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

Scott Alexander explores social dynamics through thought experiments involving castaways on a lifeboat and various 'backscratchers clubs'. He discusses how people form coalitions, make decisions in extreme situations, and how ideologies and social movements can serve as covers for mutual support networks. The post examines the formation of in-groups, the role of Schelling points in decision-making, and how these dynamics might relate to real-world phenomena like racism, nationalism, and establishment power structures. Shorter summary

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

Scott Alexander defends the use of non-frequentist probabilities for hard-to-model, non-repeating events. He argues that probabilities are linguistically convenient, don't necessarily describe one's level of information, and can be valuable when provided by expert forecasters. Scott counters claims that probabilities are used as a substitute for reasoning and addresses objections about applying probabilities to complex topics like AI. He emphasizes that probabilities are useful tools for clear communication and decision-making, even in uncertain domains. Shorter summary

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

This book review analyzes 'The Laws of Trading' by Agustin Lebron, which explores trading principles and their applications to decision-making in various aspects of life. The reviewer discusses Lebron's insights on motivation, adverse selection, risk management, liquidity, edge, models, costs and capacity, possibility, alignment, technology, and adaptation, while drawing parallels to other fields and offering personal reflections. Shorter summary

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

Scott Alexander discusses the 'wisdom of crowds' hypothesis, which claims that the average of many guesses is better than a single guess. He tests this concept using data from his ACX Survey, focusing on a question about the distance between Moscow and Paris. The post explores how error rates change with crowd size, whether individuals can benefit from averaging multiple guesses, and compares his findings to a larger study by Van Dolder and Van Den Assem. Scott also ponders why wisdom of crowds isn't more widely used in decision-making and speculates on its potential applications and limitations. Shorter summary

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

This post is a comprehensive FAQ about prediction markets, explaining what they are, why they are believed to be accurate and canonical, addressing common objections, and describing clever uses for them. Scott Alexander presents prediction markets as a potential solution to the 'crisis of trust' in modern society, arguing that they can provide unbiased, accurate predictions on a wide range of issues. The post also covers the current status of prediction markets and suggests ways people can help promote them. Shorter summary

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

This post reviews a dialogue between Eliezer Yudkowsky and Richard Ngo on AI alignment difficulty. Both accept that superintelligent AI is coming soon and could potentially destroy the world if not properly aligned. They discuss the feasibility of creating 'tool AIs' that can perform specific tasks without becoming dangerous agents. Yudkowsky argues that even seemingly safe AI designs could easily become dangerous agents, while Ngo is more optimistic about potential safeguards. The post also touches on how biological brains make decisions, and the author's thoughts on the conceptual nature of the discussion. Shorter summary

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

Scott Alexander proposes a new Bayesian theory of willpower, disagreeing with previous models like glucose depletion, opportunity cost minimization, and mental agent conflicts. He suggests willpower is a process of weighing evidence from different mental processes: a prior on motionlessness, reinforcement learning, and conscious calculations. The basal ganglia then resolves this evidence to determine actions. Scott explores how this model explains the effects of dopaminergic drugs on willpower and discusses implications for understanding mental illness and productivity. Shorter summary

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. Longer summary

Scott Alexander critiques Glen Weyl's essay 'Why I Am Not A Technocrat', arguing that Weyl's definition of technocracy is incoherent and his examples don't fit his own definition. Scott breaks down the concept of technocracy into several axes, including top-down vs. bottom-up, mechanism vs. judgment, and expert vs. popular opinion. He argues that formal mechanisms can be valuable in preventing bias and corruption, using examples like district creation and college admissions. Scott also defends the rationalist and effective altruism communities against Weyl's criticisms, highlighting their successes in areas like pandemic preparedness. He concludes that while critiques of technocracy are important, it's crucial to avoid oversimplifying the issue and to recognize that sometimes technocratic approaches can be beneficial. Shorter summary

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. Longer summary

Scott Alexander argues against the idea that probabilities should not be used without well-defined models. He presents scenarios where probability judgments are necessary even in novel situations, such as alien contact or evaluating research proposals. The post discusses the importance of making probability estimates in real-world decisions, even when precise models are unavailable. Scott acknowledges some valid criticisms but ultimately argues that using probabilities allows for better decision-making, accuracy checking, and challenging overconfidence. He suggests that alternatives to probabilistic thinking fall short when faced with real-world choices. Shorter summary

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

Scott Alexander discusses the concept of a 'General Factor of Correctness', inspired by Eliezer Yudkowsky's essay on the 'Correct Contrarian Cluster'. He explores whether people who are correct about one controversial topic are more likely to be correct about others, beyond what we'd expect from chance. The post delves into the challenges of identifying such a factor, including separating it from expert consensus agreement, IQ, or education level. Scott examines studies on calibration and prediction accuracy, noting intriguing correlations between calibration skills and certain beliefs. He concludes by emphasizing the importance of this concept to the rationalist project, suggesting that if such a 'correctness skill' exists, cultivating it could be valuable for improving decision-making across various domains. Shorter summary

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. Longer summary

This post discusses the concept of 'bicameral reasoning', drawing parallels between the US House and Senate representation systems and how people make decisions or judgments. Scott Alexander argues that often we give equal weight to issues of vastly different importance, much like how the Senate gives equal representation to states regardless of population. He illustrates this with examples from political issues, animal welfare considerations, and environmental concerns. The post suggests that this 'Senate-like' thinking can lead to poor decision-making by equating minor issues with major ones. While acknowledging some potential benefits to this way of thinking in extreme cases, the author ultimately argues for a more proportional 'House-like' approach to evaluating issues based on their actual impact or importance. Shorter summary

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

Scott proposes using a method similar to DW-Nominate, a tool used to calculate politicians' positions on the political spectrum, to investigate morality. He suggests applying this method to real-life moral decisions people make, from major choices to everyday actions. The post explores how this could potentially group people into 'good' and 'bad' categories, identify the most moral actions, and possibly provide insights into contentious moral issues. Scott also discusses how this method might work in morally inverted societies like Nazi Germany, presenting three hypothetical outcomes and their implications for understanding morality objectively. Shorter summary

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

Scott Alexander discusses the debate over selling art from Detroit's museum to address the city's financial problems. He cites an analysis from Marginal Revolution that calculates the cost of keeping a specific painting, concluding it's about $1200 per viewer. Scott emphasizes the value of attempting to quantify such decisions, even with imperfect numbers, as it can make the answer obvious. He argues for a consequentialist approach and provocatively suggests selling all the art and replacing it with forgeries, noting that signaling cultural superiority in Detroit might be misplaced. Shorter summary

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. Longer summary

Scott Alexander explores the concept of one-sided tradeoffs using college admissions as a starting point. He explains how most decisions involve tradeoffs between different qualities, but suggests ways to find opportunities for 'free' gains. These include insider trading (having unique knowledge), bias compensation (exploiting others' biases), and comparative advantage (specializing in a specific area). He applies this framework to policy debates, life hacks, and personal decisions, arguing that understanding these concepts can help identify opportunities where one can gain benefits without significant downsides. The post concludes with examples like considering nootropics if one isn't afraid of taking drugs, or buying houses on streets with rude names for a discount. Shorter summary

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. Longer summary

Scott Alexander discusses the value of using made-up statistics and quantification in decision-making, even when the numbers are imperfect. He argues that this approach can often lead to better outcomes than relying solely on intuition or System 1 thinking. The post begins with an anecdote about teaching Bayes' Theorem, then explores how quantification can improve decision-making in various fields, including utilitarianism and medical diagnosis. Scott emphasizes that while these numbers may be imperfect, they often provide more accurate results than gut feelings, which can be severely biased. He concludes by advocating for applying made-up models to various problems as a way to challenge our intuitions and gain new perspectives. Shorter summary

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. Longer summary

Scott Alexander shares his experience with Amazon Prime, describing how it has transformed his product selection process. He compares his old, complicated algorithm for choosing products in stores to his new, simpler method of using Amazon's ratings and reviews. Scott expresses surprise at how well this new approach works, given his skepticism about things actually improving. He lists several successful purchases made through Amazon, including an IRON GYM pull-up bar that has unexpectedly improved his exercise habits. The post concludes with Scott's reflections on feeling like an active participant in the economic system, both through boycotting and through using Amazon's review-based purchasing method. Shorter summary