The Philosopher's Toolkit. Julian Baggini
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Название: The Philosopher's Toolkit

Автор: Julian Baggini

Издательство: John Wiley & Sons Limited

Жанр: Афоризмы и цитаты

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isbn: 9781119103233

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СКАЧАТЬ where Dr Fishcake would be that night, but, coming across him by chance, put into action her premeditated plan to kill him. So, it could be the case (1) that both premises are true (the murder was premeditated, and Dr Salmon was the only person who knew where Dr Fishcake would be that night) but (2) that the conclusion is false (Dr Salmon is, in fact, not the murderer). Therefore, the detective has not formed a successful deductive argument.

      SEE ALSO

      1 1.1 Arguments, premises, and conclusions

      2 1.3 Induction

      3 1.4 Validity and soundness

      READING

       * Alfred Tarski (1936/95). Introduction to Logic and to the Methodology of Deductive Sciences

       * Fred R. Berger (1977). Studying Deductive Logic

       * A.C. Grayling (2001). An Introduction to Philosophical Logic

       Warren Goldfarb (2003). Deductive Logic

       * Maria Konnikova (2013). Mastermind: How to Think Like Sherlock Holmes

      I (Julian Baggini) have a confession to make. Once, while on holiday in Rome, I visited the famous street market, Porta Portese. I came across a man who was taking bets on which of the three cups he had shuffled around was covering a die. I will spare you the details and any attempts to justify my actions on the grounds of mitigating circumstances. Suffice it to say, I took a bet and lost. Having been budgeted so carefully, the cash for that night’s pizza went up in smoke.

      My foolishness in this instance is all too evident. But is it right to say my decision to gamble was ‘illogical’? Answering this question requires wrangling with a dimension of logic philosophers call ‘induction’. Unlike deductive inferences, induction involves an inference where the conclusion follows from the premises not with necessity or definitely but only with probability (though even this formulation is problematic, as we’ll see).

      Defining induction

      Perhaps most familiar to people is a kind of induction that involves reasoning from a limited number of observations to wider generalisations of some probability. Reasoning this way is commonly called inductive generalisation. It’s a kind of inference that usually involves reasoning from past regularities to future regularities. One classic example is the sunrise. The sun has risen regularly each day, so far as human experience can recall, so people reason that it will probably rise tomorrow. This sort of inference is often taken to typify induction. In the case of my Roman holiday, I might have reasoned that the past experiences of people with average cognitive abilities like mine show that the probabilities of winning against the man with the cups is rather small.

      But beware: induction is not essentially defined as reasoning from the specific to the general. An inductive inference need not be past–future directed. And it can involve reasoning from the general to the specific, the specific to the specific, or the general to the general.

      I could, for example, reason from the more general, past‐oriented claim that no trained athlete on record has been able to run 100 metres in under 9 seconds, to the more specific past‐oriented conclusion that my friend had probably not achieved this feat when he was at university, as he claims. Reasoning through analogies (see 2.4) as well as typical examples and rules of thumb are also species of induction, even though none of them involves moving from the specific to the general. The important property of inductive inferences is that they determine conclusions only with probability, not how they relate specific and general claims.

      The problem of induction

      Although there are lots of kinds of induction besides inductive generalisations, that species of induction is, when it comes to actual practices of reasoning, often where the action is. Reasoning in experimental science, for example, commonly depends on inductive generalisations in so far as scientists formulate and confirm universal natural laws (e.g. Boyle’s ideal gas law) only with a degree of probability based upon a relatively small number of observations. Francis Bacon (1561–1626) argued persuasively for just this conception of induction.

      1 Almost all elephants like chocolate.

      2 This is an elephant.

      3 Therefore, this elephant likes chocolate.

      This is not a well‐formed deductive argument, since the premises could possibly be true and the conclusion still be false. Properly understood, however, it may be a strong inductive argument – if the conclusion is taken to be probable, rather than certain.

      On the other hand, consider this rather similar argument:

      1 All elephants like chocolate.

      2 This is an elephant.

      3 Therefore, this elephant likes chocolate.

      Though similar in certain ways, this one is, in fact, a well‐formed deductive argument, not an inductive argument at all. One way to think of the problem of induction, therefore, is as the problem of how an argument can be good reasoning as induction but be poor reasoning as a deduction. Before addressing this problem directly, we must take care not to be misled by the similarities between the two forms.

      A misleading similarity

      1 The sun rises every day.

      2 Tomorrow is a day.

      3 Therefore, the sun will rise tomorrow.

      Because of its similarity with deductive forms, one may be tempted to read the first premise as an ‘all’ sentence:

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