The post uses a fabricated narrative about cardiologists to illustrate the Chinese Robber Fallacy and its role in media bias, emphasizing the importance of context in interpreting negative stories about any group. Longer summary

This post discusses the Chinese Robber Fallacy and its implications for media bias. The author begins with a satirical section presenting numerous examples of cardiologists committing various crimes and unethical acts, creating the impression of widespread issues in the profession. The second part reveals this as a demonstration of how easy it is to create a false narrative about any group using selective examples. The author then explores how this fallacy applies to media coverage of issues like police brutality and sexism in tech, emphasizing the importance of understanding base rates and population sizes when interpreting such stories. The post concludes by revealing that the initial section about cardiologists was entirely fabricated to illustrate the point. Shorter summary

A curated collection of interesting links spanning medicine, economics, social issues and quirky stories, with Scott's commentary on various developments and findings. Longer summary

This is a collection of interesting links and news curated by Scott Alexander, covering a wide range of topics from medical research to economics, social issues, and quirky stories. The post includes discussions of new medical findings about heart receptors, debates about alcohol health effects, archaeological stories, studies about demographics and education, and various social and economic developments. Scott adds his own commentary and insights to many of the links, particularly around housing policy, scientific studies, and mental health care. Shorter summary

Scott Alexander provides evidence that many prominent AI researchers are concerned about AI risk, contrary to claims in some popular articles. Longer summary

Scott Alexander responds to articles claiming that AI researchers are not concerned about AI risk by providing a list of prominent AI researchers who have expressed concerns about the potential risks of advanced AI. He argues that there isn't a clear divide between 'skeptics' and 'believers', but rather a general consensus that some preliminary work on AI safety is needed. The post highlights that the main differences lie in the timeline for AI development and when preparations should begin, not whether the risks are real. Shorter summary