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David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
David Hume
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David Hume

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  • 1. Causality The relationship between cause and effect. The principle that all events have sufficient causes. The differentia (distinguishing properties/characteristics) of causality which all causal relations have in common: The relationships held between events, objects or states of affairs. The first event A (the cause) is a reason that brings about the second event B (the effect) The first event A chronologically precedes the second event B (in some cases, a simple spatial or even conceptual separation is accepted: "Tides are caused by the moon", "Day is caused by the rotation of the Earth", "Lightning causes thunder") Events like A are consistently followed by events like B The cue ball causes the eight ball to roll into pocket." "Heat causes water to boil." "The Moon's gravity causes the Earth's tides." "A hard blow to the arm causes a bruise." "My pushing the accelerator caused the car to go faster."
  • 2. CONDITIONING AND CAUSATION • Causality detection is vital to behavioral adaptation in humans. • Can associative learning principles in animals teach us something about how people detect causes? • Recently, methods and principles of operant and Pavlovian conditioning in animals have been applied to causality detection in humans.
  • 3. CONDITIONING AND CAUSATION • How plausible is this connection? • In text, we have argued that associative learning is ―causality detection.‖ • Animals appear to be learning about causes of important events in world. • In Pavlovian conditioning, causes are environmental stimuli. • In operant conditioning, causes are organism‘s own actions.
  • 4. CONDITIONING AND CAUSATION • How can we evaluate this account? • One can directly study human causal judgment using methods inspired by animal learning research.
  • 5. David Hume and Causality • Familiarity with David Hume‘s ideas is helpful in order to comprehend causality detection. • More than any other thinker, this 18th century Scottish philosopher has shaped our understanding of causality detection.
  • 6. David Hume and Causality General • Causation is psychological impression. type of • Succession of experiences is given; learning but, impression of connection goes across all beyond sensory evidence. animals • For example, lightning regularly precedes thunder. • We associate one with the other; but, we do not sense their interconnection. Unconsoius, Black box ; A form of learning that does not relie on logic and reason (language) Associative modular
  • 7. Causality • Pavlov contiguity of events • Skinner contiguity of consequences • HUME Causality
  • 8. David Hume and Causality • Three conditions are crucial to forming causal impressions: • 1. Cause and effect must be contiguous in space and time. • 2. Cause must occur prior to effect. • 3. There must be a constant connection between cause and effect.
  • 9. David Hume and Causality • Three other conditions better define and sharpen causal attributions: • 4. Same cause produces same effect, same effect comes from same cause. • 5. When several different events produce same effect, it must be due to something that events share. • 6. Any difference between effects of similar events must arise because events differ from one another.
  • 10. David Hume and Causality • Mechanical model of causal perception: • Completely non-conscious processes lead us to automatically associate consistently contiguous experiences. • This learning is too important to leave to rational thought. Understanding cause and effect is essentail for all organisms to suvive
  • 11. David Hume and Causality • Hume‘s principles suggest that a single pairing of cause and effect will not forge a firm causal association. • A causal impression rises to its greatest strength by degrees as a function of number of cause-effect pairings. • Consistency of relation affects ultimate strength of causal association; any inconsistency weakens connection.
  • 12. David Hume and Causality • Also relevant to strength of causality judgment is superiority of one possible cause above rival candidates. • If several events often precede a given event and if one does so more reliably than others, then it will be singled out as the cause.
  • 13. David Hume and Causality • Three conditions are crucial to forming causal impressions: CONSISTENCY • 1. Cause and effect must be contiguous in space and time. • 2. Cause must occur prior to effect. SUPERIORITY • 3. There must be a constant connection between cause and effect. NUMBER
  • 14. David Hume and Causality • Three other conditions better define and sharpen causal attributions: • 4. Same cause produces same effect, same effect comes from same cause. • 5. When several different events produce same effect, it must be due to something that events share. • 6. Any difference between effects of similar events must arise because events differ from one another. CONSISTENCY NUMBER SUPERIORITY
  • 15. David Hume and Causality • Hume‘s ideas are similar to RescorlaWagner model of associative learning: • Is completely mechanical and phrased as a simple mathematical equation. • Posits gradual growth of associations to an asymptotic level. • Expects unpaired events to lower Extincition strength of associative learning. • Involves competition among causes. Blocking
  • 16. David Hume and Causality • Hume hypothesized operation of same associative principles in nonhuman animals. • This testified to the breadth of these associative principles, plus their operation in absence of language or logic.
  • 17. EMPIRICAL INVESTIGATIONS OF HUMAN CAUSALITY DETECTION • Just what is known about causality detection beyond its suspected operation in animal conditioning? • We next explore human research directed at causality detection in controlled laboratory settings.
  • 18. EMPIRICAL INVESTIGATIONS OF HUMAN CAUSALITY DETECTION • Contingency • Temporal contiguity • Cue competition
  • 19. EMPIRICAL INVESTIGATIONS OF HUMAN CAUSALITY DETECTION • Contingency • Temporal contiguity • Cue competition
  • 20. Contingency • Statistical relation between events. • Computed from 2 X 2 table.
  • 21. Contingency The 2 x 2 cont ingency table representing th e presence and ab sence of a cause and an effect. Effect present Effect absent Cause present Cell a Cell b Cause absent Cell c Cell d Overestimate A and B (subjects behave)
  • 22. Contingency The 2 x 2 cont ingency table representing th e presence and ab sence of a cause and an effect. Effect present Effect absent Cause present Cell a Cell b Cause absent Cell c Cell d Hume and Rescorla argue that cause and effects are detemined on a trial by trial basis (order of training causes overestimate) Experience by experience Moment by moment Overestimate A and B (subjects behave) Real time
  • 23. Contingency • General formula: a/(a+b)-c/(c+d) • Specific experimental investigation: • P(Light|Tap) and P(Light|No Tap)
  • 24. Experimental questions Must ask organinsm the correct question and provide the opertunity to answer (behave) appropriatly Contingency • Data suggest that people can quite keenly detect prevailing responseoutcome contingency: positive or negative or zero. • Under proper experimental conditions, people can with great accuracy and little bias report positive, negative, and noncontingent response-outcome relations. The 2 x 2 cont ingency table representing th e presence and ab sence of a cause and an effect. Effect present Effect absent Cause present Cell a Cell b Cause absent Cell c Cell d
  • 25. Contingency Learning Curves • Do people show negatively accelerated learning curves in contingency judgment tasks?
  • 26. ∆Vn = K( — Vn-1)
  • 27. Contingency Learning Curves • Do people show negatively accelerated learning curves in contingency judgment tasks? • Yes.
  • 28. Humans not perfect, Some Bias Past experience (firing caused tanks to explode) Just rated last trial
  • 29. Contingency What happen last trial + • Effects of differential conditional What has happened in the past = probability and increased training Future likelyhhod are exactly what would be expected if people‘s causality and Humans more Flexiable contingency judgments were Probaliy not just an ‗assocaitive based on an associative learning modular process like that captured in But cognition,emotion, motivation, Rescorla-Wagner model. bias affect learning • Conditioned inhibition also occurs.
  • 30. EMPIRICAL INVESTIGATIONS OF HUMAN CAUSALITY DETECTION • Contingency • Temporal contiguity • Cue competition
  • 31. Thomas Procedure With Humans Subjects could make outcomes (points) move forward in time and did (cause and effect) but doing so reduced the total amount of points CONTROL
  • 32. Thomas Procedure With Humans • Results are like those with rats. Temporal • Contiguity promotes operant contiquity can ‗overshadow‘ contingency responding. in assocaition formation • Contiguity also leads to more positive causal ratings, despite no Hume (superioty) actual contingency. • Both results also hold with negative contingency.
  • 33. EMPIRICAL INVESTIGATIONS OF HUMAN CAUSALITY DETECTION • Contingency • Temporal contiguity • Cue competition
  • 34. Cue competition • Relative validity effect • Blocking
  • 35. Relative validity effect Differentially (A,B) Non Differentially 15.7 • Group C: AX+ versus BX• Group U: AX+/- versus BX+/• More control by X in Group U despite equal association of X with + and – (at first) • True of rats, rabbits, and pigeons in conditioning experiments • True of human causal attributions
  • 36. Blocking 15.8 Predicitive (learning) • AX+ alone Diagnostic (no prior • A+, then AX+ causality assumtions) • Responding to X is greater in first case for animals in conditioning experiments • And, for humans in causal judgment experiments
  • 37. LEARNING AND COGNITION: A THEORETICAL PERSPECTIVE • Studies on human causality detection are consistent with Hume‘s theoretical approach plus literature on Pavlovian and operant conditioning in animals. • Concordances are not peculiar to findings discussed in Chapter 15. • Also extends to overshadowing, configural conditioning, and occasion setting.
  • 38. LEARNING AND COGNITION: A THEORETICAL PERSPECTIVE • An additional concordance is that Rescorla-Wagner model is also a promising theory of causality detection in human beings. • So, basic mechanisms of association formation may have just as much to say about causality detection in human beings as they do about conditioning in animals.
  • 39. LEARNING AND COGNITION: A THEORETICAL PERSPECTIVE • This is as it should be if fundamental mechanisms of learning and behavior are truly general. • Hume‘s belief in generality of associative learning and its centrality to mind and behavior is thus supported by work we have reviewed in our course and textbook.

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