Introduction to ArtificiaI Intelligence in Higher Education
Empathy in risky choices on behalf of others
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Empathy in risky choices
Erita Narhetali1,2, Magdalena Smyk 1,3, Marek Weretka 1,4
1FAME|GRAPE
2University of Warsaw
3Warsaw School of Economics
4University Wisconsin-Madison
SGH seminar, November 30, 2023
financed from NCN grant no. 2019/33/B/HS4/00151
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Table of Contents
1 Introduction
2 Theoretical foundation
3 Experiment
4 Results
5 Conclusion
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Introduction
Project ”EMPATHY and sentiment in strategic games” led by Marek
Weretka
THEORY by Marek Weretka and Jorge Vasquez
EXPERIMENT by Erita Narhetali and Magda Smyk
Two publications in Games and Economic Behavior:
”Affective empathy in non-cooperative games”
[Vásquez and Weretka, 2020] - theoretical frame for affective altruism
”Co-worker altruism and unemployment”
[Vásquez and Weretka, 2021] - context based study on altruism
among co-workers
Last step:
Empirical ”proof” - experimental study
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The roots of altruism
Two approaches in economic theory:
paternalistic altruism [classical] - cognitive empathy
non-paternalistic altruism [model proposed by Weretka & Vasquez] -
affective empathy
Main differences:
paternalistic altruism: decision-maker cares about consumption
non-paternalistic altruism: decision-maker cares about utility of the
other person
non-paternalistic altruism = interdependent utility, e.g.
Ui (ci,k, Uj (cj,k)) = αi,k(ci,k)γi,k
+ βi,kαj,k(cj,k)γj,k
non-paternalistic altruism: emotional contagion matter
if we can assess utility, the context is irrelevant (estimation of β)
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The roots of altruism
Main difficulties:
cardinal versus ordinal utility theory
empirical research: order of preferences
the choices should be the same for most goods, e.g. money
Possible solutions:
ambiguous or negative contexts: e.g. loss, pain, risk
different decision for different level of empathy (sympathetic versus
antipathetic)
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Asian Disease Problem
Famous [Tversky and Kahneman, 1981] framing experiment (decision
under uncertainty):
Imagine that (...) an Asian disease is expected to kill 600 people and you
have to decide between two policies designed to combat the disease.
GAIN framing:
(a) If Program A is adopted, 200 people will be saved (certain)
(b) If Program B is adopted, there is a 1/3 probability that 600 people
will be saved, and 2/3 probability that no people will be saved (risky);
LOSS framing:
(a) If Program C is adopted, 400 people will died (certain)
(b) If Program D is adopted, there is a 1/3 probability that nobody
will die, and 2/3 probability that 600 people will die (risky);
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Asian Disease Problem
The magnitude of the framing effect in Asian Disease Problem depends on
the context, among others:
social distance:
[Sun et al., 2017] the larger social distance the more risk neutral
decision-maker (stronger in gain than loss framing)
[Zhang et al., 2017] friends vs strangers - in gain framing: more risk
aversion when deciding for friends, in loss: more risk seeking for friends
Our contribution: the role of emotional contagion (sympathy and
antipathy)
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Our Experiment - problem with a water supply
”Please, imagine that you are the manager of a building that may
be affected by water supply interruptions.”
2 x 2 x 3 mixed design:
between subject: social distance (close versus distant)
(a) close:
”You know well all of the residents. You are on a first-name basis
with them.”
(b) distant:
”You don’t know the residents well, they are practically strangers
to you.”
between subject: GAIN versus LOSS
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Gain vs Loss
Which of the following programs would you choose for the residents of the
building you manage?
Gain framing:
Program A - 250 households (out of 1000) will have water supply
during the whole day for the maintenance period;
Program B - with a probability of 1/4 all 1000 households will have
water supply during the whole day for the maintenance period, and
with a probability of 3/4 no household will have water supply for 8
hours a day during the maintenance period.
Loss framing:
Program X - 750 households (out of 1000) will lose water for 8 hours
a day during the maintenance period;
Program Z - with a probability of 1/4 none of 1000 households will
lose water during the maintenance period, and with a probability of
3/4 all households will lose water for 8 hours a day during the
maintenance period.
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Sympathy
within subject: sympathetic versus antipathetic relationship
sympathetic
”You have great sympathy for the residents of that building, and
you meet them from time to time to talk about important com-
munity issues.”
antipathetic
”Your interactions with residents are limited to resolving conflicts,
dealing with their constant problems and listening to complaints.”
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Implementation: general info
When: October-November 2023 (ongoing)
+ two pre-studies:
January 2021, N=100 - power calculation
June 2023, N=300 - risk attitude
How: Profitest on-line survey
Who: ANSWEO: 400 Poles (341 currently)
equal representation of men and women
average age: 36.5
40% living in medium sized cities
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Subjects and their choice sets
H&L ”Asian Disease” Gain Loss T
TYPE: (individual) neutral sympathy antipathy
Affected:
ANY ANY S R 19.1% 15.2% 17.3%
ANY ANY R S
ANY R S S 7.1% 4.4% 5.9%
ANY S R R
Unaffected:
always RA RA/RN S S S 14.8% 5.1% 10.3%
always RL RL/RN R R R 13.1% 24.1% 18.2%
different margin RA R R R 45.8% 51.3% 48.4%
or inattentive RL S S S
Holt-Laury: RL - risk-lover, RN - risk neutral, RA - risk averse
Choice: R - risky, S - safe
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Hypothesis 1
The difference in probability of choosing risky plan between the
gain framing and the loss framing is different when the positive
and negative affection are induced (ceteris paribus).
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Frequency of risky choice
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Hypotheses
The probability that the subject will choose risky plan for sympa-
thetic residents than for the antipathetic ones is higher in a loss
framing (ceteris paribus).
The probability that the subject will choose risky plan for sympa-
thetic residents than for the antipathetic ones is lower in a gain
framing (ceteris paribus).
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Regression results
xtlogit RA effects FE effects
Odds ratios Odds ratios
sympathetic 1.98 2.37**
(1.05) (0.89)
antipathetic 3.47** 2.88***
(1.91) (1.1)
loss 147.66***
(155.35)
sympathetic # loss 0.28 0.31**
(0.26) (0.18)
antipathetic # loss 0.08** 0.21***
(0.07) (0.13)
N of observations (3 per subject) 1023 237
Notes: Estimates from a panel regression with random effects (1) and subject fixed effects (2).
Regression (1) includes also variables regarding social distance treatment, and interactions
between treatments and subject’s characteristics (female, age) - all insignificant. * p-value 10%,
** p-value 5%, *** p-value 1%
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Closeness versus sympathy
Comparison of the sense of closeness:
[Gachter S, Starmer C, Tufano F (2015)]
Ttest diff p N
sympathy vs antipathy -0.014 0.88 341
if close: symp vs anti -0.115 0.43 183
if distant: symp vs anti 0.101 0.46 158
if symp: close vs strangers -0.28 0.16 341
if anti: close vs strangers -0.49 0.01 341
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Conclusion
Current study:
empirical test of the affective empathy theory
use of risk context and framing
result: limited effect of the emotional aspect
hypothesis confirmed but only when playing with strangers,
ambiguous results for close social distance
regression result: difference between neutral and
sympathetic/antipathetic condition, but not between them
Future plans:
filling the gap -limited connection with experimental lit on altruism
broader, more complex test: dictatorship game
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References I
Sun, Q., Liu, Y., Zhang, H., and Lu, J. (2017).
Increased social distance makes people more risk-neutral.
The Journal of Social Psychology, 157(4):502–512.
Tversky, A. and Kahneman, D. (1981).
The framing of decisions and the psychology of choice.
Science, 211(4481):453–458.
Vásquez, J. and Weretka, M. (2020).
Affective empathy in non-cooperative games.
Games and Economic Behavior, 121:548–564.
Vásquez, J. and Weretka, M. (2021).
Co-worker altruism and unemployment.
Games and Economic Behavior, 130:224–239.
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References II
Zhang, X., Liu, Y., Chen, X., Shang, X., and Liu, Y. (2017).
Decisions for others are less risk-averse in the gain frame and less
risk-seeking in the loss frame than decisions for the self.
Frontiers in psychology, 8:1601.
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