Nature Editorial: “AI Firms Must Play Fair When They Use Academic Data in Training”
From Nature:
Researchers are among those who feel uneasy about the unrestrained use of their intellectual property in training commercial large language models. Firms and regulators need to agree the rules of engagement.
… research should continue into whether there is a need for more-radical solutions, such as new kinds of licence or changes to copyright law. Generative AI tools are using a data ecosystem built by open-source movements, yet often ignore the accompanying expectations of reciprocity and reasonable use, says Sylvie Delacroix, a digital-law scholar at King’s College London. The tools also risk polluting the Internet with AI-generated content of dubious quality. By failing to redirect users to the human-made sources on which they were built, LLMs could disincentivize original creation. Without putting more power into the hands of creators, the system will come under severe strain. Regulators and companies must act.
Learn More, Read the Complete Editorial (about 1000 words)
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About Gary Price
Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com.