Fairness, Trust, and Cooperation: Insights from Decision - - PowerPoint PPT Presentation

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Fairness, Trust, and Cooperation: Insights from Decision - - PowerPoint PPT Presentation

Apr 27, 2023 222 likes •773 views

Fairness, Trust, and Cooperation: Insights from Decision Neuroscience Alan Sanfey Donders Institute for Brain, Cognition, & Behavior Radboud University Nijmegen The Netherlands Decision Neuroscience Approach Economics Build models

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Fairness, Trust, and Cooperation: Insights from Decision Neuroscience

Alan Sanfey

Donders Institute for Brain, Cognition, & Behavior Radboud University Nijmegen The Netherlands

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  • Approach
  • Build models of decision-

making that:

– take into account neurobiology – use formal modeling approach – are psychologically plausible – study different types of decision – have practical relevance

Decision Neuroscience

Psychology Economics Neuroscience

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Social motivations

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Social motivations matter

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Social motivations

How do social motivations influence decision-making? Fairness & Equity Trust & Reciprocity Cooperation

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Fairness & Equity

Social motivations

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The Ultimatum Game

$10

You John

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The Ultimatum Game

John

$2 $8 Do you accept or reject John’s offer?

You

Accept: John $8; You $2 Reject: John $0; You $0

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Ultimatum Game: decisions

Sanfey et al (2003), Science

20 40 60 80 100

Acceptance Rate (%) Offers

$5 $3 $2 $1

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Ultimatum Game: Brain

  • Insula responsive to unfair
  • ffers

Insula

Sanfey et al (2003), Science

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20 30 40 50 60 70

Ultimatum Game: emotion priming

Acceptance Rate (%)

Harle & Sanfey (2010), Emotion; Harle & Sanfey (2012) Neuroimage

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Social decisions and emotions

Disgust: Facial actions significantly more active as offer decreases

  • f

f e r : l i n e a r i n v e r s e t r e n d

2.2 2.7 t(59)

A

“D ”: fica

“ ”: fica

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Social decisions and emotions

Disgust: Facial actions significantly more active as offer decreases

d e c i s i

  • n

( r e j e c t > a c c e p t )

2.2 3.2 t(59)

  • f

f e r : l i n e a r i n v e r s e t r e n d

2.2 2.7 t(59)

A B

“D ”: fica

“ ”: fica

Anger: Facial actions significantly more active as offers are rejected

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20 30 40 50 60 70

Ultimatum Game: deliberative priming

Acceptance Rate (%)

Tesch & Sanfey (submitted)

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20 30 40 50 60 70

Ultimatum Game: expectation priming

Acceptance Rate (%)

Sanfey (2009), Mind & Society

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Unfairness

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Unfairness

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Unfairness & Punishment

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Unfairness & Punishment

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Unfairness & Punishment

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5 15 25 35 45

Number of chips spent

2nd punish 3rd punish 3rd compensate

Unfairness & Punishment

Stallen, et al. (in prep); Civai et al (in prep)

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5 15 25 35 45

Number of chips spent

2nd punish 3rd punish 3rd compensate

Unfairness & Punishment

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5 15 25 35 45

Number of chips spent

2nd punish 3rd punish 3rd compensate

Unfairness & Punishment

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Unfairness – fMRI

Response to Unfairness Unfair vs Fair

– Insula

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Unfairness & Punishment – fMRI

Reaction to Unfairness Punishment vs Compensation

– Striatum

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Unfairness & Punishment – fMRI

Reaction to Unfairness Punishment decisions

– VLPFC

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Fairness norms are quite flexible, despite participants’ claims to the contrary Violations of perceived fairness reliably activates specific brain network of Insula/ACC/dlPFC Responses and decisions concerning unfairness are computationally quantifiable

Fairness: Summary

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Trust & Reciprocity

Social motivations

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Trust & Reciprocity

Social motivations

“Sentence this monster named Madoff to the most severe punishment within your abilities.” “The message must be sent that Mr. Madoff's crimes were extraordinarily evil. Mr. Madoff will get what he deserves, and he will be punished according to his moral culpability.”

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The Trust Game

Peter

$10

You

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The Trust Game

Peter

$2 $32 $8 How much of the $32 do you want to return to Peter?

You X 4

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Reciprocity: an economic puzzle

Why return money if you don’t have to?

Warm Glow Guilt

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A formal model of guilt

U2 = M2 -q(E2E1M1 - M1)+

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A formal model of guilt

U2 = M2 -q(E2E1M1 - M1)+

Guilt

P2’s belief about the amount

  • f money P1 expects

Amount of money P2 actually returns to P1

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  • Player 2 often returns very

close to the amount they believe Player 1 expects them to return

  • Decisions minimize

anticipated guilt

Trust & Reciprocity: second player behavior

P2 beliefs about P1 expectations ($) Amount P2 returned ($)

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Trust & Reciprocity: fMRI

Negative emotion & Expectation brain regions are active when reciprocating trust Reward brain regions are active when keeping money

Insula N Acc

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How can our theories and empirical data help inform broader questions?

  • Useful to have data-driven hypotheses to generate

policy advice

  • Opportunity to test our models in more complex,

real-life, scenarios

Policy Implications

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Big questions….

Societal Implications

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Societal Implications – Euro Crisis

Italian PM Matteo Renzi: “We haven't scrapped early retirements for Italians so that the Greeks could keep theirs” German Finance minister Wolfgang Schäuble: “I always kept to what was agreed, to our rules, if everyone had done the same Greece would not be in such a desperate situation” Greek government statement: “a new proposal which transfers the burden of austerity in a way which is socially unfair”

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Current work (1):

  • Cooperation

– Use of incentives to motivate volunteerism

  • Social vs monetary
  • Positive vs negative emotion
  • Group membership

Policy Implications

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Societal Implications – PGG results

Micheli, Stallen, & Sanfey (In prep)

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Societal Implications – PGG results

Micheli, Stallen, & Sanfey (In prep)

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Current work (2):

  • Poverty and decision-making

– Decreased cognitive focus under scarcity

Policy Implications

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Scarcity and cognitive function - results

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Scarcity and cognitive function - results

Scarcity > Abundance Abundance > Scarcity

Xie, Stallen, & Sanfey (In prep)

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  • Importance of social motivations in decision-making

– People often don’t act in accordance with their economic self-interest

  • Variety of methodological (& disciplinary) approaches

can clarify factors underlying social decisions

– Triangulate motivations of fairness, trust, cooperation etc

  • Potential usefulness in informing public policy

– Testing our theories in real-life decision contexts

Conclusion

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University of Arizona

Mascha van’t Wout  Katia Harle  Aaron Tesch Luke Chang  Filippo Rossi  Trevor Kvaran Julie Shah  Carly Furgerson  Alec Smith David Yokum  Martin Dufwenberg

Acknowledgements

Donders Institute

Veerle van Son  Mirre Stallen  Claudia Civai Maarten Boksem  Annabel Losecaat Vermeer Vincent Schoots  Catalina Ratala  Kim Fairley Xu Gong  Linda Couwenberg  Peter Vavra Leticia Micheli  Wenwen Xie  Jeroen van Baar Inge Huijsmans  Marieke Vermue

University of Trento

Cinzia Giorgetta  Alex Grecucci  Amber Heijne

Funding

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  • Player 2 is accurate at

predicting Player 1’s expectations

Trust & Reciprocity: second player beliefs

P2 beliefs about P1 expectations ($)

P1 expectation ($) Chang, Smith, Dufwenberg & Sanfey (2011), Neuron