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Contents  Page 3 - Video Presentation Monty Python’s Argument Sketch  Page 4 to 5 - What is Reasoning?  Page 6 - Deductive reasoning  Page 7 to 8 - Inductive reasoning  Page 10 to 18 - Deductive versus Inductive reasoning  Page 19 - Community of Inquiry - Problems with inductive reasoning.  Page 20 - Bibliography 2

YOUTUBE Video Monty Python’s Argument sketch  Click on the image to the left. You will need to be connected to the internet to view this presentation.  Enlarge to full screen 3

Reasoning  Reasoning is the cognitive process of looking for reasons for beliefs, conclusions, actions or feelings. Humans have the ability to engage in reasoning about their own reasoning using introspection. Different forms of such reflection on reasoning occur in different fields. Although reasoning was once thought to be a uniquely human capability, other animals also engage in reasoning. 4

Reasoning  In philosophy, the study of reasoning typically focuses on what makes reasoning efficient or inefficient, appropriate or inappropriate, good or bad. Philosophers do this by either examining the form or structure of the reasoning within arguments, or by considering the broader methods used to reach particular goals of reasoning. Psychologists and cognitive scientists, in contrast, tend to study how people reason, which cognitive and neural processes are engaged, how cultural factors affect the inferences people draw. 5

Reasoning Deductive reasoning  Deductive arguments are intended to have reasoning that is valid. Reasoning in an argument is valid if the argument's conclusion must be true when the premises (the reasons given to support that conclusion) are true. One classic example of deductive reasoning is that found in the following: Premise 1: All humans are mortal. Premise 2: Socrates is a human. Conclusion: Socrates is mortal. The reasoning in this argument is valid, because there is no way in which the premises, 1 and 2, could be true and the conclusion, 3, be false. 6

Reasoning Inductive Reasoning  Inductive reasoning contrasts strongly with deductive reasoning. Even in the best, or strongest, cases of inductive reasoning, the truth of the premises does not guarantee the truth of the conclusion. Instead, the conclusion of an inductive argument follows with some degree of probability. 7

Reasoning  A classical example of inductive reasoning comes from the empiricist David Hume: Premise: The sun has risen in the east every morning up until now. Conclusion: The sun will also rise in the east tomorrow.  Relatedly, the conclusion of an inductive argument contains more information than is already contained in the premises. Thus, this method of reasoning is ampliative. 8

A deductive argument is one that contains a deductive inferential claim. A Inductive (nondeductive) argument is one that contains a nondeductive inferential claim. 9

Deductive vs. Inductive (nondeductive) inferential claims  A deductive inferential claim is the claim, made by the arguer, that the truth of the conclusion follows with the force of absolute logical necessity from the assumed truth of the premises.  An Inductive (nondeductive) inferential claim

... is the claim, made by the arguer, that the truth of the conclusion follows with some significant degree of probability from the assumed truth of the premises. 11

Inductive inferential claims are either “strong” or “weak.” 12

when the truth of its conclusion follows necessarily from the assumed truth of its premises. 1. If Polly is a cat, then Polly is an animal. 2. Polly is a cat. 3. Polly is an animal. is valid. 13

when the truth of its conclusion DOES NOT follow necessarily from the assumed truth of its premises. 1. If Polly is a cat, then Polly is an animal. 2. Polly is an animal. 3. Polly is a cat. is invalid. 14

when the truth of its conclusion follows with some significant degree of probability from the assumed truth of its premises. 15

1. Millions of crows have been observed. 2. All of them have been black. 3. All crows are black (probably). is strong. 16

when the truth of its conclusion DOES NOT follow with any significant degree of probability from the assumed truth of its premises. 17

1.The great majority of college professors are politically liberal. 2.Patricia Quinn is a college professor. 3. Patricia Quinn is (probably) politically liberal. is weak. 18

Community of Inquiry Discussion  CLICK ON THIS LINK FOR THE STIMULUS FOR A DISCUSSION ON INDUCTION. (You might like to print this material out and distribute it to the class.) 19

Bibliography  Copeland, Jack Artificial Intelligence:a philosophical introduction. Oxford: Blackwell.  Furley, David 'Rationality among the Greeks and Romans'. In The Gale Group, Dictionary of the history of ideas. University of Virginia Library.  Jeffrey, Richard Formal logic: its scope and limits, (3rd ed.). New York: McGraw-Hill.  Kirwin, Christopher 'Reasoning'. In Ted Honderich (ed.), The Oxford Companion to Philosophy. Oxford: Oxford University Press.  Manktelow, K.I Reasoning and Thinking (Cognitive Psychology: Modular Course.). Hove, Sussex:Psychology Press  McCarty, L. Thorne 'Reflections on TAXMAN: An Experiment on Artificial Intelligence and Legal Reasoning'. Harvard Law Review. Vol. 90, No. 5.  Scriven, Michael Reasoning. New York: McGraw-Hill. ISBN