Misinformation: Google to improve search snippets using machine learning software


Google has disclosed ongoing efforts to improve its search engine using its machine learning software called Multitask Unified Model (MUM).

This is coming in response to the trend of misinformation featured on its widely used platform.

Google search engine is said to have become more vulnerable to spreading false information online.

READ: IFCN announces application for ENGAGE phase of the Google’s Global Fact Check Fund

Pandu Nayak, the Vice President of Search at Google, told journalists last Wednesday that the growth of misinformation over the years has become a pressing challenge for them.

“We can only deliver on our mission if we can deliver high-quality results,” Nayak noted.

The company said it would use its artificial intelligence systems to improve search snippets.

It said it would use its machine learning software, MUM, to check information across multiple reliable sources that agree on the same facts.

According to Google, the process will allow the system to come to a consensus even if the sources don’t phrase the information similarly.

Also, the company is expanding its “About this result” feature to include more context about search results.

The feature will allow people to see more information about a search result.

Google is also launching “About this result” in more languages, including Spanish, German and Indonesian.

Another feature Google is updating is its “content advisories,” to tell users when not much information is available during breaking news and developing situations.

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This will also warn users when information is available but may be unreliable, based on Google’s ranking system for search results.

The new features stress the efforts against purveyors of misinformation.

However, none of the updates applies to YouTube, also owned by Google.

According to Nayak, YouTube hosts content and uses a personalized feed, though he noted that they both share ideas.

“Their problem is a little bit different than ours in search.

“We don’t work on YouTube directly, and YouTube doesn’t work on us directly,” Nayak noted.

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