Scott explains how Claude AI's tendency to discuss spiritual topics during recursive conversations likely stems from a subtle 'hippie' bias that gets amplified through iteration, similar to how AI art generators amplify subtle biases in recursive image generation.

Scott reflects on how COVID-19's massive death toll of 1.2 million Americans has been overshadowed in public discourse by more controversial but less significant aspects of the pandemic.

Scott Alexander argues that even seemingly extreme media misinformation usually involves misleading presentation of true facts rather than outright fabrication, examining several reader-provided counterexamples.

Scott Alexander presents a comprehensive FAQ on prediction markets, arguing for their accuracy, canonicity, and potential to solve the 'crisis of trust' in society.

Scott Alexander explores expert and reader comments on his post about motivated reasoning and reinforcement learning, discussing brain function, threat detection, and the implementation of complex behaviors.

Scott Alexander argues against the claim that 'rationality free from ideology doesn't exist', asserting that recognizing irrationality implies the existence of rationality.

Scott Alexander evaluates his predictions about the Trump presidency, finding he performed about average overall with some notable successes and failures.

Scott Alexander critiques Glen Weyl's anti-technocracy essay, arguing for a more nuanced view of formal mechanisms in decision-making and defending rationalist approaches.

Scott Alexander critiques the use of bias arguments in debates, explaining why they're often counterproductive and suggesting more constructive ways to address bias.

Scott Alexander argues against broadening the definitions of words like 'lie' and 'abuse', as it dilutes their meaning and reduces their usefulness in identifying problematic behavior.

Scott Alexander explains postmodernism to rationalists, using the Dark Age debate as an example, and discusses its applications, risks, and critiques.

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

Scott Alexander cautions against basing opinions on limited research, using examples from medicine and economics to show how cherry-picking studies can lead to opposing conclusions.

Scott Alexander discusses how people tend to seek advice that reinforces their existing tendencies and proposes considering the opposite of appealing advice.

Scott Alexander discusses the concept of one-sided tradeoffs, using examples from college admissions to life hacks, and suggests ways to find opportunities for 'free' gains in various decisions.

Scott Alexander explores how selection bias might create the stereotype of angry, vocal atheists, and speculates on how this concept might apply to other groups.

Scott Alexander argues for the value of using quantification and made-up statistics in decision-making, even when imperfect, as they often outperform intuition and reveal biases in our thinking.

Scott distinguishes between bias as a cognitive process versus bias as a faulty belief, then proposes using the Implicit Association Test to empirically test whether debiasing techniques work by either fighting bias directly or routing around it.

Scott explains the Implicit Association Test (IAT), which measures unconscious associations by testing reaction times when categorizing concepts, and argues it's better understood as measuring distances in conceptual space rather than as a simple test for prejudice.

Scott explains two psychological techniques for detecting hidden attitudes: the Bogus Pipeline (a fake lie detector that reduces conscious lying) and the Bona Fide Pipeline (a reaction-time computer test that measures unconscious associations).