US EditionCanada, other countries struggling to come up with new rules for AI and copyright
29 Articles
29 Articles
A step forward in tracing and documenting dataset provenance
Training data are crucial for advancements in artificial intelligence, but many questions remain regarding the provenance of training datasets, license enforcement and creator consent. Mahari et al. provide a set of tools for tracing, documenting and sharing AI training data and highlight the importance for developers to engage with metadata of datasets.
IP Lawyer Breaks Down Three Copyright Lawsuits Challenging AI’s Business Model
Artificial intelligence is quickly evolving, but copyright law is still playing catch-up. A lawyer breaks down three of the biggest cases to explain how the law is evolving with this technology. Photo illustration: Nayon Cho
'Early days' of establishing AI copyright rules confounding Canada and other countries
The battle between AI companies and copyright holders notched an early win for publishers in the U.S. in mid-February when a court ruled that a legal research firm didn't have the right to use a rival's content.
Canada, Other Countries Struggling to Come up With New Rules for AI and Copyright
The battle between AI companies and copyright holders notched an early win for publishers in the U.S. in mid-February when a court ruled that a legal research firm didn’t have the right to use a rival’s content. But even as the number of legal cases grows, a definite answer to the question of whether artificial intelligence companies can use copyrighted content to train their AI products is still a long way off. “We’ve been having this conversat…
Unite.AI
thedigitalinsider.comNearly 80% of Training Datasets May Be a Legal Hazard for Enterprise AI
A recent paper from LG AI Research suggests that supposedly ‘open' datasets used for training AI models may be offering a false sense of security – finding that nearly four out of five AI datasets labeled as ‘commercially usable' actually contain hidden legal risks. Such risks range from the inclusion of undisclosed copyrighted material to restrictive licensing terms buried deep in a dataset's dependencies. If the paper's findings are accurate, …
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