How Are We Going to Stop Machine Learning Assistants From Spreading Fake News?

A race is underway to incorporate machine learning into search engines so they can answer queries with a paragraph as well as a list of links: the pioneer, the still relatively unknown You.com, was joined by Bing thanks to Microsoft’s agreement with Open.ai, while Google is experimenting with Bard. And on Friday, Brave Search announced an AI summarization feature that isn’t based on ChatGPT.

Meanwhile, ChatGPT says it has overcome some initial problems, as well as providing easier access from other countries such as Spain, which, together with its integration in more and more search engines, will likely see even more use around the world.

Noting this possible change in the usage model, The Atlantic raises an interesting question: what happens to the results that search engines offer about a person and that are possibly false, misleading or malicious, defamatory or based on conspiracy theories, when those results are included in a well-written paragraph.

Could generative assistants trained with material gleaned from the internet become the perfect allies for conspiracy theories or fake news? Hopefully, most of us will continue to use our critical faculties to question the results of searches, but for whatever reasons, others won’t, and by responding to a conversational dynamic in which previous interactions are introduced as part of the context, they may contribute to the creation of filter bubbles and, in general, to the spread of conspiracy theories and fake news.

In short, once again we talking about the interaction between critical thinking and conversational assistants, which in general try to apply a certain caution and, when asked to criticize somebody, tend to respond with formulas such as:

“As a language model, my programming prevents me from providing false or defamatory information about people. To criticize someone in a mean-spirited or baseless way is inappropriate and unfair.”

But by injecting ideas via prompt into a conversation, it is relatively easy to get these assistants to criticize or construct negative arguments based on anything they find on the web that they give credibility to, which means the documentation they use is going to have to pass some kind of quality control to the documents these assistants are trained on. This is surely already in place, but runs the risk of editorialization, even charges of censorship: Elon Musk has already accuse OpenAI’s ChatGPT, a company he helped found, of having a liberal bias, and says he wants to recruit people to develop an alternative, less “woke” model.

Anyone who lets a search assistant do their thinking for them deserves what they get. But in a scenario of increasingly common use of such technology, we are faced with a problem that may end up being quite complex. We’ll see what happens as they evolve.

(En español, aquí)

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This post was previously published on MEDIUM.COM.

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