The experimental study of economic exchange behavior revealed many discrepancies between normative theory of strategic rationality (game theory) and actual behavior. In many games games where defection and competition is expected by game theory, subjects robustly display cooperative behavior. In the ultimatum game, for instance, a ‘proposer’ makes an offer to a ‘responder’ that can either accept or refuse the offer; if the responder refuses, both players get nothing. The rational outcome is a minimal offer by the first player and an unconditional acceptance of the offer by the second. In fact, proposers make ‘fair’ offers, about 50% of the amount, responders tend to accept these offers and reject most of the ‘unfair’ offers (less than 20%;Oosterbeek et al., 2004). Cooperative and prosocial behavior is also observed in similar games, e.g. the trust game and the prisoner’s dilemma (Camerer, 2003). Neuroeconomics, the study of the neural mechanisms of decision-making (Glimcher, 2003), also showed that subjects seems to entertain prosocial preferences. Brain scans of people playing the ultimatum game indicates that unfair offers trigger, in the responders’ brain, a ‘moral disgust’: the anterior insula, an area involved in disgust and other negative emotional responses, is more active when unfair offers are proposed (Sanfey et al., 2003). In the prisoner’s dilemma and the trust game, similar activations have been found: cooperation and punishment of unfair players elicit positive affective emotions, while unfairness elicit negative one (de Quervain et al., 2004; Rilling et al., 2002). The received view of these behavioral and neural data is that human beings are endowed with genuinely altruistic cognitive mechanisms, a view now labelled “Strong Reciprocity” (SR). According to SR, an innate propensity for altruistic punishment and altruistic rewarding makes us averse to inequity (Fehr & Rockenbach, 2004). In this talk, I argue that this moral optimism is far-fetched. Yes, the ‘cold logic’ model of rationality is not an accurate description of our decision-making mechanisms, but the SR model, I shall argue, relies on unwarranted assumptions. I present another model–the ‘hot logic’ approach–according to which human agents are selfish agents adapted to trade, exchange and partner selection in biological markets (Noë et al., 2001). Cognitive mechanisms of decision-making aims primarily at maximizing positive outcomes and minimizing negative ones. This initial hedonism is gradually modulated by social norms, by which agents learn how to maximise their utility given the norms. The ‘hot logic’ approach provide a simpler explanation of cooperation and fairness: subjects make ‘fair’ offers in the ultimatum game because they know their offer would be rejected otherwise. Responders affective reaction to ‘unfair offers’ is in fact a reaction to the loss of an expected monetary gain: they anticipated that the proposer would comply with social norms. This claim is supported by other imaging studies showing that loss of money can be aversive, and that actual and counterfactual utility recruit the same neural resources (Delgado et al., 2006; Montague et al., 2006). This approach explains why subjects make lower offers in the dictator game (an ultimatum game in which the responder make an offer and the responder's role is entirely passive) than in the ultimatum, why, when using a computer displaying eyespots, almost twice as many participants transfer money in the dictator (Haley & Fessler, 2005), and why attractive people are offered more in the ultimatum (Solnick & Schweitzer, 1999). In every case, agents seek to maximize a complex hedonic utility function, where the reward and the losses can be monetary, emotional or social (reputation, acceptance, etc.). SR is thus seen as cooperative habits that are not repaid (Burnham & Johnson, 2005).

1. Social Neuroeconomics:
Strong Reciprocity of ‘Hot Logic’ ?
Benoit Hardy-Vallée
Department of Philosophy
University of Toronto

2. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
The received view :
Cooperation in behavioral
economics and neuroeconomics
‘Strong Reciprocity’
- inequity-aversion
- cooperation
- punishing cheaters
Alternative account:
‘Hot Logic’
- egoist cognition
- methodological
hedonism 2

3. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Prisoner’s dilemma
Ultimatum Game
Trust Game
Game theory
3

4. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Prisoner’s dilemma
Ultimatum Game
Trust Game
The prisoner’s dilemma
Remain
Confess
silent
Confess
- 5, -5 - 10, 0
Remain
0, -10 - 2, -2
silent
4

5. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Prisoner’s dilemma
Ultimatum Game
Trust Game
the ‘warm glow’ of cooperation
Rilling, J., Gutman, D., Zeh,T., Pagnoni, G., Berns, G., & Kilts, C. (2002). A neural basis for social cooperation. Neuron, 35(2), 395-405.
5

6. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Prisoner’s dilemma
Ultimatum Game
Trust Game
Ultimatum
Game
Proposer
Responder
$9/$1 $8/$2.... ... ...$1/$9
Accept/reject
6

7. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Prisoner’s dilemma
Ultimatum Game
Trust Game
‘unfair’ offers trigger moral disgust and cognitive conflict
Sanfey, A. G., Rilling, J. K., Aronson, J. A., Nystrom, L. E., & Cohen, J. D. (2003).The neural basis of economic decision-making in the Ultimatum Game. Science, 300(5626), 1755-1758.
7

8. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Prisoner’s dilemma
Ultimatum Game
Trust Game
1.
Trust Game
x$
3x$
A. B.
x$ x 3=
(Y$) (Y$)
A.
2. B.
(Y-x $) (Y + 3x$)
 Z$
3. A. B.
(Y-x)+Z $) (Y + 3x) –Z $)
8

9. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Prisoner’s dilemma
Ultimatum Game
Trust Game
the ‘sweet taste’ of revenge:
Punishment is predicted by activity in the striatum
de Quervain, D. J., Fischbacher, U.,Treyer,V., Schellhammer, M., Schnyder, U., Buck, A., et al. (2004).The neural basis of altruistic punishment. Science, 305(5688), 1254-1258.
9

10. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Strong Reciprocity :
Interpreting Neuroeconomics
Fehr, E., Fischbacher, U., & Gachter, S. (2002). Strong reciprocity, human cooperation, and the enforcement of social norms. Human Nature, 13(1), 1-25.
Fehr, E., & Rockenbach, B. (2004). Human altruism: economic, neural, and evolutionary perspectives. Curr Opin Neurobiol, 14(6), 784-790.
Gintis, H. (2000). Strong Reciprocity and Human Sociality. Journal of Theoretical Biology, 206(2), 169-179.
Henrich, J., Boyd, R., Bowles, S., Camerer, C., E., F., & Gintis, H. (2004). Foundations of Human Sociality: Economic Experiments and Ethnographic
Evidence from Fifteen Small-Scale Societies: Oxford University Press.
Henrich, J., Boyd, R., Bowles, S., Camerer, C., Fehr, E., Gintis, H., et al. (2005). quot;Economic manquot; in cross-cultural perspective: behavioral experiments in 15
small-scale societies. Behav Brain Sci, 28(6), 795-815; discussion 815-755.
10

11. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Strong Reciprocity
willing to sacrifice resources in order to:
- reward fair behavior
- punish unfair behavior
even if there is no direct or future reward
11

12. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Strong vs Weak Reciprocity
Weak
genetic relatedness (kinship)
tit-for-tat (direct reciprocity)
good reputation (indirect reciprocity)
signs of power or wealth (coslty signaling).
Strong
Pro-social preferences and actions
Inequity-averison
12

13. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
cooperate
or
memory of
planning punish
past encounters
Others’utility
detector
inter-agents
utility categorization
comparator
Personal utility equal fair
detector
unequal unfair
Mechanisms of
Social Reciprocity 13

14. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
cooperate
or
memory of
planning punish
past encounters
Others’utility
detector
inter-agents
utility categorization
comparator
Personal utility equal fair
detector
unequal unfair
Inequity aversion 14

15. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
cooperate
memory of
planning
past encounters
Others’utility
detector
inter-agents
utility categorization
comparator
Personal utility equal fair
detector
unequal unfair
Prosocial action 15

16. “ “the neural foundations of strong reciprocity”
”
and a
“neural basis for strong reciprocity”
(Fehr & Rockenbach, 2004, p. 786/788).
Fehr, E., & Rockenbach, B. (2004). Human altruism: economic, neural, and evolutionary perspectives. Curr Opin Neurobiol, 14(6), 784-790.
16

17. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
‘Hot logic’ approach:
2 suggestions:
other interpretation of the data
other methodology
17

18. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
trust and cooperation signals
augment the chances of forming mutually profitable relationships
18

19. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
altruism can be instrumental
“
quot;individuals attempt to outcompete each other in
terms of generosity. It emerges because altruism
enhances the status and reputation of the giver.
Status, in turn, yields benefits that would be otherwise
”
unattainable.quot;
(Hardy & Van Vugt, 2006)
19

20. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Ultimatum Game
‘fair’ acceptables splits
profitable splits
splits
9/1, 8/2, 7/3... ...3/7, 2/8, 1/9
...5/5...
20

21. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
biological altruism (instrumental)
21

22. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Haley, K., & Fessler, D. (2005). Nobody’s watching? Subtle cues affect generosity in an anonymous economic game. Evolution and Human Behavior, 26(3), 245-256.
22

23. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Bateson, M., Nettle, D., & Roberts, G. (2006). Cues of being watched enhance cooperation in a real-world setting. Biology Letters, 12, 412-414.
23

24. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
24

25. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Hot Logic and dopaminergic systems
http://thebrain.mcgill.ca
25

26. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
methodological hedonism
using feelings to
anticipate feelings in order to
control our behavior toward
a maximization of positive feelings and
a minimization of negative ones
26

27. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
Conclusion
Strong Reciprocity: genuinly altruistic + innate
drive
--more like a mystery than an explanation
Hot Logic: methodogical hedonism
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28. Introduction Games Strong Reciprocity ‘Hot Logic’ Conclusion
“
This egoism is the instrument of our
preservation; it resembles the
instrument for the perpetuation of
the species; we need it, we cherish it,
”
it gives us pleasure, and we must
hide it.
- Voltaire, discussing Mandeville’s Fable of the Bees, In Dictionnaire Philosophique
28

29. Thanks !
ben.hardy.vallee@utoronto.ca
Homepage
http://decisis.net
Natural Rationality Blog:
http://naturalrationality.blogspot.com
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