Wikipedia is ‘broken’ – Musk
The X owner apparently concurs with claims that some of the resource’s articles unjustifiably tie Donald Trump to fascist ideology
Wikipedia is “broken,” X and Tesla owner Elon Musk wrote on Tuesday, commenting on accusations that the online encyclopedia allows articles which essentially brand Republican presidential nominee Donald Trump a “fascist.”
The billionaire, who recently offered his full support to the previous US president ahead of the November election, highlighted an article called ‘Wikipedia Editors Officially Deem Trump a Fascist’ by American writer Ashley Rindsberg.
The article published on Pirate Wires drew attention to several Wikipedia entries, including ‘Trumpism’, ‘Racial views of Donald Trump’, and ‘Donald Trump and fascism’, noting that the latter page appeared on the same day that The Guardian published a 4,000-word essay called “Is Donald Trump a Fascist?” alluding to many similar points.
The page ‘Donald Trump and fascism’ also contains some of the more pointed accusations against the Republican, including comparisons between the January 6 attack by the then president’s supporters on Capitol Hill and the Beer Hall Putsch, a failed coup attempt by Nazi leader Adolf Hitler in 1923.
Rindsberg noted that the ‘Trumpism’ Wikipedia page writes that the supposed ideology “has significant authoritarian leanings,” and is “national-populist” and “neo-nationalist” in essence while relying on “a source that argues exactly the opposite.” He added that some of the key quotes in the ‘Trumpism’ article are sourced to late sociologist Richard Lachmann, who was described as a “committed leftist” and “an anti-imperialist.”
Commenting on Rindsberg’s article, Musk wrote on X: “Wikipedia is broken.” He previously claimed that the website “is controlled by far-left activists” and that “people should stop donating to them.”
Musk’s criticism of Wikipedia comes after a June report by the Manhattan Institute found that some English-language articles tended to associate right-wing leaders more often with words correlated with negative emotions as “anger” and “disgust.” This apparent bias, the researchers added, is also influencing automatic responses given by AI large language models.
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