Lecture 3 Inductive and AbdLecture 3 Inductive and Abductive Argumentsuctive Arguments

Li JianhuiLi Jianhui

ljh98@sina.comljh98@sina.com

http://philosophy.wisc.edu/lihttp://philosophy.wisc.edu/li

Two Gambling StrategiesTwo Gambling Strategies

The extreme conservative: This individual The extreme conservative: This individual refuses to wager unless winning is a sure thing. refuses to wager unless winning is a sure thing. – Its virtue: He will never loose a gamble; Its virtue: He will never loose a gamble; – its limitation: there are gambles he will decline that he its limitation: there are gambles he will decline that he

could have won.could have won.

The thoughtful risk taker: this individual at times The thoughtful risk taker: this individual at times enters into risky gambles hoping to win. enters into risky gambles hoping to win. – Its virtue: it can lead him to win wagers by taking Its virtue: it can lead him to win wagers by taking

risks; risks; – its limitation: he can loose money.its limitation: he can loose money.

Two Gambling StrategiesTwo Gambling Strategies

Limiting to deductive arguments is a conservativLimiting to deductive arguments is a conservative strategy.e strategy.– The virtue: you avoid the risk of reaching false concluThe virtue: you avoid the risk of reaching false conclu

sion from true premisses;sion from true premisses;– The limitation: you decline to say anything that goes bThe limitation: you decline to say anything that goes b

eyond the evidence.eyond the evidence.

Nodeductive arguments are riskier.Nodeductive arguments are riskier.– The gain: you can reach true conclusion that go beyoThe gain: you can reach true conclusion that go beyo

nd what the premisses say;nd what the premisses say;– The risk: you may reach false conclusion from true prThe risk: you may reach false conclusion from true pr

emisses.emisses.

Science is a risky businessScience is a risky business

In science as well as in everyday life, we make nIn science as well as in everyday life, we make nondeductive inference all the time. We often are ondeductive inference all the time. We often are prepared to take risk.prepared to take risk.

Scientists often try to reach conclusions about uScientists often try to reach conclusions about universal laws.niversal laws.

When scientists conclude that a universal law is When scientists conclude that a universal law is true or probably true, based on premisses that dtrue or probably true, based on premisses that describe the observations they have made, they aescribe the observations they have made, they aren’t making a deductively valid argument.ren’t making a deductively valid argument.

Science is a risky businessScience is a risky business

Science is a very ambitious enterprise. SciScience is a very ambitious enterprise. Science ventures beyond what strictly observence ventures beyond what strictly observed in the here and now, just as the conclused in the here and now, just as the conclusion in a nondeductive argument ventures bion in a nondeductive argument ventures beyond the information strictly contained in teyond the information strictly contained in the premisses.he premisses.Detective work is also taking risk.Detective work is also taking risk.There are two sorts of nondeductive infereThere are two sorts of nondeductive inference: indeductive and abductive.nce: indeductive and abductive.

InductionInduction

Inductive inference involves taking a description Inductive inference involves taking a description of some sample and extending that description tof some sample and extending that description to items outside the sample. E.g.: 60%of the couo items outside the sample. E.g.: 60%of the county voters called are democrats.nty voters called are democrats.→About 60% of →About 60% of the county voters are democrats.the county voters are democrats.Inductive strength is not a yes/no matter; argumInductive strength is not a yes/no matter; arguments are either stronger or weaker.ents are either stronger or weaker.Two factors influence inductive strengthTwo factors influence inductive strength – Sample sizeSample size– Representativeness or unbiasedness of the sampleRepresentativeness or unbiasedness of the sample

AbductionAbduction

Inference to the best explanation. E.g.: Mendel’s theory Inference to the best explanation. E.g.: Mendel’s theory of genetic factor. of genetic factor. – A set of observations doesn’t deductively imply a theory;A set of observations doesn’t deductively imply a theory;– But a theory deductively implies some observations. This corresBut a theory deductively implies some observations. This corres

ponds more closely to what Mendel did.ponds more closely to what Mendel did.– So a better representation of Mendel’s inference might go like thiSo a better representation of Mendel’s inference might go like thi

s: The theory entailed a prediction; the prediction came true; hens: The theory entailed a prediction; the prediction came true; hence the theory is probably true. Note that this argument is not dedce the theory is probably true. Note that this argument is not deductively valid (the logical form is on page 27). Successful predictuctively valid (the logical form is on page 27). Successful prediction isn’t absolutely conclusive proof that the theory is true.ion isn’t absolutely conclusive proof that the theory is true.

– On the other hand, if the predictions entailed by Mendel’s theory On the other hand, if the predictions entailed by Mendel’s theory had come out false, that would have followed him to deduce that had come out false, that would have followed him to deduce that the theory is mistaken. That is: a failed prediction is conclusve prthe theory is mistaken. That is: a failed prediction is conclusve proof that the theory implying the prediction is false.oof that the theory implying the prediction is false.

AbductionAbductionThe surprise principle:The surprise principle:– An observation O strongly supports HAn observation O strongly supports H11 over H over H22 if both the following conditions are if both the following conditions are

satisfied, but not otherwise: (1) if Hsatisfied, but not otherwise: (1) if H11 were true, O is to be expected; and (2) if H were true, O is to be expected; and (2) if H22 were true, O wouldn’t have been expected.were true, O wouldn’t have been expected.

– The surprise principle explains why success of “safe” predictions provides less cThe surprise principle explains why success of “safe” predictions provides less compelling evidence than the success of “daring” predictions.ompelling evidence than the success of “daring” predictions.

The only game in town fallacy: The only game in town fallacy: – If you don’t want to accept my explanation about something, you must produce a If you don’t want to accept my explanation about something, you must produce a

more plausible explanation of your own. If you can’t, you have to accept my explamore plausible explanation of your own. If you can’t, you have to accept my explanation. Now we commit an abductively fallacy: the Only Game in Town Fallacy.nation. Now we commit an abductively fallacy: the Only Game in Town Fallacy.

– Abduction is sometimes described loosely as follows: if a theory expains some oAbduction is sometimes described loosely as follows: if a theory expains some observation, and if no rival account is available that can do a better job of explain ibservation, and if no rival account is available that can do a better job of explain it, then you should accept the theory. Although this description of abduction is rot, then you should accept the theory. Although this description of abduction is roughly correct, it makes the mistake of sanctioning the Only Game in Town Fallacughly correct, it makes the mistake of sanctioning the Only Game in Town Fallacy. The fact that no rival account is better than the explanation I conduct doesn’t sy. The fact that no rival account is better than the explanation I conduct doesn’t show my explanation is even minimally plausible.how my explanation is even minimally plausible.