Evolution Slides

8/8/2019 Evolution Slides

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Basic Assumptions of EvolutionaryTheory

There are heritable variationsin traits (i.e.,either a physical characteristic such as brainsize, height or a psychological characteristic

such as sociability, selfishness, generosity,aggresiveness and intelligence).

Inparticular environments some traits

contribute more to an individualsfitness (i.e.,survivaland reproduction) than others.

As a result these traits are positively selectedand increase in frequency. In a word, they

become adaptations.


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Basic Assumptions of Evolutionary

Psychology

Human thought, feeling and action reflect adaptationsortraits that evolved over the past 5,000,000 yearswhen the human line separated from that ofchimpanzees and bonobos, our closest primate

relatives. Adaptations are modular(e.g., vision, language). But

to what extent? How distinct an entity (e.g., lungs vsjealousy vs sociality)?

Sociality (i.e., group living), is a key human adaptation. The costs and benefits associated with our peculiarly

extensive and complex networks of social relations arethe primary source of selection pressures on humans.


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Humans Compared to Chimpanzees

and Bonobos What adaptations or traits distinguish humans

form their nearest primate relatives? What do

these adaptations imply about human socialpsychology?

Large brains

Long periods of juvenile dependenceExtensive parental care including the transfer of vast

amounts of information

Multigenerational bilateral kin networks


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(And thats not all! Theres )

Habitual bipedal locomotion

Cryptic or concealed ovulation

Menopause

Culture, including language

Letal competition among kin-based coaltions

N.B. A few other species exhibit some ofthese adaptations. However, only humans

possess the entire set of them in their most

complex form.


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The Adaptive Value of a Trait

Depends on Its Contribution to Fitness

The ultimate and most direct measure of

fitness is the number of healthy offspring or

reproductive success (RS). Thus, a traits

benefits refers to how much it increases RS

and its costs, how much it decreases RS.

We often use less direct or moreproximal

measures of fitness that we assume

contribute to RS (e.g., as health, strength,

wealth) for convenience.


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Why Do We Think Group Living Is an Adaptation?

Because it is universal.

Because it is typical of species most closely related bycommon descentto humans.

Because it has neurophysiologicalcorrelates (e.g., neocortexratio and social network density; ostracism and activation ofpain area in brain).

Because it has affective correlates (e.g., isolation andostracism are painful and universal punishments while beingliked and respected are pleasurable and universal rewards).

Beause it has cognitive correlates (e.g., Theory of Mind;cheater-detection modules).

Because bio-economic analyses of fitness (i.e., benefits toRS relative to it costs) suggests living in groups is adaptive.


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Do species most closely related to humans (chimps and

bonobo) live in groups? Yes. Are chimp groups and

bonobo groups similar? No. So what?

5

10

15

MillionsOf ears a o


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Are there neurophysiological correlates of group living?

Yes. Neocortex size increases with group size social

complexity.


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Bio-economic Analysis

In examining sociality as an adaptive strategy Richard

Alexander considers the recurrent problems faced by

groups in the ancestral environmentand compares

the hypothetical fitness costs and benefits of

increasinggroup size from living with severalconspecifics (e.g., in separate nuclear families),

through a few dozen (e.g., nuclear family coalitions or

extended families), one or two hunderd (hunter-gatherer groups), to thousands or millions (towns,

cities, clans, tribes and nations).


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The cost/benefit return of increasing groups size:

Minimizing home, den or nest site shortages as an adaptive

problem


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The cost/benefit return of increasing group size:

Minimizing disease as an adaptive problem


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Minimizing food shortages (when food is widely distributed,

thus, readily found) as an adaptive problem


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Minimizing food shortages when food sites are few

and hard to find as an adaptive problem


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Minimizing food shortages when food is large, hard to catch

animals (prey) as an adaptive problem


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Minimizing the danger of predation


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Protection from predation provides the largest

benefit to fitness from living in groups during

most of human evolution. However, humans have achieve ecological

dominance so that weve not had to fear

predation by other species for the past 15-20,000 years. Even before then, predation by

other species was minimized at a relatively

small group size compared to the size ofhuman clans, tribes and nations.

3. So why do we live in such large groups?!


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For many thousands of years the most

significant predator on group living humans

has been other group living humans. Toexplain how this could cause humans live in

very large groups, Alexander proposed the

balance of power model:


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i. In multi-group environments, the membersfelt vulnerability

is inversely related to the relative size of their group.

ii. Felt vulnerability motivates smaller groups to form coalitionswhose size counter-balances or excedes that of the

previously largest group.

iii. As a result, felt vulnerability decreases among members of

the newly formed coalition (and increases among members of

the previously largest group).

iv. This in turn motivates the latter also to seek coalition partners

which, if successful, motives the former to seek further

coalition partners etc. Thus,group size spirals upwardto

some limit where there is a balance of power that minimizesfeelings of vulnerability and additional coalitions are too

costly or unavailable.

The Balance of Power Model

Li i i Ki G i E i E l i


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Living inKin Groups is Easier to Explain

Than Living in Non-Kin Groups

The protection function of groups implies altruism:

Group members willingly incur large costs to

benefit others (e.g., some will risk death to protect

fellow members from an animal predator or araiding group).

Until the second half of the last century the fact of

altruism, was a puzzle. How could such tendenciesevolve if they cause harm to the actor and should

be selected against? In 1964 Hamilton showed how

in his analysis of inclusive fitness (kin selection).


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A Heuristic for Thinking about Hamiltons

Theory

Imagine you are a gene that contributes to the traitof intelligence. You know that:

An individual is your vehicle carries you through life.

Intelligence contributes to fitness (increases RS).The probability that copies of you exist in relatives of

your vehicle increases with their degree of relatedness

to your vehicle.

Then answer the following question:

What what strategy would you want your vehicle to

follow if your goal is insure that copies of you continue

to exist in future generations?


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Hamiltons Inequality Solves Two Related

Problems: Why Living in Kin Groups is Adaptive

and How Altrusim Can be Positively Selected


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Risky Decisions Involving a Large Non-Kin Group,

a Small Non-Kin Group, or My Family

The next study indicates that when making a risky

decision for a group, the size of the group and our

ties to its members can cause us to behave seemily

irrationally, i.e., compute costs and benefits in sub-optimal fashion.

In what sense are such behaviors irrational?

According to behavioral decision theory or inclusive

fitness theory or both?

Does this consider that adaptations are designed for

recurrent problems, not rare events.


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Framing of Choices in the Tversky

and Kahneman (1981) Decision Task

The decision task:

Imagine that Lodz is preparing for the outbreak of an

unusual disease which is expected to kill 600 people.

Two alternative programs to combat the disease have

been proposed.

Assume that the exact scientific estimates of theconsequences of the programs are as follows:


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Positive framing of the Decision

Task The Certain outcome. If program A is

adopted 200 people will be saved.

The Uncertain outcome. If program B isadopted, there is a one-third probability that

600 people will be save and a two-thirdprobability that no people will be saved.


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Negative framing of the Decision

Task Certain outcome. If program C is adopted,

400 people will die.

Uncertain outcome. If program D isadopted, there is a one-third probability that

nobody will die and a two-third probabilitythat 600 people will die.


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Tversky and Kahnemans results:

Under positive framing of the decision

people are risk averse

72% of their respondents chose the certain

outcome.

28% of them chose the uncertain or

probabilistic outcome.


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Tversky and Kahnemans results:

Under negative framing people are risk

prone

22% chose the certain outcome.

78% chose the probabilistic or uncertainoutcome.

Pec liar Parameters of the


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Peculiar Parameters of the

Tversky-Kahneman Decision Task

(Wang, 1996; 2002)

The Group is Large and Its Members Have NoTies to the Respondent.

What Do You Think Would Happen If theGroup is Small and the Decision Makers Ties

to the Group Are Strong?


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Risk Proneness Decreases with Group Size and Kinship

Risk proneness as a funct ion o f g roup s ize

( fro m W a n g , 2 0 02 )

0

10

20

30

40

50

60

70

6000 6 00 60 6 (n onkin ) 6 ( k in )

Size o f h ypothet ical

Percentofsubje

ctschoosing

thesureoutcome

Posi t ive Fr ami

Negative Fram

Risk Aversion is Sensitive to Survival Rates for


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Risk Aversion is Sensitive to Survival Rates for

Non-Kin Groups But Not for Kin Groups

(Choices are Positively Framed)

Effects of changing survival rate on risk preferences for group

hypothetical patients differing in size and kinship

20

30

40

50

60

70

80

6 6 600 (Group Size)

Percentofsubjectsmakingthe

risk-avervs

echoice

Survival rate = 2/3

Survival rate = 1/3

Family Small Large (Group Context)

D i i b t Ki G Vi l t R ti l Ch i P f


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Decisions about Kin Groups Violate Rational Choice: Preferences

Under Positive Framing for Probabilistic Outcomes When Its Expected

Value is Less than that of the Certain Outcome

Proportion of Group Saved for Certain

Choice

Percentage

(Note: In all conditions the probalistic outcome is 1/3rd chance of saving all

group members)

0

20

40

60

80

100

400/600 4/6 2/3 4/6

Choice of Probabilistic Outcome (Dominated)

Choice of Deterministic Outcome (Dominant)

Non-kin Kin

Members of Kin Groups Are Nice to Each Other


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Members of Kin Groups Are Nice to Each Other

But Not Under All Conditions

Parental investment hypothesis (derived frominclusive fitness theory) argues parents should incura cost to benefit a child when it contributes toparents inclusive fitness more than doing

something else with their resources. If so, whatshould be predicted (think of the earlier heuristic):

1. When parents decide on investing in a male

versus a female offspring? 2. When parents are rich versus when they are

poor?

3. When they are step-parents?


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Recall Hamiltons Inequality

Note that it says under certain conditions altruism toward

kin may actually decrease inclusive fitness. This happenswhen:

r = 0 and/or C > r B

As relatedness (r) between donor and recipientdecreases and the cost of altruism (C) increases thedonor should act in an increasingly unaltruistic manner.The next slides summarizes research (Wilson & Day,1998) comparing the likelihood of child abuse and childhomocide, decidedly unaltruistic acts, in families withtwo biological parents and families with one stepparent(typically the father). It emphatically supportsHamiltons prediction.


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However a Violent Father or Brother Did Have Benefits

When a relative was murdered, Vikings had the choicebetween a revenge murder or accepting blood money.

Berserkers were individuals with a reputation of being

extremely fierce and dangerous. If a murderer was a

berserker (or his father or brother), the aggrieved relativesof the victim were significantly more likely to accept blood

money, but to prefer a revenge killing if the murderer was

not a berserker or a close relative.

In the next slide the plotted variable is the ratio of observed murders

relative to the number expected on the basis of the proportion of

berserkers or non-berserkers in the population. Source: 34 murders

recorded in Njal's Saga.


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0

0.5

1

1.5

2

2.5

B ers e rke r No n-b e rs e rke r

Observ

ed/expected

Revenge

B lood m one

T he F itnes s B e nef its o f V io le nce

Viking berserkers suffered significantly higher rates of mortality at the hands


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120

100

80

60

40

20

01

of their own community but their behavior benefitted male members of their

families. Therefore, Berserkers were altruists, yes? (Families of the three

berserkers in the Icelandic Njals Saga suffered significantly less mortality

than the 7 families that did not contain a recognized berserker.)

Non-Beserker Berserker

Family

killed(%

)

7 3


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Something to Think About:

From the 8th through the 10th century, the Vikings

were the fiercest and most feared group in Europe,

raiding and plundering settlements on thenorthern and western coasts of the continent as

well as the interior of eastern Europe.

A dozen centuries later their descendents are the

most peaceful and least feared group in Europe.


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In light of Hamiltons theory, how could

cooperation among non-kin evolve?

Non-kin Altruism Cooperation and


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Non kin Altruism, Cooperation and

Equity: Some Questions for Later

1. Have the benefits of cooperation sufficiently

outweighed its costs (transaction costs and

opportunity costs) to create selection pressures onhuman psychology?

2. Can large cooperative networks (e.g., markets,

trading networks) function without cognitiveadaptations that allow participants to calculate the

risks of a transaction?


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3. Are there indirect benefits of non-kinaltruism (e.g., giving money to charity topoor strangers)?

4. Are costly acts with no return benefit(e.g., altruistic punishment in a one-shotprisoners dilemma game) more a matter ofsatisfying a need for equity or fairness thantrue altruism? Or a need for vegence? Ifso, how would such motives be positivelyselected?

Ski i d h f h i ilk


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Skinnerians and others of their ilk say:

Altruism need not assume the operation of

cognitive adaptations like cheater-detection, empathy or Theory of Mind

A radical behaviorist demonstrates that helping astranger develops and is maintained because it the

act of helping is reinforced by its consequences.

Hence assumptions about cognitve adaptations aretheoretically unnecessary, a violation of scientific

parsimony.

In the following experiment subjects are free to


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In the following experiment subjects are free to

press a button as quickly as they want to record the

end of a trial. In two conditions this also turns off a

noxious noise piped into a strangers ears [i] on

every trial (continuous reinforcment), [ii] on some

randomly selected trials (partial reinforcement), or

[iii] on none of the trials (control), where the noiseends automatically after a fixed interval. The desire

or effort to help is indicated by how quickly the

subject presses the button. N.B. The stranger is a confederate of the

experimenter and there is no actual noise being

piped into his ears.


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A Question to Ponder:

If humans do persist in helping strangers and if

they do so because the act is intrinsically

reinforcing, where does that leave theories thatassumes complex computations of costs and

benefits plus discounting (e.g., for age, health,

relatedness, etc.) are necessary for the evolution

of such behavior?

THE STRUGGLE BETWEEN BEHAVIORISTS


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THE STRUGGLE BETWEEN BEHAVIORISTS

AND COGNITIONISTS CONTINUES: IS

COOPERATION MINDLESS OR DO YOU

NEED COGNITIVE ADAPTATIONS?

Sidowski: Cooperation in essentially coordinatinginterpersonal behavior and can be achieved when

individuals are totally unaware they are interactingwith another person. Just assume the Law of Effector Win-Stay, Lose-Change and forget aboutcomplex computations.

Kelly: Not true. You need to think, to take theothers perspective and think about what they arethinking to achieve cooperation. Let me show

you..


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The Sidowski-Kelley Coordination Game


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The results of applying the Win-Stay-Lose-Change rule when both players, P

and O, respond simultaneously. Note that

there are only three combination of button-press choices possible on the first trial and

from then on the Win-Stay-Lose-Change

rule determines each players outcomes:


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Win-Stay, Lose-Change Wins: An Ambiguous Triumph for


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Win Stay, Lose Change Wins: An Ambiguous Triumph for

Radical Behavior Theory


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According the Win-Stay-Lose-Change rule,cooperation (mutual reward) is inevitable underconditions of simultaneous responding whichturns out to be the case whether or not P believesO is another person or a computer.

But see what happens when one simple parameteris changed, i.e., P and O respond in alternation

rather than simultaneously. Suppose O respondsfirst and P second. The three starting trials are asfollows (continuing to apply the Win-Stay-Lose-Change rule as before):

Win-Stay Doesnt Win: An Unambiguous Triumph for


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Win Stay Doesn t Win: An Unambiguous Triumph for

Social Cognition


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Unless they start out cooperating (a mutually rewarding

exchange), they should never achieve cooperation

according to the Win-Stay-Lose-Change rule. But they do achieve cooperation if P knows O is

another person (not, say, a computer). How is this

possible? Well, not by using Skinnerian reinforcement

theory which is inadequate to explain this effect. We

have to go elsewhere for an explanation. Where?

What assumption do we need to make beyond those of

reinforcement theory to explain how cooperation ispossible in a mutual-fate-control sitution when we

know our outcome depends on another person, a

stranger, and his or her outcome on us?

New Assumptions: TOM, Foresight and Planning =C i hi ki


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Cooperative Thinking

To achieve cooperation under these conditions weforeseehaving to adjust our strategies and actions with those of others

so as to reconcile potential conflicts of interests with maximumbenefit or least cost. To do so we represent in our mind, as bestwe can,what others intend to do (their plan or strategy), andwhat they think we intend to do (our plan or strategy).

Why?In order to decide whether others are trustworthy.

In order to anticipate and, thus, coordinate each othersactions,thereby achieving a mutually beneficial or least costly

relationship (e.g., reciprocity or division of labor).


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The most common experimental

paradigms for observing cooperative

thinking is the two-person prisonersdilemma game (PDG) and the n-

person prisoners dilemma game

(SDG).

The Classic PDG


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The Classic PDG

The Social Dilemma Game (SDG)


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The Social Dilemma Game (SDG)

The SDG is an n-person (n > 2) PDG. Say, as thenext Table assumes at least 5 out of a group of 7members have to contribute their endowment asum of $5 given them at the beginning of theexperiment to fund a public good. The lattermeans that all members will benefit by receiving$10 whether or not they incurred the cost of the

public good, i.e., whether they were a contributoror a non-contributor. So like all public goods, allmembers, contributor and non-contributors benefit

if the group meets the cost criterion. Do you seewhy this creates a conflict of interest similar tothat in the PDG?


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As in the PDG the largest benefit or payoff goes to

defectors (i.e., non-contributors) ifthere are

enough cooperators (i.e., contributors) to providethe public good.

The next largest goes to the cooperators if enough

others cooperate to provide the public good.

The next largest goes to defectors if there are not

enough cooperators to provide the public good.

And least benefit, the suckers payoff goes to

cooperators when there are too few to provid thepublic good.


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Next we lay out the conditions that define

the standard SDG:

It is a non-iterated (one-shot) game.

Members are strangers.

Their decisions are completely anonymous.

There is no contact or discussion prior to,

during or after the decisions. They arrive and

leave the experiment never have seen anymember of their group.


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Non-standard versions devised to compare

with the standard SDG:

Money-back is a norm imposed on the group

that guarantees cooperators will get their money

back if there are two few of them to provide the

public good, ergo, no one gets a suckers payoff

and looses his endowment.

No free-riders is a norm imposed on the

group that guarantees defectors will not benefit

more than cooperators if the public good isprovided, ergo, there is no temptation to defect.


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S SDG t di l


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Some SDG studies also vary:

Whether or not individuals have a brief discussion

prior to deciding anonymously.Whether or not the experimenter designated who

was to contribute (but they could still defect because

their decision is anonymous).

Whether or not everybody had to contribute (called

super simple because members did not have to

decide about cooperating but again anyone could

still defect since their decision is anonymous).


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Rates of Public Goods Provision

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Designated Sets of Contributors No Designated Sets of Contributors

Super Simple

No DiscussioDiscussion

Rates of Contribution when External Authority


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y

Designates the Anonymous Contributors

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Designated Sets of Contributors No Designated Sets of Contributors

Super Simple

No DiscussioDiscussion

Intergroup Cooperation: Is Distrust of the Other theD f lt f O t (E Mi i l O t )?


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Default for Outgroups (Even Minimal Outgroups)?

10%

20%

30%

40%

50%

60%

70%

80%

Own Group Benefits Other Group Benefits

No Discussion

Discussion

Reciprocity: Knowing and Providing What is Due


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Reciprocity: Knowing and Providing What is Due

Another: Uncompelled Equity and Fairness

1. Will a person abide by a contract when it is costly to do

so and the person cannot be punished for defecting?

2. Will a person punish defectors when it is costly to do so

and it cannot force them to cooperate?3. Will a person expect to receive punishment as a result of

defecting when punishment is costly to adminsiter and it

cannot benefit the punisher (by compelling cooperation)?

If you say yes to any or all of these propositions whatdoes it imply about equity and fairness as an adaptation?

Employees Contracted and Delivered Effort in One-Shot (non-repeated) Employer-Employee Gain


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0

0.1

0.2

0.30.4

0.5

0.6

0.7

0.8

0.9

1

0-5 6-10 11-15 16-20 21-25 26-30 31-35 36-40 41-45 46-50

Contracted Effort

Delivered Effort

Payoff Offer to Employee by Employer

E

mploy

eesA

ve

rageEffort

Shot (non-repeated) Employer-Employee Gain(see Gintis, et al., 2003)


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The Mystery of Altruistic Punishment

Cooperation can be maintain by punishing free-riders.

Humans seem designed to punish non-cooperatorsin that they do so even when it is costly and there

is no direct return benefit (e.g., in a one-shotexchange).

If punishment of free-riding is costly and cannotelicit return benefits from the free-rider, how can

it be postively selected and become an adaptation?iveEven when it is costly to them and they do notdirectly benefit as a result (e.g., in a one-shotgame)?


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Milgrams study of obediance is the best known

study with data about what people expect

someone to do when punishing another person. At

first glance, the findings seem to argue against

assuming the tendency to punish free-riders is an

adaptation. But does it? Is the person being punished free-

riding? If not, does the finding imply anything

about tendencies to punish in the absence of free-

riding? Let look at Milgrims data.

Punishing Members Who Refuse to Punish Deviants May BeUnnecessary to Produce Conformity: Predictions that People (including


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y y p ( g

Self) Will Refuse to Punish Deviant Learner Are Wrong.


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C i d h Di i i f L b


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Cooperation and the Division of Labor

The division of labor is probably the most

common form of cooperation in everyday life.

It is occurs when (i) members know, prefer to or

can do different things and (ii) coordinate their

respective knowledge or performances to theirmutual benefit.

The division of labor can be not only formal,

explicit and hierarchical (e.g., military units,

sports teams, surgical teams, business teams, etc.)but also informal, implicit and egalitarian (e.g.,

families, friends, co-workers and lovers).

Cooperation Depends on Trust


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p p

Contrary to Axelrod, simulation studies demonstrate

that his best game strategy, TIT-FOR-TAT, reallyisnt. Actually, it counts for little in respect to

inclusive fitness compared to the partner-selection

strategy, i.e., being able to distinguish between

trustworthy and untrustworthy partners ahead of time. If so, then humans, being so eminently cooperative

and cooperation being so vulneralbe to cheating, must

be designed to detect potential cheaters somehow.

You agree, of course? Well okay, what do we know

about such mechanism?

The DOG Partner Selection Algorithm


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The secret to DOGs success:

[1] Unlike the other partner selection strategies,when it assesses the trustworthiness of a potential

partner DOG ignores transaction costs; it doesnt

care whether a player cooperated or defected inprior transactions.

[ii] Instead it focuses only on opportunity costs; it

tries to select the player offering the highestpotential return and never selects a player one

offering a negative return regardless of whether

the player previously defected or cooperated.

How does DOG work?


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1. On the first trial DOG assigns a random preference rank to all other players.

2. From the second trial on, DOG assigns a preference rank to all the other players

according to the following X-value rule: a. For any player DOG has ever played in the past, the X-value is the score

DOG earned in the most recent transaction with that player (X can vary from somepositive value to some negative value, i.e., it can reflect a large, moderate or smallpositive or negative return from the transaction).

b. In the case of a stranger, a player with whom DOG has never played, X is

the average of the positive X-values of the players with whom DOG has played inthe past.

3. On each trial DOG first selects the player with the largest X-value.

4. If that player doesnt select DOG as a partner within three matching rounds,DOG selects the player with the second largest X-value.

5. This process continues until all the players with positive X-values are exhaustedat which point DOG returns to the player with largest X-value that is still availableand repeats the whole process, ad infinitum.


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Evidence for mechanism to assess

the likelihood of defecting,

cheating, free-riding and

untrustworthiness


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Abstract Rule Example

Rule: If you are in category X you have tobe taller than 6.0 feet. Is the rule beingviolated?

Card P: Someone who is in category X.

Card not-P: Someone who is in category Y.

Card Q: Someone who is 6.5 feet.

Card not-Q: Someone who is 5.5 feet.


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Social Norm Example

Norm: If you are drinking alcohol you have

to be 21 or older. Is it being violated?

Card P: Someone is drinking a beer.

Card not-P: Someone is drinking a coke.

Card Q: Someone is 23 years old.

Card not-Q: Someone is 17 years old.


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What Makes Us More Trustworthy?

H.L. Menken: (Its) the little voice inside of you thatsays someone is watching. Which implies concern about:

1. Being monitored.

2. Reputation. 3. Opportunity costs (i.e., other members reject you as a

partner in transactions involving trust).

4. Other kinds of punishment (e.g., make him an offerhe cant refuse ).

Computer Monitor (Haley & Fessler, 2005)


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p ( y )

Concern about being monitored can implicit and automatic in

transactions involving trust


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Cues to Trust and Distrust


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Cues to Trust and Distrust

Aside from Cosmides cheater-detection mechanism shedemonstrated using the Wason Selection task, are thereother situational or internal cues besides reputation,

payoff structure (e.g., temptations to defect in PDG) and

transparency of return (e.g., rice versus rubber markets)that are used to compute or infer trustworthiness? 1. Self-resemblance: Facial self-morphing (conscious and

unconscious effects).

2. Facial prototypes: Defector recognition (specific features,e.g., eye shape?).

3. How you feel (mood): Oxytocin inhalation.

4. Brain activity: Anticipation of returns.

Whom Do You Trust?: Self Resemblance Studies


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Using Facial Morphs


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Effects of Qxytocin on Investor Transfers with Human (Trust) and Programmed (Risk) Trustee

(Kosfeld, Heinrichs, Zak, Fischbacher, & Fehr, 2005)


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Cheater-detection makes us think more


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If we elaborate on and analyze a lot what

suspected cheaters say, then we shouldconfuse what their actual statements withinferences we made while encoding them.

Examples of types of inferencesDirect inference: Her boss says Mary worksquickly and doesnt make mistakes and weinfer Mary is an efficient worker.

Compound inference: Her boss says Maryworks quickly etc., andwe give a bonus toour most efficient workers. We infer Marywon a bonus.


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Processing Times of Suspicious and Unsuspicious Receivers

(Schul, Burnstein, & Bardi, 1996: Experiment 4)


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( , , , p )

0

5

10

15

20

25

30

1 2 3 4 5

Order of Neighbors' Reports

MeanProcessingLate

ncies(seconds)

Suspicious Receivers

Unsuspicious Receiver

Mean Impression as a Function of Descriptor Sequence


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Mean Impression as a Function of Descriptor Sequence

(Schul, Burnstein, & Bardi, 1996: Experiment 4)

0.05

-0.1

0.32

-0.27

-0.35

-0.25

-0.15

-0.05

0.05

0.15

0.25

0.35

Impress

ion

(Z-Scores

)

Suspicious Receivers

Unsuspicius Receivers

Favorable

Neutral

UnfavorableFavorable

Unfavorable

Unfavorable

Favorable


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Suspicion Can Influence Judgment


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Unconsciously

In recent experiments a few seconds before theymake a judgment, individuals are subliminally

primed with a word (e.g., an adjective or noun)

presented imbedded in a supraliminal honest ordishonest face.

The word prime as well as the face is irrelevant

to the judgments they are about to make (e.g., Is

a second word, presented above threshold, an

adjective or a noun?).

The model tested in these experiments assumes they will


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p yelaborate congruent associates to the subliminal word prime inthe honest-face context and incongruent associates to the

subliminal word prime in the dishonest-face context. If so, the model predicts that: when the prime and the to-be judged word are both nouns or both

adjectives, then in the honest-face context individuals will elaboratecongruent associates to the prime (e.g., the concept of noun or specificnouns when both the prime and the supraliminal word are nouns) andcategorization of the to-be-judged word is facilitated (e.g., faster);whereas in the dishonest-face context they elaborates incongruentassociates (e.g., the concept of adjective or specific adjectives whenboth words are nouns) and categorization is disrupted (e.g., slower).

by the same logic, when the to-be-judged word is incongruent with the

prime (e.g., one is a noun, the other an adjective), judgments will bedisrupted (e.g., slower) in the honest-face context and facilitated in thedishonest-face context.


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Mean Latency of Correct Responses (in Milliseconds) in the

Adjective-Noun Classification Task


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(Schul, Mayo, & Burnstein, 2004: Experiment 1)

697

775

754

678

760

780

678

749 750

675

700

725

750

775

800

No Faces (Polygon) Untrustworthy Faces Trustworthy Faces

Type of Prime

Re

sponseLatency(MSEC)

Congruen

Incongrue

Irrelevant

Mean Latency of Correct Responses (in Milliseconds) on



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Adjective Noun Classification Task


750

800

850

900

Distrust Context (Female impostor) Trust Context (Spontaneity)

Res

ponseLatency(M

SEC)

Congruent Prime

Incongruent Prime

Mean Number of Words Generated in Free-Association Task

(Schul Mayo & Burnstein 2004: Experiment 3)


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31.68

11.87

30.72

7.38

0

5

10

15

20

25

30

35

Total No. of Words No. of Incongruent Words

Untrustworthy Face

Trustworthy Face


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Being able to efficiently process

information about our relationswith others (e.g., Is he or she a

friend or foe? Is his or her statushigher or lower than mine?) is

useful. Is there evidence that

humans are designed to make and

store such computations?

Adaptations: Mechanisms for Coding


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p g

Social Relations

If humans are designed to live in groups, then theyare also likely to be designed to code (i.e.,

recognize, interpret, remember and elaborate

upon) information that reduces the costs of group

living and increase its benefits.

Among the most adaptive pieces of information

concern relations among group members:

Who in the group have common interests, are friends,who have conflicting interests, are enemies?

Who is has high status (i.e., is powerful, rich, skillful,

etc.), who has low status (i.e., is weak, poor, inept,

etc.)?


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A Procedure for Assessing Cognitive

Categorization of Individuals: Are They

Perceived as Belonging Together, Forming

a Coalition or Unit?

Suppose You Wanted to Know If Observers Grouped

People Based on Common Interest or Opinion.


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Tell observers about some characteristic of thepeople (e.g., sex, age, race, clothes, and what theysaid that indicated whether they were pro or conregarding an issue).

Next ask observers to recall if an individual made aparticular statement (e.g., whether he or she said X).

Count how often the individual is confused withanother (e.g., observers say he or she made thestatement when it was actually made by another).

What was the reason for these confusions? Didthey occur most often if the two individuals were


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they occur most often if the two individuals werethe same sex, the same age, the same race, worethe same t-shirt or had the same opinion (bothwere either pro or con)?

Intra-category confusion are most frequent.Therefore, if confusion occurred most often

between those with the same opinion (both werepro or both con), then its evidence thatobservers were categorizing or cognitivelygrouping the individuals based on common

opinions or common interests. Kurzban calls thiscoalitional thinking. In Heider, the groupingwould reflect a positive unit relationship and,

perhaps implicitly, a positive sentimentrelationship.


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The Benefits and Cost of Conformity


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You dont have to learn what to believe or how to do

something. Just imitate others actions and conform totheir beliefs. Social comparison as an adaptive mechanism for imitation and

conformity.

But imitation and conformity may have opportunity costs, i.e.,you will not discover that there are better ways of doingsomething or that there are more valid views of the world.

Hence, humans may be designed to discount the validity ofothers actions or beliefs to the extent that these actions and

beliefs are themselves products of conformity (notindependently arrived at) and are not objectively demonstrable.

Is this why conformity in Asch-like normative influencesettings doesnt increase when unanimous majority becomesrelatively large?

Why Normative Influence Peaks at a

Very Small Unanimous Majority


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Very Small Unanimous Majority

1. Discounting mechanisms

i. Majority has shared interests different from

that of deviant.

ii. Non-independence of majority members. 2. Futile search for independent evidence or

objective demonstration of the majority choice.

Search is typically done under time stress andat the cost of cognitive inconsistency (i.e., the

majority seems incorrect) relative to the cost of

social rejection.

Conformity to a Unanimous Blame-the-Mother-Not-the-Manufacturer Majority in a One Six Member Group, Two Three

Member Groups and Three Two Member Groups


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1

3

5

7

9

11

13

15

17

Mother's Fault

Manufacturer's Fault

Damage Award

$10K

$ 9K

$ 8K

$ 7K

$ 6K

$ 5K

$ 4K

DegreeofBla

me

1 5

Conformity to a Unanimous Blame-the-Mother-Not-the-Manufacturer Majority in Groups and in Non-Groups (Aggregates

of Individuals) of Identical Sizes


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3

5

7

9

1 1

1 3

2 3 4 5

Indiv idual M other 's F aul t

Group Mo ther ' s Fau l t

Group Ma nufac turers ' Fa

Individual Manufacturer 's

Degreeo

fBlame


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A di t M ll d M (1997)


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According to Mueller and Mazur (1997),

we automatically judge someons status ordominence from his or her face (Mueller

and Mazur, 1997).

The faces used by Mueller and Mazur arefrom a yearbook published by West Point,

the U.S. Military Academy, that trains

career army officers. Some examples: (Can

you detect differences in facial dominance?)


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140/160

See slides based on WHO

data for male-female

differences in mortality asa function of status

competition.

Mating


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Mating

What does sexual selection theory predict about

male-female difference in:

1. Preferred number of partners?2. Probability of consenting to intercourse?

3. Preferred age difference in mate?

4. Importance of mates provisioning prospects?

5. Importance of mates attractiveness?


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Probability of Consenting to Sexual Intercoourse


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-3

-2

-1

0

1

2

3

5 Yrs 2 Yrs 1 Yr 6 Mo 3 Mo 1 Mo 1 Wk 1 Day 1 Eve 1 Hr

Time Known

Likelihoodo

fIntercourse

Male

Female

(Subjects rated the probability that they would consent to sexual intercourse after having known an attractive

member of the opposite sex for each of a specified set of timer intervals.)

Ratings of Age Difference Preferred


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Between Self and Spouse

ZambiaColumbia

Poland Italy

USA

Zambia

Columbia

PolandItaly

USA

-8

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6Women

Men

Sex of Rater

3 Ratings of Importance of Partner

Having Good Financial Prospect


145/160

0

0.5

1

1.5

2

2.5

Japan Zambia Yugoslavia Australia USA

Women

Men

Having Good Financial Prospect

Sex of Rater

3 Ratings of Importance of Mate's


146/160

0

0.5

1

1.5

2

2.5

Bulgaria Nigeria Indonesia West Germany USA

Women

Men

g p

Physical AttractivenessSex of Rater

Male-Female Differences in Antecedents

and Consequences of Homicide:


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Demographic Evidence

How (if at all) might theories of sex

differences in mating strategies, especiallytheir implications regarding competition

between and within the sexes, explain the

differences in the following data sets?

Risky Competition: Age- and sex-specific homicide rates in Canada, 1974-1983.

Female victims


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25

30

Homicidespermill io

npersonsperan

num

Female offenders

Age (years)

Age (years)


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Risky

Male victims

Age- and Sex-specific Rates of Homicide in Detroit, 1972. (From Wilson & Daly,1985)


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2000

2500

0

500

1000

1500

2000

2500

Male offenders

Hom

icid

esper

millio

nperson

spera

nnum

0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80-84 85

5-9 15-19 25-29 35-39 45-49 55-59 65-69 75-79

0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80-84 85

5-9 15-19 25-29 35-39 45-49 55-59 65-69 75-79

Age (years)

Age (years)

Age- and Sex-specific Rates of Homicide in Detroit, 1972. (From Wilson & Daly,1985)


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1000

0

1000

1

0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80-84 85

5-9 15-19 25-29 35-39 45-49 55-59 65-69 75-79

0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80-84 85

5-9 15-19 25-29 35-39 45-49 55-59 65-69 75-79

Female offenders

Female victims

Homicid e

sper

millionper

son

speran

num

Age (years)

Age (years)


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Unemployment Rates Among Male Homicide Offenders, Male victims, and

the Male Population-at-Large in Detroit, 1972.

(From Wilson & Daly, 1985)


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Proportions Unmarried Among Male Homicide Offenders, Male victims, and

the Male Population-at-Large in Detroit, 1972.

(From Wilson & Daly, 1985)


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120

Spousal Homicde Rates as a Function of the Age Difference Between Wife

and Husband. Canada, 1974-1983.


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Wife older Wife younger

25

m

Motive Categories and the Number of Cases (Victims)

Within Each, for 588 Criminal Homicides in the City of

Philadelphia, 1948-1952.

(From Wolfgang 1958)


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Motive Number of cases Percentage of total

Altercation of relatively trivial origin; insult, curse,jostling, etc.

Domestic quarrel

Jealousy

Altercation over money

Robbery

Revenge

Accidental

Self-defense

Halting of felon

Escaping arrest

Concealing birth

Other

Unknown

206

83

68

62

40

31

23

8

7

6

620

28

35.0

14.1

11.6

10.5

6.8

5.3

3.9

1.4

1.2

1.0

1.03.4

4.8

(From Wolfgang, 1958)

Two hundred Twelve Closed Social Conflict homicides in

Detroit, 1972, in Which Victim and Offender Were Unrelated

(Friends, Acquaintances or Strangers), Classified by

Conflict Typology and by the Sexes of the Principals.


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Conflict typology

Male killedmale

Male killedfemale

Femalekilled male

Femalekilledfemale

Escalated showing-off contests

Retaliation for previous verbal or physical abuse

Jealousy conflicts

Business conflicts

Intervention in family dispute

Miscellaneous unique disputes

Insufficient information

Total social conflicts among nonrelatives

26

75

20

10

5

2

26

164

0

9

5

1

0

0

4

19

2

6

6

2

0

1

1

18

1

5

3

0

0

1

1

11

(From Wilson and Daly, 1985)

Dispositions of Spousal Homicides in Various Studies.

(Data from Canada and Detroit are from Daly & Wilson, 1988; for Miami from

Wilbanks, 1984; and for Houston from Lundsgaarde, 1977)


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N

Cases

Percent

suicide

Percent

convicted

Percent

scot-free

Percent

Insane

Male offenders

Detroit, 1972Miami, 1980

Houston, 1969

Canada, 1974-1983

Female offenders

Detroit, 1972

Miami, 1980Houston, 1969

Canada, 1974-1983

2921

17

644

36

2021

161

13.828.6

17.6

30.3

0

00

5.0

69.042.9

52.9

56.2

25.0

40.014.3

58.4

17.228.6

29.4

7.1

75.0

60.085.7

31.7

00

0

6.4

0

00

3.7

The Probability of Suicide After Homicide, in Relation to the Sexes of Killer and Victim,

and Their Relationship, Canada, 1974-1983


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Male killer Female killer

Killers relationship to victim Male victim Female victim Male victim Female victim

Spouse

Lover

Parent

Offspring

Other blood relative

Other marital relative

Unrelated acquaintances

Unrelated strangers

Totals

---

---

.394 (41/104)

.010 (1/100)

.031 (7/225)

.094 (14/149)

.029 (45/1527)

.014 (12/860)

.040 (120/2965)

.236 (192/812)

.268 (22/82)

.466 (34/73)

.040 (2/50)

.092 (6/65)

.185 (10/154)

.086 (27/314)

.034 (11/324)

.171 (304/1774)

.028 (7/248)

.000 (0/7)

.110 (11/100)

.010 (1/10)

.000 (0/21)

.000 (0/12)

.011 (1/87)

.000 (0/43)

.038 (20/528)

---

---

.136 (12/88)

.083 (1/12)

.000 (0/13)

.000 (0/3)

.023 (1/44)

.000 (0/15)

.080 (14/175)

Intergroup Relations

1. Realistic Group Conflict Theory (Sherif) versus Social

C i i Th (T jf l) A h i ibl ?


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Categorization Theory (Tajfel): Are they incompatible?

2. The minimal intergroup situation: Is advantaging theingroup (or disadvantaging outgroups) the default reaction

to social categorization? Is strategy likely to have been

adaptive (positively selected for) in the ancestral

environment

3. What about N-group (not merely one in-group and one

outgroup) environments and coalitions as in the balance-

of-power model?

4. Group/category membership, the hierarchy ofgroups/categories, and self-evaluation: Are there

Documents

Evolution Slides