Google Researchers Has Published A Proposal To Cut Out The Middle Man (Publishers) And Answer Quieres Using AI

A team of Google researchers has published a proposal for a radical redesign that throws out the ranking approach and replaces it with a single large AI language model, such as BERT or GPT-3—or a future version of them. The idea is that instead of searching for information in a vast list of web pages, users would ask questions and have a language model trained on those pages answer them directly. The approach could change not only how search engines work, but what they do—and how we interact with them.

So basically AI would answer a query directly within Google, learning from what’s published on the web, without driving traffic to the source websites.

“This index-retrieve-then-rank blueprint has withstood the test of time and has rarely been challenged or seriously rethought,” Donald Metzler and his colleagues at Google Research write.

Metzler and his colleagues are interested in a search engine that behaves like a human expert. It should produce answers in natural language, synthesized from more than one document, and back up its answers with references to supporting evidence, as Wikipedia articles aim to do.

The problem is that it does not keep track of those sources and cannot provide evidence for its answers. There’s no way to tell if GPT-3 is parroting trustworthy information or disinformation—or simply spewing nonsense of its own making.