E = Easy (adequate for a low educational background)
M = Memetic Hazard (controversial ideas or works of fiction)
Summary
Do not flinch, most of LessWrong can be read and understood by people with a previous level of education less than secondary school. (And Khan Academy followed by BetterExplained plus the help of Google and Wikipedia ought to be enough to let anyone read anything directed at the scientifically literate.) Most of these references aren’t prerequisite, and only a small fraction are pertinent to any particular post on LessWrong. Do not be intimidated, just go ahead and start reading the Sequences if all this sounds too long. It’s much easier to understand than this list makes it look like.
This list is hosted on LessWrong.com, a community blog devoted to refining the art of human rationality—the art of thinking. If you follow the links below you’ll learn more about this community. It is one of the most important resources you’ll ever come across if your aim is to get what you want, if you want to win. It shows you that there is more to most things than meets the eye, but more often than not much less than you think. It shows you that even smart people can be completely wrong but that most people are not even wrong. It teaches you to be careful in what you emit and to be skeptical of what you receive. It doesn’t tell you what is right, it teaches you how to think and to become less wrong. And to do so is in your own self interest because it helps you to attain your goals, it helps you to achieve what you want.
Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultra-intelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion,” and the intelligence of man would be left far behind. — I. J. Good, “Speculations Concerning the First Ultraintelligent Machine”
The term “Singularity” had a much narrower meaning back when the Singularity Institute was founded. Since then the term has acquired all sorts of unsavory connotations. — Eliezer Yudkowsky
One of the painful things about our time is that those who feel certainty are stupid, and those with any imagination and understanding are filled with doubt and indecision. — Bertrand Russell
Ignorance more frequently begets confidence than does knowledge. — Charles Darwin
The heuristics and biases program in cognitive psychology tries to work backward from biases (experimentally reproducible human errors) to heuristics (the underlying mechanisms at work in the brain).
Here’s a phenomenon I was surprised to find: you’ll go to talks, and hear various words, whose definitions you’re not so sure about. At some point you’ll be able to make a sentence using those words; you won’t know what the words mean, but you’ll know the sentence is correct. You’ll also be able to ask a question using those words. You still won’t know what the words mean, but you’ll know the question is interesting, and you’ll want to know the answer. Then later on, you’ll learn what the words mean more precisely, and your sense of how they fit together will make that learning much easier. The reason for this phenomenon is that mathematics is so rich and infinite that it is impossible to learn it systematically, and if you wait to master one topic before moving on to the next, you’ll never get anywhere. Instead, you’ll have tendrils of knowledge extending far from your comfort zone. Then you can later backfill from these tendrils, and extend your comfort zone; this is much easier to do than learning “forwards”. (Caution: this backfilling is necessary. There can be a temptation to learn lots of fancy words and to use them in fancy sentences without being able to say precisely what you mean. You should feel free to do that, but you should always feel a pang of guilt when you do.) — Ravi Vakil
Probabilities express uncertainty, and it is only agents who can be uncertain. A blank map does not correspond to a blank territory. Ignorance is in the mind. — Eliezer Yudkowsky
Math is fundamental, not just for LessWrong. But especially Bayes’ Theorem is essential to understand the reasoning underlying most of the writings on LW.
All the limitative theorems of metamathematics and the theory of computation suggest that once the ability to represent your own structure has reached a certain critical point, that is the kiss of death: it guarantees that you can never represent yourself totally. Gödel’s Incompleteness Theorem, Church’s Undecidability Theorem, Turing’s Halting Theorem, Tarski’s Truth Theorem — all have the flavour of some ancient fairy tale which warns you that “To seek self-knowledge is to embark on a journey which … will always be incomplete, cannot be charted on any map, will never halt, cannot be described.”— Douglas Hofstadter 1979
It is precisely the notion that Nature does not care about our algorithm, which frees us up to pursue the winning Way—without attachment to any particular ritual of cognition, apart from our belief that it wins. Every rule is up for grabs, except the rule of winning. — Eliezer Yudkowsky
Remember that any heuristic is bound to certain circumstances. If you want X from agent Y and the rule is that Y only gives you X if you are a devoted irrationalist then ¬irrational. Under certain circumstances what is irrational may be rational and what is rational may be irrational. Paul K. Feyerabend said: “All methodologies have their limitations and the only ‘rule’ that survives is ‘anything goes’.”
Game theory is the study of the ways in which strategic interactions among economic agents produce outcomes with respect to the preferences (or utilities) of those agents, where the outcomes in question might have been intended by none of the agents. — Stanford Encyclopedia of Philosophy
With Release 33-9117, the SEC is considering substitution of Python or another programming language for legal English as a basis for some of its regulations. — Will Wall Street require Python?
Programming knowledge is not mandatory for LessWrong but you should however be able to interpret the most basic pseudo code as you will come across various snippets of code in discussions and top-level posts outside of the main sequences.
Python
Python is a general-purpose high-level dynamic programming language.
A poet once said, “The whole universe is in a glass of wine.” We will probably never know in what sense he meant that, for poets do not write to be understood. But it is true that if we look at a glass of wine closely enough we see the entire universe. — Richard Feynman
An electron is not a billiard ball, and it’s not a crest and trough moving through a pool of water. An electron is a mathematically different sort of entity, all the time and under all circumstances, and it has to be accepted on its own terms. The universe is not wavering between using particles and waves, unable to make up its mind. It’s only human intuitions about QM that swap back and forth. — Eliezer Yudkowsky
I am not going to tell you that quantum mechanics is weird, bizarre, confusing, or alien. QM is counterintuitive, but that is a problem with your intuitions, not a problem with quantum mechanics. Quantum mechanics has been around for billions of years before the Sun coalesced from interstellar hydrogen. Quantum mechanics was here before you were, and if you have a problem with that, you are the one who needs to change. QM sure won’t. There are no surprising facts, only models that are surprised by facts; and if a model is surprised by the facts, it is no credit to that model. — Eliezer Yudkowsky
The mathematical universe (Level IV Multiverse/Ultimate Ensemble/Mathematical Universe Hypothesis) FEM
Evolution
(Evolution) is a general postulate to which all theories, all hypotheses, all systems must henceforward bow and which they must satisfy in order to be thinkable and true. Evolution is a light which illuminates all facts, a trajectory which all lines of thought must follow — this is what evolution is. — Pierre Teilhard de Chardin
There is no such thing as philosophy-free science; there is only science whose philosophical baggage is taken on board without examination. — Daniel Dennett, Darwin’s Dangerous Idea, 1995.
Philosophy is a battle against the bewitchment of our intelligence by means of language. — Wittgenstein
Not essential but a good preliminary to reading LessWrong and in some cases helpful to be able to make valuable contributions in the comments. Many of the concepts in the following works are often mentioned on LessWrong or the subject of frequent discussions.
Elaboration of miscellaneous terms, concepts and fields of knowledge you might come across in some of the subsequent and more technical advanced posts and comments on LessWrong. The following concepts are frequently discussed but not necessarily supported by the LessWrong community. Those concepts that are controversial are labeledM.
References & Resources for LessWrong
A list of references and resources for LW
Updated: 2011-05-24
F = Free
E = Easy (adequate for a low educational background)
M = Memetic Hazard (controversial ideas or works of fiction)
Summary
Do not flinch, most of LessWrong can be read and understood by people with a previous level of education less than secondary school. (And Khan Academy followed by BetterExplained plus the help of Google and Wikipedia ought to be enough to let anyone read anything directed at the scientifically literate.) Most of these references aren’t prerequisite, and only a small fraction are pertinent to any particular post on LessWrong. Do not be intimidated, just go ahead and start reading the Sequences if all this sounds too long. It’s much easier to understand than this list makes it look like.
Nevertheless, as it says in the Twelve Virtues of Rationality, scholarship is a virtue, and in particular:
Contents
LessWrong.com
Overview
Why read Less Wrong?
Artificial Intelligence
General
Friendly AI
Machine Learning
The Technological Singularity
Heuristics and Biases
Mathematics
Learning Mathematics
Basics
General
Probability
Logic
Foundations
Miscellaneous
Decision theory
Game Theory
Programming
Python
Haskell
General
Computer science
(Algorithmic) Information Theory
Physics
General
General relativity
Quantum physics
Foundations
Evolution
Philosophy
General
The Mind
Epistemology
Linguistics
Neuroscience
General Education
Miscellaneous
Concepts
Websites
Fun & Fiction
Fiction
Fun
Go
LessWrong.com
This list is hosted on LessWrong.com, a community blog devoted to refining the art of human rationality—the art of thinking. If you follow the links below you’ll learn more about this community. It is one of the most important resources you’ll ever come across if your aim is to get what you want, if you want to win. It shows you that there is more to most things than meets the eye, but more often than not much less than you think. It shows you that even smart people can be completely wrong but that most people are not even wrong. It teaches you to be careful in what you emit and to be skeptical of what you receive. It doesn’t tell you what is right, it teaches you how to think and to become less wrong. And to do so is in your own self interest because it helps you to attain your goals, it helps you to achieve what you want.
Overview
About Less Wrong FE
FAQ FE
Less Wrong wiki (The wiki about rationality.) F
The Sequences (The most systematic way to approach the Less Wrong archives.) FE
Sequences in Alternative Formats (HTML, Markdown, PDF, and ePub versions.) FE
List of all articles from Less Wrong (In chronological order.) F
Graphical Visualization of Major Dependencies (Dependencies between Eliezer Yudkowsky posts.) FE
Eliezer’s Posts Index (Autogenerated index of all Yudkowsky posts in chronological order.) FE
Eliezer Yudkowsky’s Homepage (Founder of LW and top contributor.) FE
Less Wrong Q&A with Eliezer Yudkowsky: Video Answers FE
An interview with Eliezer Yudkowsky (Parts 1, 2 and 3) FE
Eliezer Yudkowsky on Bloggingheads.tv FE
Best of Rationality Quotes 2009/2010 FE
Less Wrong Rationality Quotes (Sorted by points. Created by DanielVarga.) FE
Comment formatting FE
Why read Less Wrong?
A few articles exemplifying in detail what you can expect from reading Less Wrong, why it is important, what you can learn and how it does help you.
Yes, a blog. FE
What I’ve learned from Less Wrong FE
Goals for which Less Wrong does (and doesn’t) help FE
Rationality: Common Interest of Many Causes FE
How to Save the World FE
Reflections on rationality a year out FE
Artificial Intelligence
General
AI Foom Debate F
Intelligence explosion FE
Why an Intelligence Explosion is Probable F
The Nature of Self-Improving Artificial Intelligence (Audio) F
SIAI Reading List: Artificial Intelligence and Technology Acceleration Skeptics
SIAI Reading List: Artificial General Intelligence and the Singularity
So You Want To Be A Seed AI Programmer F
Levels of Organization in General Intelligence F
Artificial Intelligence: A History of Ideas and Achievements F
Publications | Singularity Institute for Artificial Intelligence F
Some Singularity, Superintelligence, and Friendly AI-Related Links F
Introduction to Artificial Intelligence (index) FE
Friendly AI
Recommended Reading for Friendly AI Research F
A review of proposals toward safe AI F
Friendly AI: a bibliography F
Creating Friendly AI 1.0 (The Analysis and Design of Benevolent Goal Architectures) F
What is Friendly AI? FE
Knowability Of FAI F
Bostrom & Yudkowsky, “The Ethics of Artificial Intelligence” (2011) F
Paperclip maximizer FE
From mostly harmless to civilization-threatening: pathways to dangerous artificial general intelligences FE
A compact list of Eliezer Yudkowsky’s positions (Reasons to take friendly AI serious.) FE
The Basic AI Drives F
Catastrophic risks from artificial intelligence F
Super-intelligence does not imply benevolence (Videos) F
Coherent Extrapolated Volition (CEV) FM
Shaping the Intelligence Explosion (Anna Salamon at Singularity Summit 2009) FE
Machine Ethics is the Future F
Who’s Who in Machine Ethics F
Mitigating the Risks of Artificial Superintelligence F
Machine Learning
Not essential but an valuable addition for anyone who’s more than superficially interested in AI and machine learning.
A Gentle Introduction to the Universal Algorithmic Agent AIXI F
School in Logic, Language and Information (ESSLLI) F
Good Freely Available Textbooks on Machine Learning F
Learning About Statistical Learning
Learning about Machine Learning, 2nd Ed.
Bayesian Reasoning and Machine Learning F
The Technological Singularity
Three Major Singularity Schools, Eliezer Yudkowsky FE
The Singularity FAQ FE
Brief History of Intellectual Discussion of Accelerating Change FE
The Singularity: A Philosophical Analysis FE
Special Report: The Singularity (IEEE Spectrum) FEM
The Coming Technological Singularity (The original essay by Vernor Vinge.) FEM
Technological singularity FEM
The Singularity Is Near, Ray Kurzweil EM
Robot: Mere Machine to Transcendent Mind E
Mind Children: The Future of Robot and Human Intelligence E
There’s More to Singularity Studies Than Kurzweil FE
Tech Luminaries Address Singularity (IEEE Spectrum. (2008, June).) FEM
Economics Of The Singularity (Hanson, R. (2008).) FE
What did you learn about the singularity today? F
The Singularity Hypothesis: A Scientific and Philosophical Assessment (Bibliography) FE
Yes, The Singularity is the Biggest Threat to Humanity FE
What should a reasonable person believe about the Singularity? FE
An overview of models of technological singularity F
Hard Takeoff Sources F
Heuristics and Biases
The heuristics and biases program in cognitive psychology tries to work backward from biases (experimentally reproducible human errors) to heuristics (the underlying mechanisms at work in the brain).
Cognitive biases, common misconceptions, and fallacies. FE
Cognitive Biases Potentially Affecting Judgment of Global Risks F
Ugh fields (The Ugh Field forms a self-shadowing blind spot) FE
The Apologist and the Revolutionary (Not being aware of your own disabilities.) FE
Generalizing From One Example FE
Self-fulfilling correlations F
The scourge of perverse-mindedness FE
Dunning–Kruger effect FE
Procrastination FE
Mathematics
Learning Mathematics
Habits of Mathematical Minds FE
How to Develop a Mindset for Math FE
How to learn math? FE
How Do You Go About Learning Mathematics? (Here another version.) FE
How to Read Mathematics F
A Learning Roadmap: From high-school to mid-undergraduate studies F
Basics
The Khan Academy (World-class education for free (1800+ videos).) FE
Just Math Tutotrials (FREE math videos for the world!) F
BetterExplained (There’s always a better way to explain a topic.) FE
Steven Strogatz on the Elements of Math (A very basic introduction to mathematics.) FE
Mathematics Illuminated F
General
The Princeton Companion to Mathematics (Reference for anyone with a serious interest in mathematics.)
Concrete Mathematics: A Foundation for Computer Science (A solid and relevant base of mathematical skills.)
The Art and Craft of Problem Solving
Mathematical Logic F
Free Mathematics eBooks F
Free Online Mathematics Textbooks F
Interactive Mathematics Miscellany and Puzzles F
math.stackexchange.com (Q&A for people studying math at any level.) F
MathOverflow F
Probability
Math is fundamental, not just for LessWrong. But especially Bayes’ Theorem is essential to understand the reasoning underlying most of the writings on LW.
Probability is in the Mind FE
My Bayesian Enlightenment FE
What is Bayesianism FE
Bayes’ Theorem Illustrated (My Way) FE
An Intuitive (and Short) Explanation of Bayes’ Theorem FE
An Intuitive Explanation of Eliezer Yudkowsky’s Intuitive Explanation of Bayes’ Theorem FE
An Intuitive Explanation of Bayes’ Theorem FE
A Technical Explanation of Technical Explanation (More Bayes. Many writings rely on this page.) F
Bayes’ theorem FE
You, A Bayesian FE
Visualizing Bayes’ theorem FE
The Nature of Probability (Video talk between Eliezer Yudkowsky and the statistician Andrew Gelman.) FE
Probability Theory: The Logic of Science , E. T. Jaynes (Free draft available.)
Probability Theory With Applications in Science and Engineering, E. T. Jaynes F
Bayesian Probability Theory (Bayesian approach) vs. Frequentist Probability Theory (Frequentist approach) F
Probability Theory As Extended Logic F
Introduction to Bayesian Statistics, William M. Bolstad
Bayesian statistics (Scholarpedia) F
Bayesian probability (Wikipedia) F
Bayes’ Theorem (A whole crowd on the blogs that seems to see more in Bayes’s theorem.) F
Bayesian Epistemology (Stanford Encyclopedia of Philosophy) F
Monty Hall problemformally proven using Bayes’ theorem F
Monty Hall, Monty Fall, Monty Crawl F
The Bayesian revolution of the sciences F
Bayesian data analysis F
What to believe: Bayesian methods for data analysis F
Probability Booklist
An Introduction to Probability Theory and Its Applications
Aumann’s agreement theorem (Agreeing to Disagree) F
Logic
Mr. Spock is Not Logical FE
Logic FE
Mathematical logic FE
Introduction to Boolean algebra F
Boolean algebra F
Boolean logic F
First-order logic F
First-Order Logic, Raymond M. Smullyan
Propositional calculus F
Introduction to Mathematical Logic F
Introduction to Logic, Alfred Tarski
Introduction to Mathematical Logic, Alonzo Church
Possible Worlds: An Introduction to Logic and Its Philosophy F
Gödel Without Tears F
Second-order logic F
An Introduction to Non-Classical Logic
Logical Labyrinths
Stephen Cook’s lecture notes in computability and logic F
How to Prove It: A Structured Approach
Proofs are Programs: 19th Century Logic and 21st Century Computing F
Mathematics and Plausible Reasoning: Induction and analogy in mathematics
The Cartoon Guide to Löb’s Theorem F
Symbolic Logic: An Accessible Introduction to Serious Mathematical Logic F
Foundations
Foundations of mathematics FE
Mathematics: A Very Short Introduction E
What Is Mathematics? An Elementary Approach to Ideas and Methods F
The Mathematical Experience
What is Mathematics: Gödel’s Theorem and Around F
Metamath (Constructs mathematics from scratch, starting from ZFC set theory axioms) F
The Mathematical Atlas (Clickable Map of Mathematics) F
Miscellaneous
Introductory Mathematics: Algebra and Analysis (Bridges the gap between school & university work.)
Naive Set Theory
Proofs from THE BOOK, Martin Aigner
Principles of Mathematical Analysis, Walter Rudin
A Classical Introduction to Modern Number Theory
Reading List: Graph Isomorphism
A Measure Theory Tutorial (Measure Theory for Dummies) F
Topology Without Tears F
Category Theory for Beginners F
Category Theory for the Mathematically Impaired (A Short Reading List) F
TheCatsters’ Category Theory Videos F
Foundations of Algebraic Geometry F
Elements of Information Theory
The “no self-defeating object” argument, and the vagueness paradox F
Vanity and Ambition in Mathematics (A few posts by multifoliaterose.) F
Decision theory
Remember that any heuristic is bound to certain circumstances. If you want X from agent Y and the rule is that Y only gives you X if you are a devoted irrationalist then ¬irrational. Under certain circumstances what is irrational may be rational and what is rational may be irrational. Paul K. Feyerabend said: “All methodologies have their limitations and the only ‘rule’ that survives is ‘anything goes’.”
Decision theory F
Decision Theory (LW Wiki) F
Timeless Decision Theory, by Eliezer Yudkowsky F
What is Wei Dai’s Updateless Decision Theory? F
Good and Real (Rationality & Decision Theory)
Newcomb’s paradox F
Newcomb’s Problem and Regret of Rationality F
The Meta-Newcomb Problem (A self-undermining variant.) F
Pascal’s Mugging (Finite version of Pascal’s Wager.) F
Game Theory
Game theory (Wikipedia) F
Game Theory (Stanford Encyclopedia of Philosophy) F
Strategy F
Mixed strategy Nash equilibrium FE
Nash equilibrium F
Prisoner’s dilemma F
Gambit: Software Tools for Game Theory F
Game Theory with Ben Polak F
Game Theory — Open Yale Courses F
Game Theory 101 F
Von Neumann, Morgenstern, and the Creation of Game Theory: From Chess to Social Science F
Game theory: mathematics as metaphor F
The History of Combinatorial Game Theory F
Programming
Programming knowledge is not mandatory for LessWrong but you should however be able to interpret the most basic pseudo code as you will come across various snippets of code in discussions and top-level posts outside of the main sequences.
Python
Python is a general-purpose high-level dynamic programming language.
python.org F
Dive Into Python (Python from novice to pro) F
learnpythonthehardway.org F
A Byte of Python F
Python in a Nutshell, Second Edition
Python for Software Design
Python Cookbook
Learning Python, 3rd Edition
Free eBook Programming Tutorial
for Python Games! F
Probability and Statistics for Python programmers F
Haskell
Haskell is a standardized, general-purpose purely functional programming language, with non-strict semantics and strong static typing.
haskell.org F
hackage.haskell.org/platform/ (All you need to get up and running.) F
Learn Haskell in 10 minutes F
Learn You a Haskell for Great Good! F
Programming in Haskell
Real World Haskell F
The Haskell Road to Logic, Maths and Programming
Pearls of Functional Algorithm Design (Techniques of reasoning about programs in an equational style.)
Write Yourself a Scheme in 48 Hours F
Haskell tutorial by Conrad Barski F
General
Programming Language Pragmatics, Michael L. Scott
Practical Foundations for Programming Languages F
Structure and Interpretation of Computer Programs F
How to Design Programs (An Introduction to Computing and Programming) F
projecteuler.net (Learn programming and math by solving problems) F
GitHub (Social Coding) F
The FTP Site (Functional Programming) F
Syntax and Semantics of Programming Languages
Bootstrapping (compilers) F
Low-level programming language F
Assembly language F
Quine (computing) (Self-producing program) F
Probabilistic Programming FE
A Field Guide to Genetic Programming F
Computer science
One of the fundamental premises on LessWrong is that a universal computing device can simulate every physical process and that we therefore should be able to reverse engineer the human brain as it is fundamentally computable. That is, intelligence and consciousness are substrate-neutral.
Computer science FE
Introduction to Computer Science & Programming: Free Courses FE
Exploring Computational Thinking FE
What is computation? FE
Complexity Explained: The Complete Series F
Computation Finite and Infinite Machines, Marvin Minsky
Introduction to the Theory of Computation, Michael Sipser
The Hidden Language of Computer Hardware and Software, Charles Petzold E
Programming Language Pragmatics, Michael L. Scott
Introduction to Algorithms, Thomas H. Cormen
Concrete Mathematics: A Foundation for Computer Science (Mathematics that support advanced computer programming and the analysis of algorithms.)
Computability, Complexity, and Languages: Fundamentals of Theoretical Computer Science
An Introduction to Kolmogorov Complexity and Its Applications
Theoretical Computer Science (Q&A site for theoretical computer scientists and researchers in related fields.) F
The Original ‘Lambda Papers’ F
The Design of Approximation Algorithms F
(Algorithmic) Information Theory
An Introduction to Information Theory FE
Information vs. Meaning FE
Omega and why maths has no TOEs FE
What is Solomonoff Induction? FE
Occam’s Razor F
Decoherence is Simple F
Kolmogorov complexity F
An Introduction to Kolmogorov Complexity and Its Applications
Solomonoff Induction (An introduction to Solomonoff’s approach to inductive inference.) F
Algorithmic information theory F
Algorithmic probability F
Solomonoff Induction (SIAI Blog) F
Information theory F
Entropy in thermodynamics and information theory F
The Unknowable (Free book by Gregory Chaitin) F
Physics
General
The Road to Reality
The Feynman Lectures on Physics
Usenet Physics FAQ F
So You’d Like to Learn Some Physics… F
100 Videos for Teaching and Studying Physics F
From Eternity to Here (The Quest for the Ultimate Theory of Time)
Carl Sagan’s Apple Pie FE
General relativity
Introduction to Differential Geometry and General Relativity F
Lecture Notes on General Relativity F
The General Relativity Tutorial F
Modern Physics: General Relativity F
Quantum physics
The Quantum Physics Sequence F
And the Winner is… Many-Worlds! (MWI) F
The Everett Interpretation F
“Quantum Computing since Democritus” course notes F
Consistent Quantum Theory F
Lecture series on quantum mechanics from Oxford’s undergraduate course. F
Learning Material on Quantum Computing F
Foundations
Foundations of Physics (Journal Devoted to the Conceptual Bases and Fundamental Theories of Modern Physics) FEM
FQXi (Foundational Questions Institute) FEM
Theory of everything (TOE) FEM
Theories of Everything and Godel’s theorem FM
List of unsolved problems in physics F
The Born Probabilities FM
Scott Aaronson on Born Probabilities FE
Eliezer Yudkowsky and Scott Aaronson on Born Probabilities (Video talk.) FE
Born rule (One of the key principles of quantum mechanics.) F
Spin-statistics theorem F
Why we need the spin-statistics theorem FE
Entropy F
Entropy (arrow of time) F
Beyond the Reach of God FE
Information and the Nature of Reality: From Physics to Metaphysics
The Universes of Max Tegmark FEM
The mathematical universe (Level IV Multiverse/Ultimate Ensemble/Mathematical Universe Hypothesis) FEM
Evolution
Darwin’s Dangerous Idea, Daniel Dennett
The Greatest Show on Earth: The Evidence for Evolution, Richard Dawkins E
29+ Evidences for Macroevolution FE
Evolution: 24 myths and misconceptions FE
Micro- and macroevolution (Image) FE
Evolutionary Theory: Mathematical and Conceptual Foundations
Talk.origins (Discussion and debate of biological and physical origins.) FE
Human Evolution Education Resources F
Genetic Algorithms and Evolutionary Computation F
Evolution of Adaptive Behaviour in Robots by Means of Darwinian Selection
Inner Fish: A Journey into the 3.5-Billion-Year History of the Human Body
The Making of the Fittest: DNA and the Ultimate Forensic Record of Evolution
Evolution: What the Fossils Say and Why It Matters
Why Evolution Is True
Universal Darwinism F
Bayesian Methods and Universal Darwinism F
Evolutionary Psychology: A Primer FE
Philosophy
General
Gödel, Escher, Bach: An Eternal Golden Braid
Good and Real (Demystifying Paradoxes from Physics to Ethics)
nickbostrom.com F
Quantum Mechanics and Philosophy: An Introduction F
Metaphilosophical Mysteries FE
The Mind
The Mind’s I: Fantasies and Reflections on Self & Soul
Sweet Dreams: Philosophical Obstacles to a Science of Consciousness
The Ego Tunnel: The Science of the Mind and the Myth of the Self
Consciousness (Stanford Encyclopedia of Philosophy) F
7681 free papers on consciousness in philosophy and in science. F
Neuroscience of Ethics
Intelligence (Definitions) FE
Epistemology
Levels of epistemic accuracy.
The Simple Truth (This essay is meant to restore a naive view of truth.) FE
Probability is in the Mind (Probabilities express ignorance, states of partial information.) F
Not technically a lie FE
Falsehood FE
Bullshit (Not even wrong) FE
Evidence (What is Evidence?) F
Formal Epistemology F
In Defense of Objective Bayesianism
Bayesian Epistemology
The “no self-defeating object” argument, and the vagueness paradox F
Knowledge and Its Limits, Timothy Williamson M
Being an Absolute Skeptic FE
Ned Hall and L.A. Paul (On what contemporary philosophy thinks about causality.) F
Linguistics
Language: the Basics, R. L. Trask E
The Language Instinct, Steven Pinker E
A Brief History of Grammar F
babelsdawn.com (A blog about the origins of speech.) F
Language Log (A collaborative languageblog) F
Neuroscience
Neuroscience for Kids (For students and teachers who would like to learn about the nervous system.) FE
Principles of Neural Science (All the details of how the neuron and brain work.)
Essentials of Neural Science and Behavior (The fundamentals of biology in mental processes.)
Reverse Engineering the Brain (Ideas regarding the sufficient “hardware” and information processing capabilities to build a human equivalent computational substrate.) F
Bayesian brain F
The Bayesian brain: the role of uncertainty in neural coding and computation F
General Education
The Best Textbooks on Every Subject F
250 Free Online Courses from Top Universities F
VideoLectures—exchange ideas & share knowledge F
Online degrees and video courses from leading universities. F
Khan Academy FE
YouTube – EDU F
iTunes U F
The Harvard Extension School’s Open Learning Initiative F
Free Electric Circuits Textbooks F
Podcasts from the University of Oxford F
Ask a Mathematician / Ask a Physicist F
Miscellaneous
Not essential but a good preliminary to reading LessWrong and in some cases helpful to be able to make valuable contributions in the comments. Many of the concepts in the following works are often mentioned on LessWrong or the subject of frequent discussions.
Good and Real (Rationality & Decision Theory)
Reasons and Persons (Ethics, rationality and personal identity.)
Predictably Irrational E
Influence: The Psychology of Persuasion
The Demon-Haunted World: Science as a Candle in the Dark E
A New Kind of Science FM
Conway’s Game of Life F
Anthropic principles agree on bigger future filters FM
Cognitive Science in One Lesson FE
Concepts
Elaboration of miscellaneous terms, concepts and fields of knowledge you might come across in some of the subsequent and more technical advanced posts and comments on LessWrong. The following concepts are frequently discussed but not necessarily supported by the LessWrong community. Those concepts that are controversial are labeled M.
Rationality FE
The map is not the territory FE
Utility theory F
Utilitarianism FM
Antiprediction F
Cellular automaton F
Paradise-engineering FEM
Simulation Argument FM
Anthropic Principle FM
Boltzmann brain FEM
Self-Indication Assumption FM
Many-worlds interpretation (MWI) F
Quantum suicide and immortality FEM
Cryonics (We Agree: Get Froze) FE
Prediction market FE
Bootstrapping (compilers) F
Pascal’s mugging F
Websites
Relevant websites. News and otherwise. F
yudkowsky.net (Eliezer S. Yudkowsky)
theuncertainfuture.com (Visualizing “The Future According to You”)
overcomingbias.com
singinst.org (The SIAI, Singularity Institute for Artificial Intelligence)
acceleratingfuture.com
nickbostrom.com
Meteuphoric
wrongbot.com
Transhumanist Resources
BLTC Research (Global technology project to abolish the biological substrates of suffering.) M
Fun & Fiction
The following are relevant works of fiction or playful treatments of fringe concepts. That means, do not take these works at face value.
Accompanying text: The Logical Fallacy of Generalization from Fictional Evidence
Fiction
Harry Potter and the Methods of Rationality (A LessWrong Community Project) FE
Luminosity (A Twilight Fanfiction Story by Alicorn) FE
Three Worlds Collide (A story to illustrate some points on naturalistic metaethics and diverse other issues of rational conduct) FE
The Finale of the Ultimate Meta Mega Crossover (Vernor Vinge x Greg Egan crackfic) FM
Permutation City (Accompanying text) (The famous science fiction novel by Greg Egan.) M
Diaspora (Accompanying text) (Another influential hard science fiction novel by Greg Egan.) M
A Fire Upon the Deep (This novel by Vernor Vinge has set the stage for a new generation of SF.) M
Neverness, David Zindell M
Free Hard SF Novels & Short Stories FEM
orionsarm.com (Hard science fiction collective worldbuilding project.) FEM
Fun
The Strangest Thing An AI Could Tell You FEM
The AI in a box boxes you FEM
How Many LHC Failures Is Too Many? FEM
Hamster in Tutu Shuts Down Large Hadron Collider FEM
Eliezer Yudkowsky Facts FEM
A Much Better Life? FEM
Go
A popular board game played and analysed by many people in the LessWrong and general AI crowd.
What Is the Game of Go? FE
The Interactive Way To Go FE
Rationality Lessons in the Game of Go F
An overview of online go servers F
AITopics Go (If you want to understand intelligence, the game of Go is much more demanding.) F
Computer Go F
Go software (Extensive list of Go software) F
Go Software (A commercial Go-playing program for PC, iPhone, iPad.)
Note:
This list is a work in progress. I will try to constantly update and refine it.
If you’ve anything to add or correct (e.g. a broken link), please comment below and I’ll update the list accordingly.