How Disagreement Became ‘Disinformation’
Wall Street Journal | Barton Swaim
Swaim warns of the dangers of a “hopelessly simpleminded worldview” that “the primary factor separating…[one] side from the other side isn’t ideology, principle or moral vision but information—raw data requiring no interpretation and no argument over its importance.”
Swaim argues that “those most exercised about the spread of false information…[have a] lack of self-understanding [that] arises from the belief that the primary factor separating their side from the other side isn’t ideology, principle or moral vision but information… It is a hopelessly simpleminded worldview—no one apprehends reality without the aid of interpretive lenses. And it is a dangerous one.”
Those adhering to this vision, he explains, “believe their critics, who look at the same facts but draw different conclusions, aren’t simply mistaken but irrational, corrupt or both.”
Swaim traces this worldview back to the “doctrine of early-20th-century Progressivism, with its faith in the perfectibility of man, [that] held that social ills could be corrected by means of education… [Yet] that view is almost totally false, as a moment’s reflection on the many monstrous acts perpetrated by highly educated and well-informed criminals and tyrants should indicate. But it is an attractive doctrine for a certain kind of credentialed and self-assured rationalist.”
“Skeptics mostly attribute this new support for censorship to bad faith,” he explains. “I prefer a more charitable explanation. The new censors sincerely mistake their own interpretations of the facts for the facts themselves. Their opinions, filtered unconsciously through biases and experience, are, to them, simply information. Their views aren’t ‘views’ at all but raw data. Competing interpretations of the facts can be only one thing: misinformation. Or, if it’s deliberate, disinformation.”
When it comes to just following “the” science or “following the data,” Swaim states the obvious: “But of course you can’t follow data. Data just sits there and waits to be interpreted.” And so, when proven wrong, “They can hardly be expected to apologize for following the data.”
