Twitter CEO Jack Dorsey responded to criticism of the site and suggested that the company might be able to “determine credible voices per topic in real-time.” Dorsey was answering complaints from New York Times White House correspondent Maggie Haberman who faulted “that everyone is treated as equally expert on various topics.”
In addition to complaining about the lack of ability to decipher experts, in her piece, Haberman said she was also temporarily refraining from using Twitter as much because of the “sexism” she’s witnessed, the increased frequency of tweets, the need to defend oneself against a poorly phrased word and how every story is treated as a major story.
In a thread of tweets, Dorsey replied to a handful of Haberman’s comments individually, defending the site.
On the topic of the outrage of the day and everyone being seen as an expert on every topic, Dorsey said there is a way to help “determine credible voices per topic in real-time, but it is “extremely challenging” and would require a mix of algorithms and a network:
When discussing the number of tweets users see when they log in, Dorsey brought up the curated “in case you missed it” section, but said there is apparently “work still to do” in the subject:
The topic Dorsey said he hopes to fix “the most” is that thoughtful and nuanced discussion does not appear to happen on the site:
One of the topics Dorsey did not address originally in Haberman’s piece is that Twitter is a site where, according to her, the “underbelly of free speech is at its most bilious”:
The viciousness, toxic partisan anger, intellectual dishonesty, motive-questioning and sexism are at all-time highs, with no end in sight. It is a place where people who are understandably upset about any number of things go to feed their anger, where the underbelly of free speech is at its most bilious.
Pressed for a discussion of that topic, Dorsey said he is unaware of how to fix the problem, but is attempting to “help better conversation”:
Other responses from Dorsey included “Happy to hear specific feedback” and “Noted.”
