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How it looks if decisions are made from memory

How it looks if decisions are made from memory. Arndt Bröder & Stefanie Schiffer (2003) Department of Psychology, University of Bonn broeder@uni-bonn.de Thanks to: Jutta Bierwirth, Arvid Herwig, Andrea Kurth, Susanne Neufang & Nathalie Ziegler (data collection) DFG (funding). Overview.

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How it looks if decisions are made from memory

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  1. How it looks if decisions are made from memory Arndt Bröder & Stefanie Schiffer (2003) Department of Psychology, University of Bonn broeder@uni-bonn.de Thanks to: Jutta Bierwirth, Arvid Herwig, Andrea Kurth, Susanne Neufang & Nathalie Ziegler (data collection) DFG (funding)

  2. Overview • The Adaptive Toolbox idea • Take The Best and other heuristics • The „Memory Search“-Hypothesis • Experiment 1: Pilot study • Experiment 2: Memory vs. screen • The Format-Hypothesis • Experiment 3: representational format • Summary & Perspective

  3. 1. The Adaptive Toolbox • Gigerenzer & Selten (2001) view the human mind as an „adaptive toolbox“ with • domain-specific simple heuristics • that follow simple decision rules(„fast“), • need little information(„frugal“), • and are applied adaptively.

  4. Open questions (selection): • Selection mechanism for heuristics? („meta-rule“) • Status of toolbox: Theory? Framework? Applicability? Empirical Predicitions? • Empirical evidence?

  5. 2. The „Take The Best“-Heuristic • Domain: probabilistic inferences with uncertain knowledge • Which way leads to the city center: Left or right? • Which share will be more profitable: Volkswagen or BMW? • Which nation has a higher per capita GDP: Norway or Spain? • Which city has more inhabitants: Heidelberg or Bonn? • Which food contains more cholesterol: Fish `n Chips or pumpkin pie? • etc. • Make a „best guess“ according to probabilistic cue knowledge • How is the cue knowledge integrated?

  6. Example • Which European country has the higher per capita GDP? • Take The Best (TTB): „Spain“ • Noncompensatory, little info required, ordinal cue weighting • Weighted Additive Strategy (COMP): „Norway“ • Compensatory, high info requirement, absolute cue weighting • Majority Rule (EWL):„Norway“ • Compensatory, medium info requirement, no cue weighting

  7. TTB: Empirical Evidence • Few Studies concerning TTB & LEX: • Rieskamp & Hoffrage (1999) • Bröder (2000 ; JEP:LMC) • Newell, Weston & Shanks (2001) • Läge, Christen & Daub (2002) • Newell & Shanks (2003; JEP:LMC) • Newell, Rakow, Weston & Shanks (in press) • Bröder (in press, JEP:LMC) • (COARSE-GRAINED!) SUMMARY: • TTB appears to belong to the toolbox. • The „default“, however, seems to be a compensatory strategy which is only abandoned in the case of high information costs (relative to gains)

  8. 3. The „Memory Search“-Hypothesis • The standard experimental paradigm in multi-attribute decision research (Structural Modeling as well as Process Tracing) consists of presenting all relevant attribute information to the participant. • Gigerenzer & Todd‘s criticism (1999): • "we refer to this type of task as inference from givens, as opposed to inference from memory or inference from the external environment, both of which require search. (...) [E]xperiments in which search is obviated are unsuitable for testing models of ecological and bounded rationality that rely on limited information search as a central component." (p. 23) • MSH: TTB (and other fast and frugal heuristics) will be used when inference is from memory

  9. My criticism: • The authors do not even give a hint how this memory search hypothesis could be tested empirically. • Therefore, this looks like an attempt to make the „fast and frugal“ framework immune to empirical critique! • Increasing the precision of a hypothesis involves delineating constraints and deriving new predictions.

  10. Methodical problems & solutions: • Problem 1: Participants‘ knowledge base must be known to the experimenter •  Participants learn attribute patterns of objects by heart • Problem 2: How can strategies be inferred when (a) response errors are allowed and (b) Process Tracing is impossible? •  Bayesian model selection method based on likelihood of empirical choice vectors, given the models (=measurement model)

  11. Paradigm • Criminal story: • A popular singer was murdered by one of his 10 former lovers...

  12. Experiment 1: Pilot study • Aim: • Material testing: Can it be learned in a reasonable amount of time? • Do participants use TTB when deciding from memory? • Participants: • 50 Students of Bonn university (35f, 15m, age 25.5)

  13. Learning phase

  14. Decision Phase

  15. Results Experiment 1 • 64% (!) of participants classified as TTB users • estimated reponse error rate: 18%

  16. Discussion Experiment 1 • Surprisingly high rate of TTB-users seems to confirm the MSH • Caveat: Maybe a materials effect! A direct comparison of „inference from givens“ and „inference from memory“ is necessary.

  17. Experiment 2: Memory vs. Screen • Design: • „Inference from memory“ (replication of Study 1) • vs. • „Inference from givens“ (attribute information available on the screen) • Participants: • 50 Students of Bonn University (35f, 15m, age 24.1)

  18. Results of Experiment 2 • Less TTB-users than in Experiment 1(n.s.), but significant difference between conditions (2(2)=6.25; p<.05; w=0.35) • Estimated response errors: 26% vs. 8% (t(48)=7.33, p<.05)

  19. Discussion concerning the MSH • The Memory Search Hypothesis of Gigerenzer & Todd (1999) was corroborated. • In line with other studies this suggests that memory search causes subjective costs which trigger the use of „fast and frugal“ heuristics Question: Is search in memory always costly?

  20. 4. The Format-Hypothesis • TTB is a sequential heuristic. • Sequential retrieval is plausible for a verbal or propositional information format. • Image-based formats cause simultaneous retrieval of cue information which should trigger the usual preference for compensatory decision making. • Hence: Image-based representation may be a boundary condition for MSH

  21. Experiment 3: Representation format • Design (simplified): • verbal Cue-Info vs. image-based Cue-Info • Realization: • Presentation of items in a way encouraging holistic image-based encoding (Stimuli: www.otto.de, virtual dressing room). • Participants: • 114 Students of Bonn University and other volunteers (76f, 38m, age:24.4)

  22. Learning (1)

  23. Learning (2)

  24. Learning (3)

  25. Learning (4)

  26. Learning (5)

  27. Decision Phase

  28. Results Experiment 3 • Difference consistent with hypothesis (2(2)=10.98, p<.01) • estimated response error: 30%

  29. 5. Summary • Summary: • TTB belongs to the toolbox • It is especially prevalent in decisions from memory when this information is in a verbal/propositional format. • An image-based format leads to more compen-satory DM. • „cognitive algorithms (...) cannot be divorced from the data format on which they operate“(Gigerenzer & Hoffrage, 1995, p. 710)

  30. Perspective • Future projects • How adaptive is the toolbox? • Precise formulation of boundary conditions and empirical testing • Influence of habits and personality differences • Closer connection between decision research and other fields of cognitive pychology • representational assumptions • working memory components

  31. Thank you for your attention!

  32. Appendix • Critical item Types

  33. Item types: • Critical evidence found at scene of crime: Blood type A, Marlboro cigarettes, Chanel perfume, limousine TTB=COMP=EWL TTB≠(COMP=EWL) TTB=COMP; EWL=?

  34. Does an image-based format exist? • Pro: • Con: • Compromise: There is a special format of representation which also contains propositional information (Kosslyn, 1994). It is not a photograph-like copy of the physical world.

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