Transcript How moral illusions make us less effective

How moral illusions make us less
effective
Stijn Bruers
Stijnbruers.wordpress.com
[email protected]
Discrimination (speciesism)
Empathy
Unwanted arbitrariness
Arbitrary categorization and
nationalism
1. Whole world
2. Land mass (Eurasia)
3. Continent (Europe)
4. Country (Belgium)
5. Region (Flanders)
6. Municipality (Ghent)
???
Arbitrary categorization and religious
conflicts
1. all beliefs
2. religions
3. Abrahamists
4. Christians
5. Catholics
6. Roman-Catholics
???
1. all life
2. kingdom (animals)
3. phylum (vertebrates)
4. class (mammals)
5. order (primates)
6. family (great apes)
7. genus (Homo)
8. species (Homo
sapiens)
???
9. ethnic group (whites)
Your
grandmother
Your
mother
You
Irrational fear
Irrational fear
• Smallpox vaccine
• No interpersonal violence
(world peace)
10% of deaths
1% of deaths
Eradicating smallpox = 10 times world peace!
Irrational fear
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•
•
•
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•
Violence free world?
Ebola free world?
AIDS free world?
Smoke free world?
Hunger free world?
Accident free world?
Vegan world?
1% of DALYs
0% of DALYs
3% of DALYs
5% of DALYs
5% of DALYs
8% of DALYs
9% of DALYs
Disability
Adjusted
Life
Years
Non vegan world
Vegan world
Compassion fade and psychic numbing
Compassion fade and psychic numbing
Compassion fade and psychic numbing
• Letter A: save Rokia
• Letter B: save Rokia and Moussa
Västfjäll D, Slovic P, Mayorga M, Peters E (2014)
Compassion Fade: Affect and Charity Are Greatest for a
Single Child in Need. PLoS ONE 9(6): e100115.
doi:10.1371/journal.pone.0100115
Slovic, P. (2007), If I Look at Mass I Will Never Act:
Psychic Numbing and Genocide. In Judgment and
Decision Making, Volume 2, no. 2, pp. 79-95.
• 100€
• 80€ (40€ for Rokia)
Compassion fade and psychic numbing
Scope neglect
• Letter A: save 2000 birds
• Letter B: save 20000 birds
Desvousges, W. Johnson, R. Dunford, R. Boyle,
K. J. Hudson, S. and Wilson K. N. (1992).
Measuring non-use damages using contingent
valuation: experimental evaluation accuracy.
Research Triangle Institute Monograph 92-1.
• $80
• $78
Identifiable victim effect
Kogut T. & Ritov I (2005). The “identified victim” effect: an identified
group, or just a single individual? Journal of Behavioral Decision Making
18 (3): 157–167.
Zero risk bias
• Disease A: affects 1% of
people
• Vaccine A: reduces
disease A with 100%
(from 1% to 0%)
• Total reduction of (risk
of) all diseases: 1%
(from 23% to 22%)
Kahneman, D. &Tversky, A. (1979) Prospect
theory: An analysis of decision under risk,
Econometrica, 47, 263-291.
• Disease B: affects 22%
of people
• Vaccine B: reduces
disease B with 10%
(from 22% to 20%)
• Total reduction of (risk
of) all diseases: 2%
(from 23% to 21%)
Perceived
badness
of risk
Zero risk bias
Vaccine B
Vaccine A
0% 1%
Problem A
20% 22%
Problem B
Risk
Zero risk bias
Arbitrary categorization
1. all suffering
2. type (diseases)
3. class (infectious diseases)
4. transmission (viral
diseases)
5. species (disease A)
???
6. subspecies (disease A1)
Cause neutrality
Framing effects
Tversky A. & Kahneman D. (1981). The Framing of decisions and
the psychology of choice. Science 211 (4481): 453–458.
Asian disease problem
• Intervention A
• 200 of 600 lives saved
• Expectation value: 1/3
of people saved
• Intervention B
• 1/3 probability of saving
600 lives
• Expectation value: 1/3
of people saved
Asian disease problem
• Intervention C
• 400 of 600 people die
• Expectation value: 2/3
of people die
• Intervention D
• 2/3 probability 600
people die
• Expectation value: 2/3
of people die
Futility thinking
• Intervention A: helps
1000 of 3000 people
• 33% of people saved
• 1000 people saved
• Intervention B: helps
2000 of 100.000 people
• 2% of people saved
• 2000 people saved
Fetherstonhaugh, D., Slovic, P., Johnson, S. and
Friedrich, J. (1997). Insensitivity to the value of
human life: A study of psychophysical numbing.
Journal of Risk and Uncertainty, 14: 238-300.
Unger, P. (1996). Living High and Letting Die,
Oxford: Oxford University Press.
Certainty effect (Allais paradox)
• Policy A: everyone
receives 1000€
• Policy B: 50% receive
3000€, 50% receive
nothing
Certainty effect (Allais paradox)
• Policy A: 10% of people
receive 1000€
• Policy B: 5% receive
3000€, 95% receive
nothing
Existential risk
• Probability: 0,000000001 (P1)
• Number of future lives at stake:
1000000000000000000000000 (N)
• Expected number of lives lost (P1xN): 1000000000000
(E1)
• 1% reduction of risk; new probability (P2):
0,00000000099
• New expectated number of lives lost (P2xN):
990000000000 (E2)
• Expected number of lives ‘saved’ (E1-E2): 10000000000
Population ethics
Variable populations
Maximize total well-being?
Population ethics
The repugnant conclusion (Derek Parfit)
10
10
9
8
Population ethics
The repugnant conclusion
9
8
1
7
Intransitivity
Status quo bias (reversal test)
Value
???
Bostrom N. & Ord T. (2006). The reversal test: eliminating status
quo bias in applied ethics. Ethics 116 (4): 656–679.
Parameter
Questions?
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