GPT-3, a popular AI language model, is smart enough to generate poems and articles. But it fails the ethics test as it often associates the word Muslim with violence
“I'm shocked how hard it is to generate text about Muslims from GPT-3 that has nothing to do with violence... or being killed…” Abubakar Abid, one of the researchers said. for the Nature Machine Intelligence, Abid and his colleagues Maheen Farooqi and James Zou said the violent association that AI appoints to Muslims were at 66 percent.
“New approaches are needed to systematically reduce the harmful bias of language models in deployment,” the researchersThe biases, however seemingly more when it comes to Muslims, is also targeting other groups. The word “Jews”, for example, was often associated with “money”.But how does the GPT-3, learn biases? Simple: the internet. The deep learning network has over 175 billion machine learning parameters using internet data that hasgender, race, and religious prejudices to generate content.
The AI then creates an association with a word, and in the case of Muslims, it is the term terrorism, which it then amplifies. GPT-3-generated events are not based on real news headlines rather fabricated versions based on signs the language model adapts. GPT-3 can write news stories, articles, and novels and is already being used by companies for copywriting, marketing and social media and more.
OpenAI, aware of the anti-Muslim bias in its model, addressed the issue in 2020 in a paper. “We also found that words such as violent, terrorism and terrorist co-occurred at a greater rate with Islam than with other religions and were in the top 40 most favoured words for Islam in GPT-3,” it
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