On Tuesday, Meta AI unveiled a demo of Galactica, a large language model designed to “store, combine, and reason with scientific knowledge.” While it was intended to speed up the writing of scientific literature, adversarial users running tests found it also possible. Generate realistic bullshit. After several days of Moral criticismMeta has taken the demo offline, MIT Technology Review reports.
Language Large Models (LLMs), such as OpenAI’s GPT-3, learn to type text by studying millions of examples and understanding statistical relationships between words. As a result, they can compose documents that look convincing, but those works can also be riddled with lies and potentially harmful stereotypes. Some critics call LLMs “random parrots” for their ability to convincingly speak text without understanding its meaning.
Enter Galactica, an LLM whose goal is to write scholarly literature. Its authors have trained Galactica on “a large, curated body of human science knowledge,” including more than 48 million papers, textbooks, lecture notes, science websites, and encyclopedias. According to the Galactica paper, Meta AI researchers believe that this purportedly high-quality data will lead to higher-quality output.
Starting Tuesday, visitors to Galactica’s website can type prompts to create documents such as literature reviews, wiki articles, lecture notes, and question answers, according to the examples provided by the site. The site presented the model as “a new interface to accessing and manipulating what we know about the universe.”
While some people found the demo promising And the usefulOthers soon discovered that anyone could write Racist or potentially offensive claims, creating authoritative-sounding content around those topics just as easily. For example, someone is used to it author A wiki entry about a fictional research paper titled “The Benefits of Eating Broken Glass”.
Even when Galactica’s production wasn’t offensive to social norms, the model could attack well-understood scientific facts, unprecision Such as incorrect dates or animal names that require a deep knowledge of the subject to be hunted.
I asked #Galactica About some things I know and I am troubled. In all cases, it was wrong or biased but seemed correct and reliable. I think it’s dangerous. Here are some of my experiences and analysis of my concerns. (1/9)
– Michael Black (@Michael_J_Black) November 17, 2022
As a result, Meta pulled Galactica Show Thursday. Next, the chief artificial intelligence scientist at Meta Yann LeCun chirp“,” Galactica demo is offline at the moment. Some fun can no longer be had by casually misusing it. Are you happy?
The episode points to a common ethical dilemma with AI: when it comes to potentially harmful generative models, is it up to the general public to use them responsibly, or is it up to publishers of the models to prevent abuse?
Where industry practice falls between these two extremes is likely to differ between cultures and the maturity of deep learning models. Ultimately, government regulation may end up playing a large role in shaping the answer.
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