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Singapore Writers Push Back On LLM Training
The government of Singapore asked local writers if they would agree to have large language model AIs train on their works.
"No."
An email sent late in March said that the National Multimodal LLM Programme (NMLP) aimed to address the bias of existing LLMs that have “disproportionately large influences” from Western societies. Singapore’s own LLM, trained on material produced locally, would have more accurate references to the nation’s history, colloquialisms, and culture and train on widely spoken languages, such as Malay, Mandarin, and Tamil, it said.
However, writers such as Gwee Li Sui, one of the city’s best-known literary figures, are not convinced.
“The stages of planning [for the LLM] before writers are even considered as worth consulting do not inspire confidence that my interest will be a priority,” Gwee, author of more than a dozen books, told Rest of World. There is also little clarity on how the works would be protected from being used “for purposes other than what is now claimed as public service towards cultural representation,” he said.
(Via restofworld.org.)
Science fiction writers have long kept readers ahead of technology, even by generations. In his 1943 short story Q.U.R., Anthony Boucher describes how royalties should be paid to the subjects of machine learning:
When the Singaporean government asked local writers if they would agree to having their work used to train a large language model, it probably did not expect the country’s tiny literary community to react so fiercely.
"I got one of those new electronic cameras - you know, one thousand exposures per second... So we took pictures of Guzub making a Three Planets, and I could construct this one to do it exactly right down to the thousandth of a second. The proper proportion of vuzd, in case you're interested, works out to three-point-six-five-four-seven eight-two-three drops. It's done with a flip of the third joint of the tentacle on the down beat. It didn't seem right to use Guzub to make a robot that would compete with him and probably drive him out of business, so we've promised him a generous pension from the royalties on usuform barkeeps."
(Read more about Royalties For Machine Learning Subjects)
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