Critical Thinking | Tom Chatfield

Critical Thinking | Tom Chatfield

Date Finished: Jan 20, 2022
Author: Tom Chatfield
Tags: LINK to the board

  1. Chatfield T. Critical Thinking: Your Guide to Effective Argument, Successful Analysis and Independent Study / T. Chatfield, First edition-е изд., Los Angeles ; London: SAGE Publications Ltd, 2017. 328 c.

🚀 The Book in 3 Sentences

🎨 Impressions

How I Discovered It

Who Should Read It?

I think anyone who wishes to study critical thinking should start with [[Thought and Knowledge An Introduction to Critical Thinking]] by Halpern. Otherwise this book might appear as very good, though after Halpern it oversimplified. Nonetheless, there are several interesting additions to critical thinking framework, and even several useful ideas on note-taking.

☘️ How the Book Changed Me

How my life / behaviour / thoughts / ideas have changed as a result of reading the book.

✍️ My Top 3 Quotes

📒 Ideas

On taking notes

![[How to Take Smart Notes#Some updates from Critical Thinking by Tom Chatfield]]

On critical thinking

  • Is not about changing who we are, it’s about understanding our limitations, knowing that we not always act from rational standpoint [[What is rationality#^9923aa]] all the time, but most of the time we act irrationally and harshly. Critical thinking is about stopping and thinking at the right time, and reach for questions in order to be able to work out what is wrong.
  • It is also the ability to control the environment, a skill that helps understand where attention is at the moment and what is the main source of distraction and how to avoid and remain focus no matter what.
    • Help build a frame of mind where return from distractions is fast and smoothness.

One idea that came into mind while reading, is to make peer to peer review in classroom possible. Show children that mentoring and being a mentor is the best way to learn.

  • Difference between argument and non-argument entities
    • Non-argument
      • Descriptions
      • Summaries.
        • Good summary answers the following questions:
          • What is the purpose of the summary?
          • What are the key point needed to understand what is going on?
          • Is there any relevant detail that can be left out, or some essential information to be added, in order to make in concise and clear as possible?
      • Opinions and beliefs.
      • Clarifications and illustrations.
  • Another important part of critical thinking that has been omitted by Halpern is the explanation part.
    • We can call it reasoning backwards.
    • Explaining something to somebody as hard to understand it.
  • What is a good explanation?
    • It is able to account all evidence in a particular case, and doesn’t ignore inconveniences.
    • It is economical. No unnecessary steps, no additional and meaningless assumptions.
    • Rule of thumb, strive for simplicity rather than to complexity.

Three ways of reasoning

  • Reasoning plays a critical role in explaining anything to anybody. ^39c9c5
    • Inductive reasoning is where conclusion can be drawn from logical consequences, premises. If an argument is valid then all premises are true, therefore the conclusion also must be true, though only if an argument valid in itself. ![[Эффективные рассуждения теория правила и контекст#^8a8f90]] ^ea08e6
    • Deductive reasoning supported by premises and cannot be proven true. It must be true if an argument well-structured, all premises are true, inductively forceful (one follows another and do not contradict), and reasonably acceptable. ![[Эффективные рассуждения теория правила и контекст#^9533a6]]
    • Abducting reasoning. ^395fbc
      • Leads away from the existing theory.
      • Seeks the best possible explanation, by moving away from evidence, to the theory and asks «Why things the way they are?»
      • Formulated the simplest explanation with given facts. If facts fit and acceptable, it is time to start testing to find out the truth.
      • Application of the abducting reasoning starts by asking, «What is the best explanation for this?«
      • Following framework, provides step-by-step instruction to successfully accomplish the research.
        • Start with a precise explanation of what is needed.
        • Suggest why it is important, underline significance or the reason why it must be interesting.
        • Present the train of thoughts that lead to possible explanation, from theory to hypothesis.
        • Come up with experimental method, or non-experimental approach that have extensive pool of diverse sources of evidence.
        • Investigate if the current explanation takes into account sources of evidence. If you cannot investigate in all the detail, prediction at this stage might suffice.
        • Acknowledge limitation of your approach, they are always there. Maybe you missed other possible explanation that might be more convincing and take into account presented evidence in more solid manner, or provide more sound results. ![[What is rationality#^9923aa]]
        • If so, then outline possible investigation you’ll conduct in the future. Think about new tests, refine or change the theory, or outright forget about it and seek something different. If your previous one has proven successful or true. Should I forget a research or a problem if I can’t find a solution?
  • [[How to Actually Change Your Mind — Eliezer Yudkowsky#^395267]]

Explanation, theory, hypothesis

[[Critical thinking could not be taught#^44c967]]
The best way to explain how hypothesis work is to compare these three parts of any hypothesis.

  • Explanation.
    • The most general description of the event.
    • It might be considered just an attempt to explain.
      • Formally.
      • Or informally.
    • Example: The planets orbit the sun because of gravity.
  • Theory.
    • Theory is formulated out of basic explanation and usually larger with bigger level of abstraction.
    • Theory touches underlying nature of particular phenomenon.
    • Example: All matter is attracted towards other matter by gravitational force, in proportion to the quantity of matter involved.
  • Hypotheses. ^7e56d2
    • Is testable and precise formulation of a theory.
    • Any hypothesis is designed to allow an investigation of the presented fact in the controlled environment and as rigorously as possible.
    • The purpose is to explain natural phenomenon in widely accepted way, that community will support.
      • Good theory helps make prediction and understand current results for future inquiries.
    • Example: It will be possible to explain unexpected perturbations in the orbit of one of the planets in the solar system using Newton’s theory of gravitation.


  • It’s not the goal of a research to rely on any hypothesis.
    • Sometimes better results could yield more open approach in exploration of a problem.
  • The most important skill for medicine, psychology (anthropological part of it), philosophy.
  • It relies heavily on scientific method.
      • Can the same results be replicated?
      • What testable prediction can be made from the base theory?
      • What evidence is there that is able to falsify the theory?
        • Goes by the name of null-hypothesis.
    • Successful attempt at a problem explains all things already known.
    • It is as simple as possible, without over simplification.
      • While, still explaining everything.
      • It sticks to Occam’s razor principle.

Occam’s razor principle

If you choose between two or more possible explanation if any given fact, choose the simplest one. More assumption make something less probable.

  • Example.
    • SIMPLE
      • In our study, users who self-identified as ‘inexperienced with tablets and apps’ were more prone to making simple errors during our first round of testing via a tablet-based app. This may be because consistently using software correctly in the case of a tablet-based app is dependent on a certain level of experience.
      • In our study, users who self-identified as ‘inexperienced with tablets and apps’ were more prone to making simple errors during our first round of testing via a tablet-based app. This may be because such users are likely to have lower intellectual abilities than those with more experience, in turn making them more likely to commit simple errors in comparison to those whose greater experience suggests greater general intelligence.


  • We are creatures not of logic, but of emotions:
    • First, we are bones, muscles and marrow, creatures.
    • Second, we are brain and maybe mind, thinkers.
    • Third, we can rationalize, gauge and response accordingly, rational, critical-thinkers.
  • Irrationality is driven by emotions, morals, intuitions, subjective and objective.
  • Rhetoric encompasses our strive to master language, drive to seek cause of our decisions and cause change in others. ![[How to speak How to listen#Rhetoric by Aristotle]]
  • Tom Chatfield proposes, that we change the order of rhetoric.
    • Start with Ethos, introduce, present your expertise.
    • Then continue with logic, show the credibility of your speculation.
    • Finish with pathos. Emotionally and powerfully, there is certain truth behind this order.
  • Adler looks at the same order from a different angle. He swaps last to entities. In my opinion, the ending must be emotionally charged. ^950837
    • What Adler forgot to tell us is about Kairos.
      • Kairos is a moment, I think after emotional part, where persuasion begins in honest or actually happens.
  • Three key question to ask about persuasion. You should look into them before answering any advice, accept or decline it, or check information and argument.
    • What am I reading, listening, watching? Type?
    • Why author using thus particular language, and who is their intended audience?
    • According to what criteria or value I should measure and judge his or her words?

Always aim to non-involvement (impartiality), be a specter, observe, register and think. Don’t act instantly. (p.163).

Speech and writing is full of informal and formal fallacies.


Six questions worth asking if you are letting yourself be guided down the slippery slope of wrong conclusions and arguments.

  • Is an emotional, traditional or personal position being presented as a general truth without any proof?
  • Is a claim judged not due to its validity, but because of the source?
  • Is part of the premises used as a belief? And a person doing this thinks that he is using reasoning.
  • Is anything hammered as a relevant conclusion while it is not?
  • Is any vivid analogies are used to describe a real word? Check for usage of metaphors and generalizations.
  • Is it too good to be true? Usually it isn’t? There is no simple answers to a complex problem.


  • Problems usually start when we begin testing theories and in building hypotheses.
  • We face different results.
    • False positive. Positive result, that produces an error. Often in testing various health conditions, such as pregnancy.
    • False negative. Negative result, that produces an error. Same with pregnancy.
    • True positive. A result that is correctly corresponds to the state of affairs.
  • To avoid multiple errors, Bayes’s theorem was invented by 18th century philosopher and minister Thomas Bayes.
    • This theorem deals with an issue of chance, or to be more exact, how to update our probabilistic beliefs in the light of new evidence. (p.199).

Conscious awareness

  • This provided us with the ability to make fast decisions with small groups of humans, to co-operate on the ground of common causes.
  • In short, it looks like that.
    • Speed and simplicity over slowness and complexity.
    • We are influenced by local and immediate instead of future gains.
    • We see things not as they are, but as a narrative weaved by our brain and patterns provided by it too.
      • They reflect what we already know.
      • We extend them to the past and extrapolate to the future.
    • We don’t see, but select what we wish to see.

Heuristics that explain our shortsightedness

  • Affect heuristic.
    • Strong influence of emotions, even when they are misleading. Celebrity conditioning.
  • Availability heuristic.
    • Easiness with which certain fact comes to mind. Recent and usually negative events come much faster than something positive.
  • Anchoring heuristic.
    • First encountered information considered more than everything that comes next.
  • Representative heuristic.
    • Conformity. How strong something correlates with a present belief. (p. 208)

Heuristics help gain awareness in two ways that could turn to be useful in life.

  • Be aware.
    • Of shortcuts, our mind does. That could give insight on our choices.
  • Be alert.
    • To be able to put strategies in place, timely.
    • Resist deliberate and accidental causes. Avoid mistakes that could be done due to the cognitive bias.


  • Re-framing information. After you hear anything that doesn’t feel right, pause and select different emphasis.
    • Look for intentions behind words. They frame your decision.

Cheat sheet to avoid cognitive bias

[[Читерский лист для избежания одного из когнитивных искажений или почему записывать важно]]

Cheat sheet might help trigger an interesting response to any framing that is done to you or the one that you do yourself. Buster Benson a technologist invented it.

  • There is too much information here. That support our belief.
    • Pay attention to notable changes.
    • Strikingly odd things.
    • Constant or infrequent repetitions.
  • There is not enough meaning out there. We fill left gaps for us on purpose.
    • With patterns.
    • Generalization.
    • Assumptions.
    • Simplifications. ^7a3b80
    • Projection of current mindset.
  • We don’t have enough time. And because of that, we assume the correctness of stated things.
    • We look into where our competency lies.
    • Reach for what is easily touched. To what in our grasp.
    • We think that we should finish what we have started.
  • We can’t remember or track everything. Furthermore, we recall experiences selectively.
    • Generalize on the basis of examples and archetypes.
    • Rely on technology as a form of external memory.

Small numbers

Three principle for dealing with them

  • Be aware of amount of data. Small number show greater variability than large ones.
  • If an exceptional result is involved, always assume that you are dealing with small numbers.
  • Don’t explain that doesn’t need explaining. Focus on larger prey or longer-term results. Collect sizeable data to suggest significance.


  • Human’s mind can’t deal with something that never happened before. If say the situation hasn’t been planned beforehand, we won’t be able to predict any possibility of it happening under any circumstances.
  • Some principles exist that can help learn something from non-event.
    • Assess strategies irrespective of the outcome. Don’t put too much hope and emphasis on the positive outcome. Take into account an alternative history, Kahneman proposed a negative experiment protocol. [[Препарирование живого проекта negative experiment]]
    • Pay attention to rates of failure in the field, don’t get into a trap of survivor mistake. Don’t be fascinated by success, look at failure. Success is rare where failure is common.
    • Short term outcome is dominated by luck and random variation. Long term outcome, by sound strategy and skill. By looking at long term and large scale trends, we can hope to find meaningful patterns. Beware of small number fallacies.
      • How to avoid short-term thinking?
        • Plan and take into account surprises and serendipity. Not a single event or trend is going to prevail. Eventually, it ends at some point.
        • In the bulk of data, carefully consider a one-off extreme. It can be a game breaker and ruin everything you’ve worked for.
        • Means and normal distribution make intuitive sense, but don’t describe most of what happen in any complex system.
        • Look into the past. The longer something has lasted, the longer it is to go on lasting. It is time proof, weathered a great number of shocks and surprises. (p.243)

From data to knowledge via fake news


  • What’s the difference between data, knowledge, and information.
  • Take a look at these raw numbers: 8091, 8848, 8167, 8611, 8586, 8485, 8163, 8126, 8188, 8516
  • And if we put them like this? 8848, 8611, 8586, 8516, 8485, 8188, 8167, 8163, 8126, 8091
  • And what if I said that they are heights of the tallest mountains in the world would you believe me?

Claude E Shannon, the father of modern theory of knowledge, separated all three definitions.

  • Raw data is facts or figures awaiting processing.
    • Data is made, not found: it is manufactured by careful measurement, as a result of a particular process. Infallibly accurate record.
  • Information is data that structured in specific way and within certain context, that it is easily understood.
    • The same as data it is created but in contrast it is meticulously arranged and contextualized. Information exists in the absence of knowledge.
    • Information is riddled with noise, and in order for it to become useful we have to discern signal among nonstopable clamor of everything and everyone. ![[Essentialism The Disciplined Pursuit of Less#^839ae0]]
      • Taleb echoes this ![[Antifragile books 2 and 3#^f81513]]
      • Look up words NOISE in antifragile book. For more information.
      • [[The Poverty of Historicism — Karl Popper#^4e5d3f]]
  • Knowledge is verified information that we have good reason to believe is true. ^387fd7
    • Verification is a reliable process for testing the truth of information. [[Critical thinking#Explanation theory hypothesis]].
    • The process of gaining knowledge is messy and open-ended. It involves a lot of questions about what is possible for us to know, how we know it, and where and how different sources of information disagree. ![[What is knowledge?#^b26d96]] ^b38b8a
    • It requires information, and relies heavily on particular decisions about how and what we measure, test and know things in the first place.
      • This frames knowledge around specific assumptions.
      • Thus, important to be as transparent as possible about assumptions because no knowledge is final, neutral, and exhaustive.

Everything that asks for social proof have to answer two questions:

  • Are you correctly interpreting other people’s beliefs?
  • Are these beliefs reasonable, to begin with?
  • Yet there is another side to the question of data – information – knowledge that has been discussed on the forum.
    • data — information (What, where, when?) — knowledge (how?) — wisdom (why?).
    • ![[data-info-know-wise.png]]

Nice addition for deeper understanding of [[What is knowledge?]] will be [[Синтезированное знание]]

Ten ways to resist system biases online in then easy steps

  1. Don’t let emotional impact dominate your online actions: if the topic is an important one, focus on verification and the provenance and basis of others’ claims.
  2. Dig into edit histories and follow-up references: try to find out how and where information that may be widely accepted actually came into being.
  3. Go beyond the easy and instant: always aim to browse beyond the first page of search results, the most-cited sources and the most popular solutions.
  4. Allow yourself to engage deeply and serendipitously with themes and topics that interest you, rather than simply trying to cover the ‘greatest hits’ in a field.
  5. Go big and small: deliberately use small networks and services in parallel with large ones. Draw on a diversity of individual recommendations, reviews and curated links.
  6. You can use social media to break out of your echo chamber: deliberately follow people and sources from different perspectives and backgrounds to your own.
  7. Don’t get institutionalized: it may be where your friends spend all their time, but don’t end up using just one service more than you do everything else put together.
  8. Become more aware of your filters: see how search results and recommendations may be being customized based on your history or preferences, and how you can turn this off.
  9. Live beyond the moment: dig into the past, take the longer view, deliberately search back through years rather than months. Resist the perpetual pressure of the present.
  10. Always ask of data: which things are and are not being measured, how is this being done, and what might be the biases and limitations of the resulting claims? (p. 256)

Different search and discovery strategies

Mindful approach to looking for information is quite basic thing that must be taught at school to the primary pupils. It doesn’t just help you find useful information or particular, related to your topic data, more importantly in puts you on track what you actually should have looked all that time.

This paradigm divides search and discovery algorithms.

  • Search strategies are about finding known things or information that we are aware about.
  • Discovery strategies are about finding things we have to learn about, they lay a field of research and investigation, They all about exposing ourselves to new perspective that differs from current point of view.

To understand the difference between two paradigms, we have to take into account categories of knowledge and ignorance.

  • Identified knowledge.
    • Known knowns. Typically, one click away.
  • Identified ignorance.
    • Known unknowns. Things we know that we lack knowledge about, and thus we explicitly set ourselves to investigate. Careful search strategy should be in place. Good way to start thesis.
  • Unidentified knowledge.
    • Unknown knowns. Things that we have learned about but that stay in a field of information. Contextualized, not verified, therefor not changed into knowledge yet.
  • Unidentified ignorance. ^3deaa8
    • Things that we don’t know that we do not know and are likely to find out about belatedly, if at all.
    • Those unknowns matter the most in the long term.

On good writing

Be sure that you understand what you wish to say.

Good recipe is to write in the preface the problem we are facing then in each chapter’s first paragraphs clearly state what we are dealing with in the specific passage.

  • The most common mistake at every level is failing to think sufficiently about the question we are addressing, or making unwarranted assumptions about what is and is not required.
  • It’s a good habit to determine premises before proceeding to the writing itself.
    • Paraphrase in own words the problem you are addressing.
    • Confirm how mush you are willing of aiming to write, don’t forget about deadline.
    • Check the success parameters of your work. Feedback, what readers expect to receive. Make a list of all this things.
    • Compare your work with at least several successful examples in the same field, get a sense where are you aiming to.
    • Don’t waste time writing full manuscript, make small commitment everyday. Don’t waste time wondering of getting confused.
  • Constantly revise and iterate, with reference to the following questions.
    • What are the most important things that I want to say?
    • In what order does it make sense to say them?
    • Which evidence best supports these points?

Seven practical principles for rewriting

  1. Be brief: look for unnecessarily wordy phrases that can be replaced by simpler, shorter ones – and for waffle and unnecessary qualifications that detract from your points.
  2. clear: look for long, complex sentences that would be better off as several shorter ones.
  3. Clarity isn’t the same as precision: it’s much more important to say clearly what you mean than to obsess about defining every term precisely.
  4. Stay on point: look for unnecessary or distracting content that can be removed entirely.
  5. Guide your reader: use signposting words and links to clarify the flow of your ideas.
  6. Revise radically: don’t be afraid to shift around sentences and paragraphs as much as needed to improve structure and flow.
  7. Re-read yourself closely: it’s a waste of time to skim your own writing when you’re editing. Re-read yourself slowly and closely. It may help to print your work out and go through it line by line with a pen in hand.

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