Psychology 3130A/B Chapter Notes - Chapter 6: Conjunction Fallacy, Catfield, First Statement

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Chapter 6: Inference and Induction
- Induction is about predicting the future
Role of Induction in thinking
Inferences and conclusions
Use induction to make inferences
Inferences are conclusions based on available evidence
Generalization
Induction is also used when we make generalization
Generalization is also an inductive conclusion, but rather than describing a specific prediction,
generalization is a broad conclusion about a whole class or group of things
Rely on it to make inferences about how people will behave and react
Rely on inductive reasoning to discover something new by thinking
How induction works
Hue’s prole of idutio
David Hume considered induction to be one of the greatest problems
o Unlike deductive logic, which many believed could be explained by formal operations, induction
seemed to defy this
Hume gave a description of what he called the problem of induction
o Induction = act of relying on past experience to make inferences and conclusions about future
o Thought this was circular reasoning
b/c it works if the future resembles the past; but Hume claimed that this only works because the future
reseles the past …i the past
problem with this is we cant use these past inductive successes to predict future inductive successes
relying on induction to explain induction
says we rely on induction because we have a habit, but instead would argue that our cognitive system
is designed to track regularities in the world, and make conclusions and predictions on basis for those
regularities
Basic Learning mechanisms
all cognitive systems rely on the fundamental processes of associative learning
a relate it to lassial oditioig; ted to talk aout oditioed respose, also fair to sa it’s a
simple inductive inference (make prediction, generate explanation)
Stimulus generalization
conceptual advantage of relating induction to basic learning theory is that we can also talk about the
role of similarity and stimulus generalization
can also relate it to operant conditioning; rat makes inferences about presentation of food following
various lights
universal law of stimulus generalization generalization gradient
o Rat pressing level when its red (been reinforced) but also when it was similar shade of red
Something fundamental and universal about generalizing the new stimuli as a function of how similar
they are to previously experienced stimuli
Tendency to base predictions about future on similarity to past events should also obey this universal
law of stimulus generalization
Gooda’s prole of idutio
According to Hume, induction may be a habit, but its difficult to explain in logical terms without
resorting to some kind of circular argument
Nelson Goodman raised similar concern
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His eaple: iagie ou are a eerald eaier, eer oe ou’e see so far is gree
o So we can say all emeralds are green; this is saying all we have seen are green and any we will
see will be green
This inductive inference is made with confidence
But there is a prole, osider alteratie propert alled grue
If you say, all emeralds are grue, it means that all the emeralds that you have seen so far are green and
all emeralds that have not yet been seen are blue: green emeralds in the past, but blue emeralds from
this moment forward
Goodmans point, is that at any given time this property of grue is true
Both properties are true given the evidence of green emeralds
Notice, past experience (green emeralds) is identical for both properties
His suggestion is that both of these properties green and grue, can be simultaneously true, given
available evidence
Possible all emeralds are green, also possible some are blue, but you have not seen them yet
o These properties also make opposite prediction about what colour the next emerald will be
If green is true, then next emerald will be green; if grue is true then next will be blue
Since both are true, clear prediction cant be made; and yet we will all predict the next emerald will be
green; why? This is a problem of induction
Entrenchment and natural kinds
Hume stated we have a habit to make inductions; current understanding of learning theory suggests
that we naturally generalize
Gooda’s is’t as straight forard, ho do e hoose hih oe of the idutios to ake
Entrenchment = term or property has a history of usage w/in a culture or language
Emerald example: green is an entrenchment term (term we can use to describe many things)
Grue however is not an entrenchment; no history of usage and no general property of grue outside the
emeralds that were grue yesterday and blue tomorrow
o Goodman argued we can only make reliable inductions from entrenchment terms
o
Quine argued that natural kinds are natural groupings of entities that possess similar properties,
much like what we have referred to earlier as a family resemblance concept
o Suggested that objects form a kind only if they have apple properties that can be projected to
all the members (e.g. apple is natural grouping; not apple is not)
o Argued all humans make use of natural kinds; reliable inductions come from natural kinds
Quie’s otio of a atural kid suggests a solutio for Nelso Gooda’s prole of idutio
Quine pointed out that green is a natural property
Green emeralds form a kind via similarity; grue emeralds do not
Categorical induction
Most organisms have a tendency to display stimulus generalization
Basic generalization is sensitive to the similarity b/w the current stimulus and mental representations
of previously experienced stimuli
Have shown in other chapters that concepts and categories are often held together by similarity
Productive way to investigate inductive reasoning is to consider that inductions are often based on
concepts and categories
o Known as literature as categorical induction
Structure of an induction task
For the present purposes, we can define categorical induction as the process of which people arrive at
a conclusion or a statement of confidence about whether a conclusion category has some given
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