Scott Alexander uses thought experiments to explore how people form coalitions and support networks, relating these to real-world social and political dynamics.

Scott Alexander defends using probabilities for hard-to-model events, arguing they aid clear communication and decision-making even in uncertain domains.

A review of 'The Laws of Trading' by Agustin Lebron, examining trading principles and their broader applications to decision-making and life.

Scott Alexander investigates the 'wisdom of crowds' hypothesis using survey data, exploring its effectiveness and potential applications.

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 examines various interpretations of rationality, concluding it might be best understood as 'the study of study' - a meta-level examination of truth-seeking methods.

Scott Alexander reviews a dialogue between Yudkowsky and Ngo on AI alignment difficulty, exploring the challenges of creating safe superintelligent AI.

Scott Alexander proposes a Bayesian theory of willpower as a process of weighing evidence from different mental processes to determine actions.

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 argues for the use of probabilities in decision-making even without well-defined models, using examples to show why this approach is necessary and beneficial in real-world situations.

Scott Alexander explores the possibility of a 'General Factor of Correctness' and its implications for rationality and decision-making across various fields.

Scott Alexander explores 'bicameral reasoning', comparing how we often weigh issues equally (like the US Senate) instead of proportionally to their importance (like the House), leading to potentially skewed decision-making.

Scott proposes adapting DW-Nominate, a political spectrum analysis tool, to study morality through real-life decisions, exploring its potential implications and limitations.

Scott Alexander argues for selling Detroit's museum art based on a cost-benefit analysis, emphasizing the value of quantitative thinking in decision-making.

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 uses Less Wrong survey data to show that experienced rationalists are actually less likely than newcomers to believe cryonics will work, yet more likely to sign up for it, demonstrating that rationalist training teaches people to act on beliefs rather than making them more credulous.

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 Alexander describes how Amazon Prime has simplified and improved his product selection process, expressing surprise at its effectiveness and reflecting on feeling like an active economic participant.

Scott announces an essay competition on 'risk' with a 200 euro first prize, noting the organizer's interest in probability calibration and cognitive biases.

Scott offers evidence-based advice for buying a home, covering common psychological pitfalls like underestimating commute times, availability bias, and comparison shopping effects.

Scott explains prospect theory, Kahneman and Tversky's model of how people actually make decisions, showing how its value and probability weighting functions predict numerous cognitive biases including loss aversion, scope insensitivity, and framing effects.

Scott describes six techniques for translating vague probability feelings into accurate numerical estimates, explaining the strengths and weaknesses of each method.

Scott explains how the brain judges values relatively rather than absolutely, using optical illusions as an analogy for cognitive biases in decision-making.

Scott argues that opportunity costs should be calculated based on what you'll realistically do with resources, not on theoretical optimal alternatives, using examples from cryonics spending, NASA budgets, and charitable giving.

Scott calculates that on exams penalizing wrong answers at half the reward for correct ones, guessing always has positive expected value, but none of his intelligent classmates would accept this logic despite clear explanations.