constitutes plagiarism. Violations of Stonehill’s Academic Integrity Policy cannot be gauged if there is no clarity on what constitutes that violation.
Given the inexorable expansion and scope of generative AI capabilities and accessibility, both institutional and course-specific guidance in the use and acknowledgement of AI tools would need to be formalized.
The policy wheel need not be recreated from scratch. Guidelines and policy examples of AI use have mushroomed at a dizzying rate across the nation, fueled by both fear of academic dishonesty and the very real excitement of a powerful new technology that could enhance the academic research process.
Syllabi Policies for AI Generative Tools - curated by Lance Eaton
Using Generative AI in Coursework - Boston University, Computing & Data Sciences
Generative AI Policy for Students - University of Notre Dame
The ability to spread mis- and disinformation is relatively easy with generative AI. Images, videos, text, audio content can be realistically altered so that they appear wholly authentic. That is a problem!
The constant need to identify and verify sources of information has to become part of information culture. Cross-checking content from a wide range of trusted sources is one way. Counter-tools like reverse searches can aid in verifying the origin of images.
Given that fire fights fire, it is tempting to assume that AI-generated text can be detected by AI. Resist the temptation!
While AI detectors have proliferated alongside the increasing use of generative AI, as can be seen in some of the selections below, detection of AI could be gravely counterproductive.
AI detectors are notoriously fallible and prone to a slew of false positives. It has led faculty into false accusations against students, with the concomitant potential for lawsuits such as that faced by Adelphi University.
The AI classifier, for example, was discontinued by OpenAI, in less than six months due to "its low rate of accuracy."
As with any emerging technology, it is entirely possible that levels of efficacy will improve in the future. For now, however, proactively establishing course guidelines on the use of AI, transparency in its usage, and AI-resistant assessments of student comprehension are undeniably preferable to relying on the capriciousness of fledgling and commercialized detection systems.
When in doubt, take advantage of the assistance provided by Ed Tech Consultants at Stonehill's Department of Information Technology.
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