Scott examines the concept of 'priesthoods' (like medicine and academia) as epistemic communities that maintain high standards through isolation from the public, showing both their strengths and their vulnerability to ideological capture. Longer summary

Scott analyzes how professional 'priesthoods' like medicine and academia function as epistemic communities, maintaining their effectiveness through deliberate isolation from the public and strict internal standards. He explains how their key features - separation from the public, resistance to capitalism, and formal communication norms - help them maintain quality but also make them vulnerable to ideological capture. The post explores how these institutions were particularly susceptible to political capture in recent years, while arguing that despite their flaws, they still serve an important function that would be difficult to replicate. The discussion concludes by questioning how to deal with priesthoods' current state of partial corruption. Shorter summary

Scott clarifies his stance on conspiracy theories and expert trust, advocating for a nuanced approach that acknowledges both the value of expert opinion and the potential for misrepresentation. Longer summary

Scott revisits his previous post on fideism, addressing criticism and clarifying his stance on conspiracy theories and trusting experts. He presents three perspectives on conspiracy theories: Idiocy, Intellect, and Infohazard, and argues for a nuanced approach. Scott emphasizes that conspiracy theories can be convincing even to smart people, and that completely avoiding discussion of them is not always effective. He stresses the importance of trusting experts while also being aware of potential biases and misrepresentations. The post concludes with detailed advice on how to approach conspiracy theories and maintain a balanced perspective. Shorter summary

Scott Alexander examines his evolving view on scientific consensus, realizing it's more reliable and self-correcting than he previously thought. Longer summary

Scott Alexander reflects on his changing perspective towards scientific consensus, sharing personal experiences where he initially believed he was defying consensus but later discovered that the scientific community was often ahead of or aligned with his views. He discusses examples from various fields including the replication crisis, nutrition science, social justice issues, and AI risk. Alexander concludes that scientific consensus, while not perfect, is remarkably effective and trustworthy, often self-correcting within a decade of new evidence emerging. Shorter summary

Scott explores the nature of scientific contrarianism, discussing how ideas spread through the scientific community and the challenges faced by both crackpots and legitimate contrarians. Longer summary

This post discusses the concept of contrarians and crackpots in science, exploring how ideas move through different levels of the scientific community. Scott examines cases like Gary Taubes and the serotonin theory of depression to illustrate how scientific consensus can differ at various levels. He proposes a pyramid model of scientific knowledge dissemination and discusses how contrarians might be skipping levels in this pyramid. The post then contrasts virtuous contrarians with crackpots, noting that the former often face indifference rather than opposition. Scott concludes by discussing paradigm shifts in science and how even correct contrarians often lose credit for their ideas. 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

Scott Alexander estimates the frequency of significant scientific failures to evaluate the plausibility of climate change skepticism. Longer summary

Scott Alexander explores the frequency of scientific failures to assess the likelihood of climate change skepticism being correct. He defines criteria for significant scientific failures and identifies three clear examples: Lysenkoism, Freudian psychoanalysis, and behaviorism in psychology. After estimating the total number of possible scientific paradigms, he calculates a failure rate of about 1.2-3.6%. He concludes that this low failure rate doesn't provide much support for climate change skepticism, as it's similar to the proportion of papers that don't support anthropogenic climate change. Shorter summary