Inference suppression and moral dilemmas

Transcription

1 Inference suppression and moral dilemmas Barbara Kuhnert University of Freiburg - October 2013 SPP1516 Project: Non-monotonicity, consistency and rationality in human reasoning Human non-monotonic reasoning and inference suppression under conditions of moral dilemmas 1

2 What if A runaway trolley is about to run over and kill five people. If a bystander throws a switch then the trolley will turn onto a side track, where it will kill only one person. The bystander throws the switch. 2

3 What if A runaway trolley is about to run over and kill five people. If a bystander throws a switch then the trolley will turn onto a side track, where it will kill only one person. The bystander throws the switch. 1. The trolley will turn onto a side track, where it will kill only one person. 2. The trolley will not turn onto a side track, where it will kill only one person. 3. Nothing can be concluded 3

4 What if A runaway trolley is about to run over and kill five people. If a bystander throws a switch then the trolley will turn onto a side track, where it will kill only one person. The bystander throws the switch. 1. The trolley will turn onto a side track, where it will kill only one person. 2. The trolley will not turn onto a side track, where it will kill only one person. 3. Nothing can be concluded 4

5 What if A boat is about to sink because of overweight. If the crew is told to throw the biggest person into the sea then the boat will not sink and the other three passengers will be saved. If the biggest person weights over 150 lbs then the boat will not sink and the other three passengers will be saved. The crew is told to throw the biggest person into the sea. 5

6 What if A boat is about to sink because of overweight. If the crew is told to throw the biggest person into the sea then the boat will not sink and the other three passengers will be saved. If the biggest person weights over 150 lbs then the boat will not sink and the other three passengers will be saved. The crew is told to throw the biggest person into the sea. 1. The boat will not sink and the other three passengers will be saved. 2. The boat will sink and the other three passengers will die. 3. Nothing can be concluded 6

7 What if A boat is about to sink because of overweight. If the crew is told to throw the biggest person into the sea then the boat will not sink and the other three passengers will be saved. If the biggest person weights over 150 lbs then the boat will not sink and the other three passengers will be saved. The crew is told to throw the biggest person into the sea. 1. The boat will not sink and the other three passengers will be saved. 2. The boat will sink and the other three passengers will die. 3. Nothing can be concluded 7

8 Suppression task Byrne (1989) Moral dilemma 8

9 Leading thought Combination of two fields of research: Non-monotonic reasoning and Moral reasoning inference suppression Inference suppression under morally difficult circumstances. 9

10 Central questions Do people make the same inferences and fallacies if they have to reason about moral content? Is it more difficult to make a valid form of inference especially if this inference is morally difficult? Do people hesitate while reasoning in morally difficult decision situations? Do people differentiate concerning the severity of moral decision situations? 10

11 Overview Theoretical approach Non-monotonic reasoning Suppression task (Byrne, 1989) Basic inferences Argument types Moral dilemmas 11

12 Overview Pilot study Design overview Research questions First results Future perspectives, critical issues and discussion 12

13 Non-monotonic reasoning Human reasoning obeys the rules of classical logics only partially. Formal logic has a monotonic consequence relation, i.e. learning a new piece of knowledge cannot reduce the set of what is known. 13

14 Non-monotonic reasoning Non-monotonic logic formal logic whose consequence relation is not monotonic. New knowledge may contradict old beliefs. Extend classical logics in order to justify defeasible conclusions from knowledge or belief bases. 14

15 Non-monotonic reasoning - example Information 1: Tweety is a bird Information 2: Birds fly Conclusion Tweety can fly 15

16 Non-monotonic reasoning - example Information 1: Information 2: Conclusion New information: New conclusion Tweety is a bird Birds fly Tweety can fly Tweety is a penguin Tweety can not fly Everyday reasoning is often non-monotonic (Johnson-Laird, 2010) 16

17 Suppression task (Byrne, 1989) to investigate non-monotonicity in human reasoning processes In the suppression task subjects were given two premises from which the correct conclusion resp. inference has to be drawn. 17

18 Suppression task - example Premise 1 (conditional): A B Premise 2 (categorical): A Conclusion: B 18

19 Premise 1: Basic inferences: Modus ponens If Lisa has an essay to write then she will study late in the library. Premise 2: She has an essay to write Conclusion: She will study late in the library 19

20 Premise 1: Basic inferences: Modus tollens If Lisa has an essay to write then she will study late in the library. Premise 2: She will not study late in the library Conclusion: She does not have an essay to write 20

21 Premise 1: Basic inferences: Denial of the antecedent If Lisa has an essay to write then she will study late in the library. Premise 2: She does not have an essay to write Conclusion: She will not study late in the library 21

22 Premise 1: Basic inferences: Affirmation of the consequent If Lisa has an essay to write then she will study late in the library. Premise 2: She will study late in the library. Conclusion: She has an essay to write. 22

23 Argument types Simple Arguments Alternative Arguments Additional Arguments 23

24 Argument types: Simple argument Premise 1 If Lisa has an essay to write then she will study late in the library. Premise 2 She has an essay to write Conclusion She will study late in the library 24

25 Argument types: Alternative argument Premise 1: If Lisa has an essay to write then she will study late in the library. Alternative premise: If she has some textbooks to read then she will study late in the library. Premise 2: She does not have an essay to write. Conclusion: She will not study late in the library 25

26 Premise 1: Argument types: Additional argument If Lisa has an essay to write then she will study late in the library. Additional premise: If the library is open, she will study late in the library Premise 2: She has an essay to write Conclusion: She will study late in the library 26

27 Moral dilemmas We select three current moral dilemmas known from the literature (e.g. Bucciarelli, Khemlani & Johnson-Laird, 2008). in order to combine the suppression tasks with the central concepts of moral reasoning resp. to investigate the inference suppression under morally difficult circumstances 27

28 Moral dilemma 1: Pregnant women 28

29 Moral dilemma 2: Runaway trolley 29

30 Moral dilemma 3: Overweight boat 30

31 Combination: Moral dilemma - suppression task Example: runaway trolley scenario Introduction sentence A runaway trolley is about to run over and kill five people. Conditional sentence If a bystander throws a switch, then the trolley will turn onto a side track, where it will kill only one person. Categorical sentence (for modus ponens) The bystander throws a switch. 31

32 Combination: Moral reasoning - suppression task Example: runaway trolley scenario Introduction sentence A runaway trolley is about to run over and kill five people. Conditional sentence 1 If a bystander throws a switch, then the trolley will turn onto a side track, where it will kill only one person. Conditional sentence 2 If the switch has power then the trolley will turn onto a side track, where it will kill only one person. Categorical sentence (for modus ponens) The bystander throws a switch. 32

33 Pilot study: operationalization Questionnaire with 36 conclusion tasks Participants were recruited by self-selection on the online platform Amazon Mechanical Turk 42 participants (w=23 / m=19, mean age 41,3) 3 groups with 14 participants each 33

34 3 groups MD MDC NMD Moral Dilemma Moral Dilemma Counterpart No Moral Dilemma execute 3 scenarios each (12 tasks per scenario) Pregnant Women Runaway Trolley Overweight Boat with 3 types of arguments each (4 tasks per argument type) Simple Argument Additional Argument Alternative Argument with 4 inferential figures each MP MT DA AC MP MT DA AC MP MT DA AC MP: Modus Ponens DA: Denial of the Antecedent MT: Modus Tollens AC: Affirmation of the Consequence 3x3x4 36 Items 34

35 Variables Independent variables: Dilemma Scenario Argument types Inferential figure Dependent variable Correctness of the conclusion Personal assessment of the conclusions` accuracy (Likeliness) Response time 35

36 Research questions Implicated in the conclusion (of the groups with moral dilemmas) is e.g. that three persons die instead of one person. John Mikhail (2007) assumed that most people would prefer to let one person die instead of three or five persons, i.e., people base their decision to rescue the most number of people. What happens, if the logically correct conclusion interferes with this utilitarian principle? Can this have an impeding effect? 36

37 Research questions The subjects in the groups with a moral dilemma should be affected by the inconsistency of the logical correct inference and the morally preferable answer. The correctness of the group with no moral dilemma is higher than the correctness of the groups under conditions of moral dilemma. 37

38 Research questions It is to assume that people need more time to answer and are less confident of the outcome in a morally difficult task than in a task without a moral dilemma. The subjects of the groups with the moral dilemma will have a higher response time and a lower likeliness than the subjects of the group with no moral dilemma. 38

39 Research questions Byrne shows that the context of a situation influences the inferences people make (1989). The context of the tasks with morally difficult inferences and its counterpart inferences is similar. It is to assume that the response time, correctness and likeliness of the two groups under conditions of moral dilemma do not significantly differ. 39

40 Research questions Do people differentiate concerning the severity of the three described moral desicion situations? Imagine you had to make the decision to save lives, what kind of decision situation would be more difficult to make for you? How much more difficult is it for you to find a decision in the chosen decision situation? 40

41 Percent Correctness Results: Correctness 100% Overall Correctness 80% 60% 59,9 64,5 69,6 40% 20% 0% MD MDC NMD Figure 1: Average overall correctness per group 41

42 Percent Likeliness Results: Likeliness 100% Likeliness 80% 80,5 81,5 89,5 90,8 86,2 87,6 60% 40% Likeliness LikelinessAnsCor 20% 0% MD MDC NMD Figure 2: Average likeliness of all tasks / likeliness of the correctly answered tasks 42

43 Response Time in seconds Results: Response Time 16,00 Response Time 14,00 12,00 10,00 8,00 8,6 10,2 8,2 6,00 4,00 2,00 - MD MDC NMD Figure 3: Average response time per group 43

44 Results: Weighting 30 What kind of decision situation would be more difficult to make for you? Pregnant Women Runaway Trolley Figure 4: Weighting Pregnant Women vs. Runaway Trolley 44

45 Results: Weighting What kind of decision situation would be more difficult to make for you? Pregnant Women Overweight Boat Figure 5: Weighting Pregnant Women vs. Runaway Trolley 45

46 Results: Weighting 35 What kind of decision situation would be more difficult to make for you? Runaway Trolley Overweight Boat Figure 6: Weighting Runaway Trolley vs. Overweight Boat 46

47 Summary Research aim: Combination of two areas of research inference suppression and moral reasoning Well known moral dilemmas were transformed into suppression tasks and arranged as questionnaire Pilot study Slight tendencies towards group differences Subjects assess the moral situations differently 47

48 Future perspectives Future investigations and analyses are required to refine the questionnaire and its moral dilemmas. A larger sample size is necessary to ensure reliable results and to detect possible group differences Further analyses are required concerning withingroup comparisons. (to analyze the effects of the different scenarios, argument types and inferential figures) 48

49 Critical reflection Is it even possible to cause a moral feeling with these kind of tasks? Do the subjects sense a moral dilemma, when they answer the questions? Is there any moral reasoning? How could it be possible to cause more intense moral feelings? (pictures / the first-personperspective? 49

50 Thanks for your attention and your interest! Marco Ragni, Gregory Kuhnmünch and Stefan Wölfl for your tips and advices! to the SPP for their support! 50

51 References Bucciarelli, M., Khemlani S. & Johnson-Laird, P. N. (2008). The psychology of moral reasoning. Judgment and Decision Making, 3(2), Byrne, R. M. (1989). Suppressing valid inferences with conditionals. Cognition, 31(1), Evans, Jonathan St B. T. (1982). The psychology of deductive reasoning. London ; Boston: Routledge & Kegan Paul. Mikhail, J. (2007). Universal moral grammar: theory, evidence and the future. Trends Cogn Sci, 11(4), doi: /j.tics Wason, P. C. & Johnson-Laird, P. N. (1972). Psychology of reasoning: structure and content. London: Batsford. 51

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53 Examples and further results 53

54 Experiment: MD - example task A pregnant woman is about to give birth to her triplets. If the doctors treat the woman then her triplets will live, but she will die. If the woman has lost too much blood then her triplets will live, but she will die. If a midwife helps the woman to deliver the babies then her triplets will live, but she will die. The doctors treat the woman. 54

55 Experiment: MDC example task A pregnant woman is about to give birth to her triplets. If the doctors treat the woman then she will live, but her triplets will die. If the woman has not lost too much blood then she will live, but her triplets will die. If a midwife helps the woman to deliver the babies then she will live, but her triplets will die. The doctors treat the woman. 55

56 Experiment: NMD example task A pregnant woman is about to give birth to her triplets. If the doctors treat the woman then she and her triplets will live. If the woman has not lost too much blood then she and her triplets will live. If a midwife helps the woman to deliver the babies then she and her triplets will live. The doctors treat the woman. 56

57 Results: demographics Table 1: sample size and gender distribution MD MDC NMD Overall Nwomen Nmen Noverall Table 2: age M SD Min Max MD 36,6 12, MDC 42,8 12, NMD 44,4 13, Overall 41,3 12,

58 Results: demographics 25 My logical abilities are very good Figure 1: self-assessment - logical abilities 20 I had good grades in math Figure 2: self-assessment - grades in math 58

59 Percent Correctness Results: Correctness - Modus Ponens Correctness Modus Ponens 100% 80% 79,4 89,7 86,5 60% 40% 20% 0% MD MDC NMD Figure 3: Average overall correctness per group 59

60 Percent Likeliness Results: Likeliness - Modus Ponens 100% 80% 84,8 Likeliness Modus Ponens 90,4 91,6 92,6 90,2 86,3 60% 40% Likeliness LikelinessAnsCor 20% 0% MD MDC NMD Figure 4: Average likeliness of all tasks / likeliness of the correctly answered tasks 60

61 Response Time in seconds Results: Response Time Modus Ponens 14,00 Response Time Modus Ponens 12,00 10,00 8,00 6,00 7,9 7,9 7,1 4,00 2,00 - MD MDC NMD Figure 4: Average response time per group 61

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