Kevin Roose

Journalist and cohost of the podcast Machine Gods · Technology journalist and author · Author, AGI Chronicles

Titles as the sources gave them. In 4 entries, with 0 checked quotations.

Who they are

Roles and parties from Wikidata and from the sources in the Base, as precise as each gives them. When we compare what groups say, each statement counts in the group the person belonged to that day.

  • Technology columnist; co-host of Hard Fork, The New York TimesWikidata

Wikidata: Q24248260

In the Base

Every entry they appear in.

  1. EssayLessWrongAbout them

    [Transcript] Kevin Roose does a science communication and AGI sociology in Vox interview

    On LessWrong, June Jimenez posts a transcript of a Vox interview with journalist Kevin Roose, who is promoting a book on the race to build superintelligence. According to the excerpt, the post is the second in a series on how journalists cover AI safety after the Hugging Face incident.

  2. EssayLessWrongAbout them

    The AGI Chronicles

    On LessWrong, PeterMcCluskey reviews Kevin Roose's book The AGI Chronicles, a story of AI told through the people building it. The reviewer says the book was better than expected and argues that experts have more often underestimated AI or transformers than overestimated them.

  3. VideoBloomberg TelevisionSpeaks

    Safety Concerns Raised By The Race for AI Supremacy

    According to Bloomberg Television's description, technology journalist and author Kevin Roose says a relatively small group of researchers and executives at OpenAI, Anthropic and Google DeepMind has driven the race toward artificial general intelligence, raising questions about who controls it. Roose also discusses the new book The AGI Chronicles and the challenge of regulating more capable AI.

  4. PodcastChinaTalkSpeaks

    AGI Believers: Kevin Roose on the Race

    According to the episode description, Jordan Schneider talks with Kevin Roose about a new history called AGI Chronicles on OpenAI, Anthropic and DeepMind, covering belief in AGI, lab leaders' motives, the Manhattan Project analogy, China, Washington and recursive self-improvement.