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The Google Feature Magnifying Disinformation

The Atlantic – “…Google calls a “knowledge panel,” a collection of definitive-seeming information (dates, names, biographical details, net worths) that appears when you Google someone or something famous. Seven years after their introduction, in 2012, knowledge panels are essential internet infrastructure: 62 percent of mobile searches in June 2019 were no-click, according to the research firm Jumpshot, meaning that many people are in the habit of searching; looking at the knowledge panel, related featured snippets, or top links; and then exiting the search [emphasis added]. A 2019 survey conducted by the search marketing agency Path Interactive found that people ages 13 to 21 were twice as likely as respondents over 50 to consider their search complete once they’d viewed a knowledge panel….when every square inch of the internet is contested terrain, Google results have become an unlikely site for the spread of misinformation: Some knowledge panels, and related featured snippets, cite information posted in bad faith, and in so doing, magnify false and hateful rhetoric….Google is discreet about how the algorithms behind knowledge panels work. Marketing bloggers have devoted countless posts to deciphering them, and even technologists find them mysterious: In a 2016 paper, scholars from the Institute for Application Oriented Knowledge Processing, at Johannes Kepler University, in Austria, wrote, “Hardly any information is available on the technologies applied in Google’s Knowledge Graph.” As a result, misleading or incorrect information, especially if it’s not glaringly obvious, may be able to stay up until someone with topical expertise and technical savvy catches it…For its part, Google has acknowledged that it has a disinformation problem. In February, the company published a white paper titled “How Google Fights Disinformation”; the paper actually cites knowledge panels as a tool the company provides to help users get context and avoid deceptive content while searching. The paper also emphasizes that algorithms, not humans, rank results (possibly as a means of warding off accusations of bias)…”

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