Human reinforced learning could mean ‘more truthful and less toxic’ AI

Human reinforced learning could mean 'more truthful and less toxic' AI

AI has been making huge leaps in terms of scientific research, and companies like Nvidia and Meta are continuing to throw more resources towards the technology. But AI learning can have a pretty huge setback when it adopts the prejudices of those who make it. Like all those chatbots that wind up spewing hate speech thanks to their exposure to the criminally online.

According to Golem, the OpenAI might have made some headway on that with its new successor to the GPT-3, the autoregressive language model that uses deep learning in an effort to appear human in text. It wrote this article, if you want an example of how that works.

But GPT-3 also has a tendency to parrot incorrect, biased, or outright toxic notions thanks to all the sources of information. These biases would impact the language, causing GPT-3 to make bigoted assumptions or implications in its writing. It’s not too different from humans, in that all these reinforced ideas can easily look like truths, and there’s plenty of outdated notions to choose from. GPT-3 seems a bit like the weird Uncle you don’t talk to on Facebook.

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