1. 1 Introduction to Complex Systems: How to think like nature Russ Abbott Sr. Engr. Spec. Rotn to CCAE 310-336-1398 Russ.Abbott@Aero.org  1998-2007. The Aerospace Corporation. All Rights Reserved. Groups: organization and innovation

2. 2 Flocking Craig Reynolds wrote the first flocking program two decades ago: http://www.red3d.com/cwr/boids.http://www.red3d.com/cwr/boids Here’s a good current interactive version: http://www.lalena.com/AI/Flock/ http://www.lalena.com/AI/Flock/ A soccer game based on “forces.”soccer game based on “forces.” –Download, execute. –After it starts, click Console tab and reduce speed to 0.025.

3. 3 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. In Evolution for Everyone, David Sloan Wilson argues that all biological and social elements are best understood as both groups and entities.Evolution for EveryoneDavid Sloan Wilson You and I are each (a) entities and (b) cell colonies. In Evolution for Everyone, David Sloan Wilson argues that all biological and social elements are best understood as both groups and entities.Evolution for EveryoneDavid Sloan Wilson You and I are each (a) entities and (b) cell colonies. http://evolution.binghamton.edu/dswilson/

4. 4 Breeding groups/teams/systems 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. Traditional evolutionary theory says there is no such thing as group selection, only individual selection. Bill Muir (Purdue) demonstrated that was wrong. Evolutionary processes are fundamental to complex systems Wikipedia commons http://www.ansc.purdue.edu/faculty/muir_r.htm

5. 5 Wilson on groups 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). –Human groups are much more complex because it’s not all built-in. 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

6. 6 We’re smart because we are “programmable,” i.e., able to learn—both information and norms As humans we’re 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. 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. 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. Clearly fundamental. How are we autonomous? Herbert Gintis Next slide

7. 7 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

8. 8 Experimental “games” Prisoner’s Dilemma. –One shot: Defect is the 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. –Real experiments (world-wide). Responder rejects unless offer ~1/3. –Some societies are different, e.g., where giving a gift means power. –What would you offer/accept? Try it. (Played anonymously. Write offer.) Try it table against table. Each table prepares an offer. -Version 1. The winning table is the one with the greatest total. -Version 2. A table survives if it winds up with at least $50. CD C3/30/5 D5/01/1

9. 9 The Public Goods Game Contributions to a common pot grow—via emergence. The result is divided among everyone, even free-riders. 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. Hannelore Brandt, Christoph Hauert†, and Karl Sigmund, “Punishing and abstaining for public goods,” PNAS, Jan 10, 2006. http://www.pnas.org/cgi/reprint/103/2/495Karl Sigmundhttp://www.pnas.org/cgi/reprint/103/2/495 Games of Life

10. 10 Wise crowds: more than the sum of their parts Web wise crowd platforms Wikis Mailing lists Chat rooms Prediction markets (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. Condorcet Jury Theorem (18 th century) example Five people (a small crowd). Each person has a 75% chance of being right. Probability that the majority will be right: ~90% Traditional wise crowds Teams Juries Democratic voting Participant autonomy. Emergence. Second slide ahead

11. 11 A wise crowd as assistant and companion

12. 12 Prediction markets Abstract: Prediction markets are markets for contracts that yield payments based on the outcome of an uncertain future event, such as a presidential election. Using these markets as forecasting tools could substantially improve decision making in the private and public sectors. We argue that U.S. regulators should lower barriers to the creation and design of prediction markets by creating a safe harbor for certain types of small stakes markets. We believe our proposed change has the potential to stimulate innovation in the design and use of prediction markets throughout the economy, and in the process to provide information that will benefit the private sector and government alike. StatementStatement issued by 25 world-famous academics. May 2007. Including:Kenneth Arrow, Daniel Kahneman, Thomas Schelling, Robert Shiller, Cass Sunstein.

13. 13 Beats Alternatives Vs. Public Opinion –I.E.M. beat presidential election polls 451/596 (Berg et al ‘01) –Re NFL, beat ave., rank 7 vs. 39 of 1947 (Pennock et al ’04) Vs. Public Experts –Racetrack odds beat weighed track experts (Figlewski ‘79) If anything, track odds weigh experts too much! –OJ futures improve weather forecast (Roll ‘84) –Stocks beat Challenger panel (Maloney & Mulherin ‘03) –Gas demand markets beat experts (Spencer ‘04) –Econ stat markets beat experts 2/3 (Wolfers & Zitzewitz ‘04) Vs. Private Experts –HP market beat official forecast 6/8 (Plott ‘00) –Eli Lily markets beat official 6/9 (Servan-Schreiber ’05) –Microsoft project markets beat managers (Proebsting ’05)

14. 14 Prediction markets Contracts: Intrade (UK-based): real money or play money.real moneyplay money Panos Ipeirotis But, there is evidence that prediction markets are not efficient.prediction markets are not efficient Slate’s Election Market Page Other Intrade contracts:Current Events > Google Lunar X Prize Split off from TradeSports

15. 15 Concerns and Myths Self-defeating prophecies Decision selection bias Price manipulation Rich more “votes” Inform “enemies” Share less info Combinatorics Risk distortion Moral hazard Alarm public Embezzle Bubbles Bozos Lies Crowds always beat experts People will work for trinkets High accuracy is assured

16. 16 Market mechanisms Intrade uses a continual double auction (CDA) (Like stocks). –Aggregates information in price; can buy or sell any time; requires liquidity or market maker. Pari-Mutual betting. Losing bets distributed to winning betters. (Like horse racing). –Does not aggregate information. Can’t trade. Price doesn’t vary—but odds do. – kahst.kahst Market Scoring Rules (MSR). Combines pari-mutuel with CDA. –Robin Hanson –Inkling, QMarketsInklingQMarkets Dynamic Pari-Mutuel Market (DPM). MSR variant.Dynamic Pari-Mutuel Market (DPM) –The later you back a favorite, the more expensive. –David M. Pennock & Mike Dooley –Yahoo! Tech Buzz GameYahoo! Tech Buzz Game Listing of markets: MidasOracle.org.MidasOracle.org

17. 17 Exploratory behavior (recall evolutionary processes) 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. 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

18. 18 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. 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. 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. 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. Innovative organizations make that inevitability work in their favor. Innovation is the (disruptive) invader not the defender. 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.

19. 19 Innovative environments The Internet The inspiration for net-centricity and the GIG Goal: to bring the creativity of the internet to the DoD What do innovative environments have in common? What do innovative environments have in common? Other innovative environments The scientific and technological research process The market economy Biological evolution

20. 20 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.

21. 21 Designs in various environments Recorded asCreated by How instantiated Established InternetSoftware Programmers who know the techniques Self-instantiatingBy 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 Whether it finds a niche All bottom-up

22. 22 How does this apply to organizations? To ensure innovation: Sounds simple doesn’t it? 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.

23. 23 Initial funding Prospect of failure ApprovalsEstablishment 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. New ideas aren’t the problem. Trying them out Innovation in various environments Getting good ideas established