the rich get richer: self-organizing inequality and agent-based modeling michael w. macy

The Rich Get Richer::Self-Organizing Inequality and Agent-Based Modeling………..…CSSI Workshop .…. June 13, 2005….1

The Rich Get Richer:Self-Organizing Inequality and Agent-Based Modeling

Michael W. MacyCornell University

CSSI Workshop, Tohoku University

June 13, 2005


flocking behavior

flock remains cohesive despite disturbances changes direction to avoid obstacles or

pursue a moving target appears to be organized by a leader – but

there is none!


flocking as group process

flock behavior is highly complex but individual behavior is extremely simple:

– separation: avoid collisions– alignment: match the vectors of neighbors– cohesion: move toward the center of neighborhood


implications for social science

individual human beings and social systems are both extremely complex

but flocking demonstrates that complexity of social systems need not be based on complex behavior.

question: can we discover simple rules of local interaction to explain persistent puzzles of social life, including the reproduction of inequality?


how do you make a paperclip chain?


step one: buy a nice big box of paperclips


step two:open up the box and pour out the clips


step three: spread the clips out on the table

step four: find a chain and pick it up!


so where did the chain come from?

Aquinas: God made it– organization is evidence that there must be an

Organizer– organization is imposed from the top down

Descartes: (Discourse on Method, pt.V)– God has better things to do than make paperclip

chains.– instead God created the Universe as a self-organizing

system and turned it loose


most sociologists are Cartesians

but many still assume inequality is imposed from above…– elite theory– theory of the state– class, racial, or patriarchal domination– hegemonic ideology– theories of occupational or class closure, glass

ceilings, etc.

what if inequality is like a chain of paperclips?


what can birds and paperclips tell us about human behavior?

birds have “bird brains” paperclips have no brains at all but flocks and chains have emergent properties!

– simple rules of local interaction – generate complex global patterns


self-organizing group dynamics

more like improvisational jazz than a symphony orchestra– people compose their “parts” on the fly, but not

just as they please– but improvisation is badly behaved, highly

nonlinear requires a new approach to modeling

– old social science: interactions among variables– new science of ABC modeling: interactions

among agents


what is self-organization?

entropy: tendency toward disorganization self-organization:

– transfer of entropy to the environment– hence, only in open systems, with permeable

boundaries– characterizes the out-of-equilibrium dynamics of

autopoietic systems.


an autofactory is not autopoietic(it is allopoietic)

reorganizes raw materials and energy into autos which then exit the system.


autopoietic system

Jupiter’s Great Red Spot is a vortex that has persisted for a much longer time than the average amount of time any one-gas molecule has spent within it.


examples of self-organization

natural systems hurricanes/tornados flocks, swarms, schools,

hives consciousness evolution life

social systems traffic jams high school cliques residential segregation social division of labor reproduction of classes,

gender roles, etc.?


social self-organization

actors are– autonomous (behavior is internally generated)– interdependent

influence one another in response to influence they receive consequences of actions depend on actions of others

– embedded (local interaction)

emergent patterns are dynamically stable


mechanisms for self-organizing inequality

assortative mating, homophily, mobility– Schelling neighborhood segregation– but with people constantly moving in and out– shifting boundaries (like Jupiter’s Great Red Spot)

stable hierarchies– status expectations, labeling, – leveled aspirations

gender differences that are dynamically stable– Brinton: differential parental investment in Japan– Ridgeway: self-reinforcing status characteristics


what is a “social agent”?

cognitive architecture– heuristic (norms, habits, rituals, routines, etc.)– adaptive (learning, evolution)

social architecture– autonomous (self-organizing)– interdependent– relational (embedded in networks)


heuristic adaptive autonomous interdependent relational

“human beings viewed as behaving systems, are quite simple” (Simon 1998)

behavior based on “rules of thumb” (norms, conventions, rituals, routines, moral and social habits)


population learning alters frequency distribution across individuals

– evolutionary selection (survival and reproduction)– imitation (role modeling, conformity)– social influence (instruction, persuasion, suggestion)

individual learning alters probability distribution within individuals

– reinforcement (behavioral propensities, attitudes)– bayesian updating (beliefs)– back-propagation of error in artificial neural networks




like self-organizing flocks and paperclip chains, global patterns emerge spontaneously out of local interaction


behavioral interdependence: agents influence others in response to the influence that they receive (persuasion, sanctioning, and imitation)

strategic interdependence: the consequences of each agent’s decisions depend in part on the choices of others (as in the prisoner’s dilemma)



group dynamics depend on network properties

– density– clustering (short cycles)– hubs, bridge ties (“small worlds”)– elective ties (dynamic networks)



applications of ABC models

local interactions generate familiar but enigmatic global patterns that may appear unexpected and then just as dramatically disappear:– polarization of opinion– riots & revolutions– panics– emergence of norms– market crashes

– ethnic segregation & conflict– collective behavior– collapse of social trust– fads– feeding frenzies


Schelling’s Tipping Model

an interesting and important puzzle:– after 1964 housing discrimination was illegal– since 1950 racial prejudice has declined– yet neighborhoods remain highly segregated

Schelling hypothesized that segregation:– does not need to be imposed (top-down)– does not reflect preferences (bottom-up)– self-organizes through dynamic interaction


an agent based

model of the

emperor’s new clothes


naked emperor’s are easy to find… feigned allegiance

– adulation of an incoherent scholar

– enthusiasm for a despised regime

peer pressure for self-destructive behaviors– drug or alcohol consumption (to be “cool”)

– Kuran: Indian caste system

witch hunts– exposing “collaborators” to avoid exposure

– homophobic violence to affirm masculinity

common theme: self-organizing status inequality


easy to find but hard to explain

easy to explain why people succumb to peer pressure.

but why do they put public pressure on others to comply with norms they privately oppose?

to find out, we modeled the Andersen fable using adaptive agents who influence one another in response to the influence they receive.


a formal model of the Andersen fable

agents make two decisions:– whether or not to admire the Emperor

(“compliance”)– whether to pressure others to do so as well

(“enforcement”)


how agents decide to comply

“true believers” comply out of conviction “posers” comply if local pressure exceeds

conviction


why agents enforce

“true believers” enforce their convictions “posers”

– fear exposure as approval-seeking imposters– use enforcement to signal sincerity of convictions

fanaticism of the new recruit to prove conviction “closet” deviants who persecute others to avoid

suspicion


parochial populations are highly vulnerable very unlikely in networks characteristic of

pluralistic societies the key people in these cascades:

– not those who are highly influential they start the cascade but do not sustain it critical role is played by those who are easily influenced!

what do we learn?


why not use game theory instead?

striking similarities– global properties emerge from local interaction– among strategically interdependent but autonomous

actors compared to natural language

– both are less nuanced– but more rigorous

an explicit logical structure whose validity can be tested unequivocally

ABC models are as rigorous as axiomatic theory


mathematical tractability imposes limitations

discourages complex or dynamic networks– either a complete graph (hence a small N)– or a random graph (no clustering, no hubs)

applies to games played by game theorists– perfect rationality– complete information– unlimited calculating ability


complexity from simple behaviors

analytical and game theoretic models – heroic assumptions about cognitive capacities – social order is simplified as an equilibrium

agent-based models reverse this. – Agents follow simple rules that evolve through

experience observational and reinforcement learning imitation of “role models” competitive selection pressures

– population dynamics are highly complex


advantages of agent modeling

identification of equilibrium says nothing about– probability that each equilibrium will obtain– path into or out of equilibrium– system behavior far from equilibrium– “Emperor’s New Clothes”

unpopular norms are a global equilibrium but can agents get there from a random start?


a final thought to take home …

is “self-organizing inequality” blaming the victim?

is it fatalistic? by identifying the mechanisms that underlie

emergent hierarchies, can we discover how to make vicious circles turn virtuous?


END

the rich get richer: self-organizing inequality and agent-based modeling michael w. macy

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