Self Help

I Think, Therefore I Laugh - John Allen Paulos

Author Photo

Matheus Puppe

· 19 min read

“If you liked the book, you can purchase it using the links in the description below. By buying through these links, you contribute to the blog without paying any extra, as we receive a small commission. This helps us bring more quality content to you!”



This passage summarizes the comparison between Ludwig Wittgenstein and Lewis Carroll, as well as introducing Bertrand Russell and Groucho Marx as another unlikely pair. Some key points:

  • Wittgenstein and Carroll both explored topics of nonsense, logical confusion, and language puzzles, though Wittgenstein was tortured by these issues while Carroll delighted in them.

  • Many passages from Alice’s Adventures in Wonderland and Through the Looking Glass illustrate the type of philosophical jokes Wittgenstein thought could make up an entire philosophical work. Several examples of such passages are quoted.

  • Bertrand Russell and Groucho Marx are presented as another unlikely pair to be compared. Few details are given about their comparison yet.

  • The passage establishes the theme of exploring unlikely pairings of thinkers and using humor/jokes to illuminate philosophical problems, as per Wittgenstein’s comment that a serious philosophical work could consist entirely of jokes.

So in summary, it introduces the two unlikely pairings that will be discussed further, between Wittgenstein/Carroll and Russell/Marx, as a way to exemplify Wittgenstein’s idea of using humor for philosophical purposes.

These examples summarize a couple key principles of logic:

  1. The law of non-contradiction - Something cannot both be true and untrue at the same time.

  2. The law of excluded middle - For any statement, it is either true or untrue. There is no middle ground.

It provides three examples of applying these principles:

  1. A humorous example of a rabbi using logic to reason out his situation after waking up drunk in a cemetery.

  2. An example suggesting the law of excluded middle means future events are already determined, which is problematic. Statements about future truths are meaningless.

  3. A minority view of some mathematicians who reject applying the law of excluded middle to statements that cannot be constructively proven true or false, like the existence of a string of numbers in pi’s decimal expansion.

So in summary, it introduces the two basic logic laws, provides examples of their application, and notes some caveats about how they should not be applied uncritically, like with statements about unknowable future events.

Here is a summary of the third and most common use of the law of the excluded middle as being valid presented above:

  • For some philosophers and logicians, truth is a matter of constructive provability. In other words, for a proposition to be considered true, it must be possible to construct a proof of its truth.

  • Under this view, the law of the excluded middle is valid because for any proposition P, either P can be constructively proven true or P can be constructively proven false. There is no third option of P being undetermined or indeterminate.

  • Quantum physics also rejects the applicability of the law of the excluded middle in some contexts. Ever since the 1920s, some logicians have formally studied three-valued logics where a proposition can be true, false, or undetermined.

  • However, classical logicians who accepted the law of the excluded middle sometimes mocked these alternative logics. For example, they joked that a Polish logician who believed in three truth values must think there are three people in the room - the logician, the Pope, and someone else.

  • In summary, for this third view, the law of the excluded middle is considered valid because for any proposition, it should be possible to construct a proof of its truth or falsity, with no third option of being undetermined. Truth is a matter of constructive provability under this view.

  • The passage discusses different types of logical arguments and fallacies, including self-referential statements like Epimenides’ paradox “All Cretans are liars” and related liar paradoxes.

  • It gives examples of ambiguous or nonsensical logical statements like “This argument is helopita” that seem to both be and not be valid.

  • Self-referential statements about the truth or falsity of sentences within themselves can lead to paradoxes, as can certain conditional statements.

  • Even non-paradoxical statements combined in certain ways, like Socrates saying what Plato said is false if Plato said what Socrates will say is true, can create paradoxes.

  • The passage discusses how logical reasoning can sometimes reveal ambiguities in language rather than leading to more conclusions, and how mathematicians in particular may struggle with common sense due to their tendency towards literal interpretations.

  • Examples are given of language that seems contradictory but is commonly used, like signs saying “violators will be towed” when no one is literally being towed.

  • Relationships between paradoxes, double binds, and situations requiring contradictory behavior are briefly explored.

The passage discusses self-referential paradoxes and situations where something communicates or references itself in a contradictory way. It uses examples like jokes, dramatic performances, and art to illustrate how they contain both literal content but also framing cues that say “this is not to be taken seriously” or as everyday communication.

It then discusses Russell’s paradox involving sets that do or do not contain themselves as members, and how this leads to a contradiction. It explains Russell’s theory of types which resolved this by establishing a hierarchical structure of sets of different types or orders to avoid sets containing themselves.

Finally, it discusses the distinction between object language, which are statements within a system being studied, and metalanguage, which are statements about that system or object language statements. Interpreting statements at the proper language level is important to avoid paradoxes caused by self-reference, as shown in the examples involving Groucho Marx jokes and Lewis Carroll’s Tortoise.

Here is a summary of the key points about meaning, reference, and Dora Black’s first husband from the passage:

  • Meaning and reference are difficult philosophical notions to pin down precisely. Meaning is often identified with verification, which the logical positivists saw as a way to eliminate metaphysics, but the verifiability principle itself cannot be verified.

  • Two expressions can have the same reference/referent but different meanings. For example, “the morning star” and “the evening star” refer to Venus but have different meanings. Likewise, “the younger coauthor of Principia Mathematica” and “the first husband of Dora Black” both refer to Bertrand Russell.

  • Terms may occur extensionally in a sentence if replacing them with a co-referring term does not change the truth value. However, outside of mathematics, substitution may fail to preserve truth value, as shown by examples involving Elizabeth Taylor and the King of France.

  • Expressions can have meaning without having a referent, according to some philosophical accounts. Russell’s “The present King of France is bald” is given as an example - it is meaningful but lacks a referent.

  • The key example used is that “the first husband of Dora Black” refers to Bertrand Russell, demonstrating relationships between meaning, reference, and descriptions involving people.

Here is a summary of the key points about rge?:

  • rge? is asking about the meaning or intent behind a word, phrase, or statement. It represents a logical question mark.

  • Examples are given of phrases that superficially seem to make sense grammatically but don’t logically make sense when you think about what they actually mean.

  • Pairs of phrases are contrasted where one is logically coherent and the other isn’t, to illustrate how logical analysis differs from just grammatical analysis.

  • Some examples play on ambiguous or unclear references to illustrate logical problems.

  • The point is that natural language often obscures logical inconsistencies, so explicit logical analysis and clarification of meanings/references is important.

  • Asking “rge?” prompts breaking down statements, questions, or claims into their logical components to check if they hold up to logical scrutiny beyond just superficial linguistic/grammatical analysis.

So in summary, “rge?” represents asking a question about the logical coherence, meanings, implications or intent behind a statement, not just its surface structure or grammar. It’s a logical consistency check.

Here is a summary of some key points about Hume’s views on induction and causality:

  • Hume argued that inductive reasoning, which forms conclusions beyond the information given in the premises, cannot be rationally justified. Trying to justify induction inductively is circular.

  • We rely on induction in daily life to assume patterns observed in the past will continue, like the sun rising tomorrow, but Hume notes there is no deductive argument for this.

  • Hume analyzed causation as merely a relationship of constant conjunction between events - we observe A and B regularly occurring together, but there is no necessary connection.

  • This view raises issues for scientific laws, which seem to imply relationships beyond just descriptions of observed patterns (they support counterfactual conditionals).

  • The ontological status of scientific laws is unclear - they are more than summaries of observations but less than logical necessities.

  • Hume’s insights unsettle common assumptions about induction and causation and exemplify philosophy’s role in realizing what is implicit in our thinking, not just providing facts or guidance. His views remain influential and problematic.

  • The bulvon was pleased with the three suggestions for properly courting a girl: showing her family respects her, discussing philosophy shows intellectual respect, and sharing food is a sign of companionship.

  • However, when the bulvon met the girl, he bungled the interaction by abruptly asking if she likes noodles or has a brother, without properly establishing any connection first.

  • The passage discusses how scientists and biologists sometimes make incorrect causal inferences. Just because something alleviates a condition does not necessarily mean the lack of that thing causes the condition. Correlation does not imply causation.

  • Examples are given of dopamine and schizophrenia, and aspirin reducing headaches without lacking aspirin actually causing headaches.

  • Similar flawed causal reasoning can occur in the social sciences as well. Overall the passage cautions against assuming that what alleviates a condition is necessarily the cause, as that kind of thinking can lead to incorrect conclusions.

  • The passage discusses several paradoxes and counterintuitive examples involving concepts like confirmation, knowledge, statistics, and probability.

  • One example involves “grue” and “bleen” - strange color terms defined based on time periods. Observations support both grue/bleen and normal color terms equally well.

  • Carl Hempel’s raven paradox notes that observations of non-black objects somehow statistically confirm the statement “all ravens are black.”

  • Gettier cases show that justified true belief is not sufficient for knowledge - one can have a justified true belief that is true by accident.

  • Statistics and probability involve both a pure formalism and real-life interpretations/applications, where problems can arise from inappropriate interpretations rather than the mathematics itself.

  • Even simple examples like densities can go wrong if the application/interpretation is flawed, separating the mathematics from proper usage.

  • Batting averages over different half-seasons can make intuitive comparisons misleading if not considering the full dataset and time period.

The question suggests that it should not be possible for Gehrig’s average to be higher than Ruth’s over the season, but provides an example to show how it can theoretically happen.

Specifically, it describes a scenario where Ruth hits better than Gehrig during the first half of the season (.344 vs .342 average), but worse during the second half (.250 vs .238).

When calculated over the full season, Gehrig’s overall average of .300 is higher than Ruth’s .287, even though Ruth outperformed Gehrig during the first half.

This demonstrates how averages can be misleading when calculated over different sample sizes or time periods. Even though Ruth hit better during the first half of games, Gehrig’s full-season average was higher due to Ruth’s relatively poor performance in the second half.

So while intuitively it seems Ruth should have the higher average if he hit better for part of the season, this example shows how averages can be manipulated to produce counterintuitive results when calculated over unequal splits of data.

Here are summaries of the passages provided:

  • Erosion and Civilization - No details were provided about this title.

  • A Critique of Tolerant Purity - No details were provided about this title.

  • Social Origins of Mental De-activation - No details were provided about this title.

  • The story describes a debate between a Mulla (Islamic scholar) and a Roman scholar, where the Mulla uses metaphorical responses to show his knowledge and understanding, even though the meanings were not actually explained. It highlights how different perspectives or levels of understanding can both be “right.”

  • Conventionalism is discussed as the view that scientific laws are conventions that reflect choices in descriptions, similar to how perspectives on time sequences can vary. Notation is important for communicating ideas.

  • Reductionism, behaviorism, and opportunism in philosophy of science are briefly introduced. Reductionism aims to reduce complex phenomena to more basic explanations, but is not always feasible or illuminating. Behaviorism defines psychology through observable behavior alone, which is an incomplete approach. Opportunism refers to pursuing explanations where it is convenient rather than where the true keys may lie.

  • Genes and culture, and reductionism carried to further extremes, are used as examples of oversimplified reductionist accounts. Complete determinism is debatable and multiple perspectives are needed.

  • The story at the end notes that simply accumulating observations is not enough for scientific progress - theories, assumptions, problems, and supportability are also needed. Popper’s emphasis on falsifiability is referenced.

Karl Popper argued that scientific theories must be falsifiable in order to be considered scientific. They cannot be completely unfalsifiable, as some metaphysical beliefs are.

Popper criticized Marxism and psychoanalysis for not being falsifiable. For example, when a Marxist prediction does not come true, Marxists can attribute it to a reaction of the ruling class rather than admit falsification. Similarly, psychoanalysts can attribute unexpected behavior to “reaction formations” rather than admitting a theory is false.

Popper was also opposed to “historicism,” the idea that there are immutable laws of history that allow for long-term social predictions. He argued scientific advances are not predictable and affect social development in unpredictable ways.

In summary, Popper held that for a theory to be considered scientific, it must be capable of being shown false through empirical testing and evidence. Unfalsifiable theories are more philosophical or metaphysical in nature rather than scientific according to Popper’s view.

  • Gödel’s incompleteness theorem shows that within any formal axiomatic system of arithmetic, there will be statements that are true but cannot be proved or disproved within the system.

  • This indicates that systems like formalized physics theories that include arithmetic cannot be “provably deterministic” - they cannot prove that every question has a determined answer based on the laws and axioms.

  • Even asking a deterministic “know-it-all” computer a self-referential question like what its own output will be in the future leaves the question undetermined by its programming.

  • Quantum mechanics demonstrates physical indeterminism - some microscopic phenomena are fundamentally probabilistic and random, contrary to determinism.

  • Bell’s inequality proves that deterministic “hidden variable” theories intended to restore determinism to quantum mechanics are logically and physically impossible. Quantum mechanics incorporates inherent randomness and probabilistic behavior at its core.

So in summary, both logical/mathematical considerations like Gödel’s theorem and empirical evidence from quantum mechanics point to limits on determinism and indicate some degree of inherent randomness, uncertainty or indeterminism in physical systems and nature.

  • The device consists of 3 unconnected parts - detectors A and B, and a central box C that emits particles.

  • When the button on C is pressed, it simultaneously emits particles to A and B. The dials on A and B can be set independently before or during particle flight.

  • When particles arrive, a light flashes red or green on A and B depending on the dial settings.

  • Repeated trials show lights match when dials match, but differ 1/4 of the time when dials differ, contrary to expectation of ≥1/3.

  • This violates assumptions of “hidden variables” determining particle properties and detector outputs. No model explains the 1/4 result other than quantum mechanics.

  • The device behavior is strange and realism about independent physical objects is challenged. Physicists are left slightly mystical or pragmatically accepting the quantum formalism.

The passage discusses how some physicists take a hardline positivistic approach to interpreting quantum mechanics, relying strictly on empirical rules and formulas without providing explanatory models. This leaves the door open for some nonphysicists to interpret certain quantum experiments as indicating telepathy or instant communication, even if these interpretations do not provide any useful information transmission.

The passage further argues that addressing philosophical assumptions and developing new conceptual frameworks, like non-classical logic, may be necessary to fully understand quantum phenomena in the way that developments in mathematics helped resolve paradoxes in classical physics. It uses several analogies and thought experiments to illustrate how unexamined assumptions can shape one’s theories and observations in potentially misleading ways. Overall, it advocates being careful about assumptions and open to revising theoretical frameworks.

  • The passage describes an early experiment in machine translation where a Russian phrase was translated to English and then back to Russian, resulting in a humorous mistranslation due to contextual nuances.

  • Capturing metaphor, context, background knowledge is very challenging for AI compared to formal rule-based tasks like chess.

  • Passing the Turing test requires not just factual knowledge but understanding context and significance in conversation.

  • There is a tendency to dismiss tasks as not “real intelligence” if they can be formalized and performed by a computer, but complex integrative skills should also be considered a form of intelligence.

  • Future high-status jobs may reward integrative skills over specific formalized skills as computers take over more routine work.

  • The distinction between hardware and software in computers parallels the mind-body problem - what is the relationship between logical programs and physical states?

So in summary, it discusses the challenges of context and common sense knowledge for AI, sketches what would be needed to pass the Turing test, and draws parallels between the mind-body problem and hardware/software distinction in computers.

Here are the key points about intensional vs causal explanations:

  • Intensional explanations give reasons or rationales for behavior based on the agent’s beliefs, intentions, social/cultural context. They presume rationality. Examples include George explaining the man touched his head to signal in baseball.

  • Causal explanations cite underlying physical/chemical causal laws without reference to mental states or rationality. Waldo’s explanation is causal, citing neuron firings and muscle contractions.

  • There is no conflict between the two; both can explain the same behavior but one may be more appropriate depending on context.

  • Intensional explanations allow for variability and context dependence in interpretation of behavior as a rational action. Causal explanations are more fixed.

  • Intensional explanations determine an action by the reasons an agent considers it rational, then identify those reasons as the cause. Causal explanations cannot determine actions.

  • Intentional notions are essential for communication and interpretation, unlike causal explanations which do not depend on descriptions.

  • Subject-object confusion can arise in intensional explanations requiring empathy with another’s perspective. Causal explanations avoid this issue.

So in summary, intensional explanations consider rational motives while causal explanations cite physical determinants, but both can be valid depending on context and purpose of explanation. Intentional aspects are important for understanding behavior.

  • Causal explanations generally don’t have the property of affecting what they explain, unlike intentional explanations. A rock’s trajectory is not affected by calculations or explanations of it.

  • Intentional explanations are probabilistic for several reasons:

    1. The subject-object blur - explaining or observing something can change what is being explained/observed, especially regarding oneself and close ones.

    2. Explanations provide rationales, not sufficient causes, and rationales don’t ensure the action will occur.

    3. Microphysical indeterminism may allow for metaphysically free will through a filtering process in the mind-brain.

  • Low probability conclusions don’t necessarily mean a poor explanation. Our genetics resulted from an improbable accident but that accident is still the explanation.

  • Explanations don’t need to have highly probable conclusions to have value. The explanations for rolling dice have the same value regardless of probability of the outcome.

The passage discusses the challenges of aggregating individual preferences into group preferences and decisions. It provides examples to illustrate voting paradoxes and dilemmas that can arise:

  • Condorcet’s paradox shows how majority voting can lead to irrational or intransitive societal preferences. In an election with 3 candidates, the preferences of voters could result in each candidate being preferred by a majority over the others in pairwise comparisons.

  • Arrow’s impossibility theorem proves that no voting system can always satisfy certain reasonable criteria like transitivity, non-dictatorship, and independence of irrelevant alternatives.

  • The prisoners’ dilemma shows how rational self-interest at the individual level can lead to suboptimal outcomes for the group. Both prisoners confessing dominates cooperating, but if they could cooperate and stay silent, they would both be better off.

It notes skepticism is warranted when trying to predict groups and societies, as individual preferences must be aggregated and there are inherent difficulties and paradoxes involved. The passage emphasizes the challenges but also importance of translating individual preferences and interests into collective outcomes and decisions.

  • The incongruity at the heart of jokes is analogous to philosophical problems - they both expose contradictions or paradoxes.

  • The argumentative/aggressive tone in many jokes and philosophical papers serves a similar function of intellectual dominance or social control.

  • However, this tone presupposes an independent intelligence in the audience/reader that can engage critically.

  • Both humor and philosophy require the human ability to transcend oneself and one’s situation and see discrepancies between reality and hopes/pretensions.

  • The authors (Wittgenstein, Russell, Carroll, Marx) discuss whether philosophy addresses “big questions” about meaning, life, death, etc. or smaller logical/conceptual questions.

  • It is argued that progress on smaller questions may sometimes clarify the big questions, while empty talk about the big questions does not help.

  • Groucho Marx questions if any of this will make a difference in 50,000 years, but Lewis Carroll argues that what happens then does not determine what is meaningful now.

  • Groucho then departs to pursue a romantic encounter, leaving the philosophers to ponder.

Here is a summary of the key points from “In Machinery and Intelligence”:

  • The paper explores the question of whether machines can think, and proposes the “Turing test” as a way to evaluate machine intelligence.

  • Under the Turing test, a human judge would have conversations with both humans and machines without seeing them. If the judge cannot reliably distinguish the machine from the human, then the machine would be considered thinking.

  • Turing argues that the real issues are to do with the performance of machines, not how they are constructed or what they are made of. If a machine can exhibit intelligent behavior that is indistinguishable from a human’s, then it should be considered thinking.

  • He addresses counterarguments like the idea that thinking requires a human-level intelligence or consciousness. Turing responds that we cannot define thinking precisely enough to rule out the possibility of it occurring in non-biological systems like computers.

  • The ability to have an intelligent conversation is used as a practical definition of intelligence and thinking, without needing to resolve philosophical issues about consciousness or the nature of the human mind. If a machine passes the Turing test, it shows it has achieved human-level intelligence in a practical sense.

So in summary, the paper proposes the Turing test as a way to evaluate machine intelligence based on behavior rather than construction, and argues that if a machine can exhibit intelligent conversation, it should be considered thinking for practical purposes even if its internal workings are different from the human brain.

Author Photo

About Matheus Puppe