Chapter
Slippery Slope to Censorship
26:43 - 43:20 (16:36)
The episode discusses the slippery slope towards censorship and manipulation of opinion due to algorithm-based feedback loops and anecdotal evidence. It highlights the need for critical thinking and the reliance on statistics over anecdote to make sound judgments.
Clips
This podcast episode explores the issue of censorship on social media platforms such as Twitter and Facebook, particularly in the case of the New York Post article which was recently censored.
26:43 - 37:21 (10:37)
Summary
This podcast episode explores the issue of censorship on social media platforms such as Twitter and Facebook, particularly in the case of the New York Post article which was recently censored. The hosts argue that the algorithms used by social media platforms are designed to keep users engaged and may create feedback loops, and that the power of censorship is a sweeping assertion of power.
ChapterSlippery Slope to Censorship
EpisodeE10: Twitter & Facebook botch censorship (again), the publisher vs. distributor debate & more
PodcastAll-In with Chamath, Jason, Sacks & Friedberg
Despite the media's attempt to keep people in fear, there are very effective treatments for COVID-19, including Regeneron and Remdesivir.
37:21 - 41:24 (04:03)
Summary
Despite the media's attempt to keep people in fear, there are very effective treatments for COVID-19, including Regeneron and Remdesivir. While it may be hard for people to believe in statistics, the numbers show that there is a 97% chance of making it through the virus.
ChapterSlippery Slope to Censorship
EpisodeE10: Twitter & Facebook botch censorship (again), the publisher vs. distributor debate & more
PodcastAll-In with Chamath, Jason, Sacks & Friedberg
A recent study of dialysis patients in the Northeast showed that 27.7% of them had already been infected with COVID-19, which translates to 217,000 cases.
41:24 - 43:20 (01:55)
Summary
A recent study of dialysis patients in the Northeast showed that 27.7% of them had already been infected with COVID-19, which translates to 217,000 cases. The study also suggests that the true infection fatality rate (IFR) is likely lower than reported due to undetected cases.