Introduction to Complex Systems: How to think like nature Groups: organization and innovation Russ Abbott Sr. Engr. Spec. Rotn to CCAE 310-336-1398 Russ.Abbott@Aero.org 1998-2007. The Aerospace Corporation. All Rights Reserved.

Flocking Craig Reynolds wrote the first flocking program two decades ago: http://www.red3d.com/cwr/boids. Here’s a good current interactive version: http://www.lalena.com/AI/Flock/

Group/system-level emergence Both the termite and ant models illustrate emergence (and multi-scalarity). In both cases, individual, local, low-level rules and interactions produce “emergent” higher level results. The wood chips were gathered into a single pile. The food was brought to the nest. Emergence in ant and termite colonies may seem different from emergence in E. coli following a nutrient gradient because we see ant and termite colonies as groups of agents and E. coli as a single entity. But emergence as a phenomenon is the same. In both cases we can explain the design of the system, i.e., how the system works. In the ant/termite examples, the colony is the system. In the case of E. coli, the organism is the system. http://evolution.binghamton.edu/dswilson/ In Evolution for Everyone, David Sloan Wilson argues that all biological and social elements are best understood as both groups and entities. You and I are each (a) entities and (b) cell colonies.

Breeding groups/teams/systems Evolutionary processes are fundamental to complex systems http://www.ansc.purdue.edu/faculty/muir_r.htm Traditional evolutionary theory says there is no such thing as group selection, only individual selection. Bill Muir (Purdue) demonstrated that was wrong. Chickens are fiercely competitive for food and water. Commercial birds are beak-trimmed to reduce cannibalization. Breeding individual chickens to yield more eggs compounds the problem. Chickens that produce more eggs are more competitive. Instead Muir bred chickens by groups. At the end of the experiment Muir's birds' mortality rate was 1/20 that of the control group. His chickens produced three percent more eggs per chicken and (because of the reduced mortality) 45% more eggs per group. Wikipedia commons

Wilson on groups Moral systems are interlocking sets of values, practices, institutions, and evolved psychological mechanisms that work together to suppress or regulate selfishness and make social life possible. —Jonathan Haidt What holds for chickens holds for other groups as well: teams, military units, corporations, religious communities, cultures, tribes, countries. Groups with rules for working together can often accomplish far more (emergence) than the sum of the individuals working separately. But if a group good is also an individual good (e.g., money), the group must have mechanisms to limit cheating (free-ridership). Group traits (although they are carried as rules by individuals) evolve because they benefit the group. (E.g., insect behavior.) Group selection (not just individual selection) now accepted as valid. These traits may be transmitted genetically (by DNA). They may also be transmitted culturally (by indoctrination). Built-in sense of fairness in both us and chimpanzees.

Homo economicus vs. strong reciprocity Homo economicus: individual selection Agents care only about the outcome of an economic interaction and not about the process through which this outcome is attained (e.g., bargaining, coercion, chance, voluntary transfer). Agents care only about what they personally gain and lose through an interaction and not what other agents gain or lose (or the nature of these other agents’ intentions). Except for sacrifice on behalf of kin, what appears to be altruism (personal sacrifice on behalf of others) is really just long-run material self-interest. Ethics, morality, human conduct, and the human psyche are to be understood only if societies are seen as collections of individuals seeking their own self-interest. Strong reciprocity: group selection A predisposition to cooperate with others, and to punish (at personal cost, if necessary) those who violate the norms of cooperation even when it is implausible to expect that these costs will be recovered at a later date. Strong reciprocators are conditional cooperators They behave altruistically as long as others are doing so as well. and altruistic punishers They apply sanctions to those who behave unfairly according to the prevalent norms of cooperation. Moral Sentiments and Material Interests: The Foundations of Cooperation in Economic Life Herbert Gintis, Samuel Bowles, Robert T. Boyd and Ernst Fehr (eds), MIT Press, 2005

Clearly fundamental. How are we autonomous? We’re smart because we are “programmable,” i.e., able to learn—both information and norms Socialization: norm internalization. There's no such thing in biology, economics, political science, or anthropology. Humans can want things even when they are costly to ourselves because we were socialized to want them to be fair, to share, to help your group, to be patriotic, to be honest, to be trustworthy, to be cheerful. Humans are successful because we’re smart. We’re smart because we operate in complex groups. We can operate in complex groups because we have strong reciprocity. We both share and are willing to punish non-sharers. Take bees. You always think of the hive as the big social collective. Not true. Workers often try to lay eggs, even though only the queen is supposed to lay eggs. If workers lay eggs, other workers run around, eat the eggs, and then punish the workers that laid the eggs. Wherever you find cooperation, you’ll also find punishment. Think of your own body. Each cell has its own self-interest to multiply. Why don’t they go berserk (cancer)? How do you get cells to cooperate? You punish cells that don’t cooperate. What does it mean to say that we can learn? The word may sound cold and robotic, but it means that we are “programmable,” i.e., capable of internalizing new skills and ideas. Socialization is a form of learning. Herbert Gintis Clearly fundamental. How are we autonomous?

Experimental “games” Prisoner’s Dilemma. C D 3/3 0/5 5/0 1/1 Prisoner’s Dilemma. One shot: Defect only rational strategy. Iterated. Tit-for-tat: cooperate initially and then copy the other guy. Pavlov: repeat on success; change on failure. (More robust.) Ultimatum Game. Proposer must offer to divide $100—e.g., from TAI. Responder either accepts the proposed division or rejects it—in which case neither gets anything. Only rational strategy: proposer offers as little as possible; responder always accepts. What would you offer/accept? Try it. Try it table against table. Each table prepares an offer. Shuffle. The winning table is the one with the greatest total. Real experiments (world-wide). Responder rejects unless offer ~1/3. Public Goods Game. Contributions to a common pot grows—via emergence. The result is divided among everyone, even free-riders.

The “public goods” riddle Free riders do better than cooperators/contributors. But then cooperation (and public goods) will vanish. Punishment is important in sustaining cooperation. But how can punishment emerge if it is costly? Categories of players Loners do not participate; they neither contribute nor benefit. Defectors do not contribute but benefit. Cooperators contribute and benefit but do not punish. Punishers are contributors who also (pay to) punish defectors and simple cooperators—to prevent simple cooperators from free-riding on punishers. Which category dominates depends on modeling assumptions. Games of Life Hannelore Brandt, Christoph Hauert†, and Karl Sigmund, “Punishing and abstaining for public goods,” PNAS, Jan 10, 2006. http://www.pnas.org/cgi/reprint/103/2/495

Wise crowds: more than the sum of their parts Traditional wise crowds Teams Juries Democratic voting Web wise crowd platforms Wikis Mailing lists Chat rooms Prediction markets Condorcet Jury Theorem (18th century) example Five people (a small crowd). Each person has a 75% chance of being right. Probability that the majority will be right: ~90% (James Surowiecki, The Wisdom of Crowds) (Scott Page, The Difference) Wise crowd criteria Diverse: different skills and information brought to the table. Decentralized and with independent participants: No one at the top dictates the crowd's answer. Each person free to speak his/her own mind and make own decision. Distillation mechanism: to extract the essence of the crowd's wisdom. Emergence. Participant autonomy.

A wise crowd as assistant and companion

Prediction markets Like either an option market or a modified and automated pari-mutuel betting system. http://www.midasoracle.org/links/exchanges/ Real money options http://www.intrade.com/

Exploratory behavior How can the human genome, with fewer than 25,000 genes produce A brain with trillions of cells and synaptic connections? The filling out of the circulatory and nervous systems? Cell growth followed by die-off produce webbing in duck feet and bat wings but not in human fingers. Military strategy of “probing for weakness.” Ant and bee foraging. Corporate strategy of seeking (or creating) marketing niches. The general mechanism is: Prolifically generate a wide range of possibilities Establish connections to new sources of value in the environment. Mechanism generation Function explore Purpose use result Bottom up

Like water finding a way down hill From a tutorial on the immune system from the National Cancer Institute: http://www.cancer.gov/cancertopics/understandingcancer/immunesystem. Microbes attempting to get into your body must first get past your skin and mucous membranes, which not only pose a physical barrier but are rich in scavenger cells and IgA antibodies. Next, they must elude a series of nonspecific defenses—and substances that attack all invaders regardless of the epitopes they carry. These include patrolling phagocytes, granulocytes, NK cells, and complement. Infectious agents that get past these nonspecific barriers must finally confront specific weapons tailored just for them. These include both antibodies and cytotoxic T cells. Quite a challenge! We are very well defended. But we still get sick! Some “invaders” will make it past these defenses. The problem is not even that some get through, it’s that they exploit their success. How do they find the open pathways? It’s not “invaders” vs. “defenders.” Through evolutionary exploratory behavior, if there is a way, some will inevitably find it. Innovation is the (disruptive) invader not the defender. Innovative organizations make that inevitability work in their favor.

Innovative environments The Internet The inspiration for net-centricity and the GIG Goal: to bring the creativity of the internet to the DoD Other innovative environments The scientific and technological research process The market economy Biological evolution What do innovative environments have in common?

Innovative environments Innovation is always the result of an evolutionary process. Randomly generate new variants—by combining and modifying existing ones. Select the good ones. (Daniel Dennett, Darwin's Dangerous Idea) Requires mechanisms: For creating stable and persistent design instances so that they can serve as the basis for new possibilities. For combining and modifying designs. For selecting and establishing better ones.

Designs in various environments All bottom-up Designs in various environments Recorded as Created by How instantiated Established Internet Software Programmers who know the techniques Self-instantiating By users Scientific knowledge A publication Scientists who know the literature The publication is the instantiation By peer review Market economy Trade secrets Product developers who know the tricks Entrepreneurial manufacturing Consumers Biological evolution DNA Combination and mutation Reproduction Whether it finds a niche Entities: nature’s memes An implicit design Construction, combination and mutation Implementation of a level of abstraction

How does this apply to organizations? To ensure innovation: Creation and trial Encourage the prolific generation and trial of new ideas. Establishing successful variants Allow new ideas to flourish or wither based on how well they do. Sounds simple doesn’t it?

Innovation in various environments New ideas aren’t the problem. Trying them out Getting good ideas established Initial funding Prospect of failure Approvals Establishment Biological evolution Capitalism in the small. Nature always experiments. Most are failures, which means death. (But no choice given.) None. Bottom-up resource allocation defines success. Entrepreneur Little needed for an Internet experiment. Perhaps some embarrassment, time, money; not much more. Few. Entrepreneur wants rewards. Bottom-up resource allocation. Bureaucracy Proposals, competition, forms, etc. Who wants a failure in his/her personnel file—when “mission success” is the corporate motto? Far too many. Managers have other priorities. Top-down resource allocation.