The Rich Get Richer: Self-Organizing Inequality and Agent-Based Modeling Michael W. Macy

1. The Rich Get Richer:Self-Organizing Inequality and Agent-Based Modeling Michael W. Macy Cornell University CSSI Workshop, Tohoku University June 13, 2005

2. 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!

3. 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

4. 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?

5. how do you make a paperclip chain?

6. step one: buy a nice big box of paperclips

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

8. step three: spread the clips out on the table

9. step four: find a chain and pick it up!

10. 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

11. 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. most sociologists are Cartesians

12. what if inequality is like a chain of paperclips?

13. 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

14. 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

15. 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.

16. an autofactory is not autopoietic(it is allopoietic) reorganizes raw materials and energy into autos which then exit the system.

17. 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.

19. 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.? examples of self-organization

20. 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

21. 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

22. 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)

23. 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)

24. heuristic adaptive autonomous interdependent relational • 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

25. heuristic adaptive autonomous interdependent relational like self-organizing flocks and paperclip chains, global patterns emerge spontaneously out of local interaction

26. heuristic adaptive autonomous interdependent relational • 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)

27. heuristic adaptive autonomous interdependent relational • group dynamics depend on network properties • density • clustering (short cycles) • hubs, bridge ties (“small worlds”) • elective ties (dynamic networks)

28. 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

29. 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

30. an agent based model of the emperor’s new clothes

31. 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

32. 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.

33. 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”)

34. how agents decide to comply • “true believers” comply out of conviction • “posers” comply if local pressure exceeds conviction

35. 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

36. what do we learn? • 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!

37. 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

38. 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

39. 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

40. 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?

41. 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?

42. END