The findings make sense, provided that people who find themselves already artistic don’t really want to make use of AI to be artistic, says Tuhin Chakrabarty, a pc science researcher at Columbia College, who makes a speciality of AI and creativity however wasn’t concerned within the examine.
There are some potential drawbacks to benefiting from the mannequin’s assist, too. AI-generated tales throughout the board are comparable when it comes to semantics and content material, Chakrabarty says, and AI-generated writing is filled with telltale giveaways, corresponding to very lengthy, exposition-heavy sentences that include a lot of stereotypes.
“These sorts of idiosyncrasies in all probability additionally cut back the general creativity,” he says. “Good writing is all about displaying, not telling. AI is all the time telling.”
As a result of tales generated by AI fashions can solely draw from the information that these fashions have been educated on, these produced within the examine had been much less distinctive than the concepts the human contributors got here up with solely on their very own. If the publishing trade had been to embrace generative AI, the books we learn might change into extra homogenous, as a result of they’d all be produced by fashions educated on the identical corpus.
This is the reason it’s important to check what AI fashions can and, crucially, can’t do nicely as we grapple with what the quickly evolving know-how means for society and the economic system, says Oliver Hauser, a professor on the College of Exeter Enterprise Faculty, one other coauthor of the examine. “Simply because know-how may be transformative, it doesn’t imply will probably be,” he says.
