1. 1 Introduction to Complex Systems: How to think like nature  1998-2007. The Aerospace Corporation. All Rights Reserved. Organizations: when groups are better than individuals Innovation required individual autonomy. What do groups add? Russ Abbott Sr. Engr. Spec. 310-336-1398 Russ.Abbott@Aero.org

2. 2 “Self-organizing” groups 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/ –Separation: Steer to avoid crowding birds of the same color. –Alignment: Steer towards the average heading of birds of the same color. –Cohesion: Steer to move toward the average position of birds of the same color.

3. 3 “Self-organizing” groups Debora Gordon on ant colonies Debora Gordon on ant coloniesThe bird, termite, and ant models illustrate emergence (and multi-scalarity). (See video Debora Gordon on ant colonies.)Debora Gordon on ant colonies In both cases, individual, local, low-level rules enabled “the group” to achieve “emergent” higher level results. –The birds flocked. –The wood chips were gathered into a single pile. –The food was brought to the nest. Exploratory behavior extends the perceptual reach of any individual. Emergence is successful group design.

4. 4 Breeding groups 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. Group (and more generally multi-level) selection is now accepted as valid. Traditional evolutionary theory says there is no such thing as group selection, only individual selection. Bill Muir (Purdue) demonstrated that was wrong. Wikipedia commons http://www.ansc.purdue.edu/faculty/muir_r.htm Groups are entities. You and I are both entities and cell colonies.

5. 5 But then groups found that coordination, specialization, and coordinated specialization enabled emergence. –Consider any multi-cellular organism, or any organism with multiple organs, or any society with any sort of specialization, or any social grouping with coordinated and/or specialized roles. –These groups exemplify real emergence. Entirely new capabilities appear. Wind instruments can play melodies. Piano and guitar can play chords as well. Why groups? Perhaps groups formed initially because they increased survival value. A team will generally beat an individual of approximately the same skill level. –This is not so much emergence as power in numbers. Why groups? Two steps.

6. 6 David Sloan Wilson on groups What holds for chickens holds for other groups as well: teams, military units, corporations, religious communities, cultures, tribes, countries. Successful groups are those that minimize within-group conflict and organize to succeed at between-group conflict. Groups with mechanisms for working together can often accomplish far more (emergence) than the sum of the individuals working separately. –Corporations, military organizations; reproduction; mitochondria and “us.” But if a group good is also an individual good (e.g., money, security), 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.) These traits may be transmitted genetically (by DNA). They may also be transmitted culturally (by training/parenting/indoctrination/mentoring/…). –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 We evolved to be pro-social within groups but xenophobic between groups. – Michael Shermer

7. 7 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. CD C3/30/5 D5/01/1 A far-from-equilibrium system. New energy is supplied “for free.”

8. 8 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. 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.

9. 9 Homo economicus vs. strong reciprocity 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 both 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 even at a cost to themselves. 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.

10. 10 Wise crowds: more than the sum of their parts Web wise crowd platforms Wikis Mailing lists Chat rooms Prediction markets 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% With 10 people: ~98%. Simple if you think about it. Traditional wise crowds Teams Juries Democratic voting

11. 11 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 is free to speak his/her own mind and make own decision. Distillation mechanism: to extract the essence of the crowd's wisdom. Participant autonomy. James Surowiecki, The Wisdom of Crowds

12. 12 Example from The Difference Which person from the following list was not a member of the Monkees (a 1960s pop band)? (A) Peter Tork (B) Davy Jones (C) Roger Noll (D) Michael Nesmith Imagine a crowd of 100 people with knowledge distributed as follows: 7 know all 3 of the Monkees 10 know 2 of the Monkees 15 know 1 of the Monkees 68 have no clue In other words, less than 10 percent of the crowd knows the answer, and over two- thirds are culturally deprived of any Monkees knowledge. We assume individuals without the answer vote randomly. The Condorcet Jury Theorem, then, doesn’t apply because only a small minority knows the answer. Still, the crowd will have no problem getting the right answer. The 7 who know all the Monkees vote for X; 5 of the 10 who know 2 of the Monkees will vote for X; 5 of the 15 who know 1 of the Monkees will vote for X; and 17 of the 68 clueless will vote for Noll. So X will garner 34 votes, versus 22 votes for each of the other choices. Diverse groups of problem solvers outperformed the groups of the best individuals at solving problems. The diverse groups got stuck less often than the smart individuals, who tended to think similarly.

13. 13 A wise crowd as assistant and companion

14. 14 Distillation mechanism: prediction markets Statement Statement Statement issued by 25 world-famous academics. May 2007. Including: Kenneth Arrow, Daniel Kahneman, Thomas Schelling, Robert Shiller, Cass Sunstein. 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.

15. 15 Often 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) from Robin HansonRobin Hanson

16. 16 Market mechanisms Intrade uses a continual double auction—bid and asked prices. (Like stocks.)Intrade –Requires high liquidity or a market maker. –Aggregates information in price; can buy or sell any time. Pari-Mutual. Losing bets distributed to winning betters. (Like horse racing). –Requires neither liquidity nor a market maker. –Aggregates information as odds. Can’t trade. Prices don’t vary. No profit in being right early. Best strategy is to wait until the last minute. But that reduces the amount of information supplied to the pool. – kahst.kahst Market Scoring Rules (Robin Hanson) and Dynamic Pari-Mutuel Market (David M. Pennock & Mike Dooley).Dynamic Pari-Mutuel Market –Combines pari-mutuel with continual double auction. –Benefit for being right early. –MSR: Inkling, Qmarkets; DPM: Yahoo! Tech Buzz Game.InklingQmarketsYahoo! Tech Buzz Game List of markets: MidasOracle.org.MidasOracle.org

17. 17 Prediction markets Contracts: Intrade (Ireland-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 PrizeGoogle Lunar X Prize Split off from TradeSports Land a privately funded robotic rover on the Moon that is capable of completing several mission objectives, including roaming the lunar surface for at least 500 meters and sending video, images and data back to the Earth.

18. 18 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 don’t always beat experts. People will not work for trinkets. High accuracy is not assured. from Robin HansonRobin Hanson

19. 19 Other distillation mechanisms: making the crowd’s “wisdom” “actionable” Elections, polls, etc. Traditional. Many possible processes, e.g., transferrable ballots, etc. –Expression of preferences. –Many online options (and more options).options Collaboration: wikis and other collaboration tools (shared spaces), mailing lists, chat rooms, etc. –Explicit: Generation of new “work products.” Here’s a (long!) list of collaborative work environments.collaborative work environments –Implicit: Google’s page rank, “reputations” (e.g., eBay), “recommendation engines” (e.g., Amazon)

20. 20 Backups

21. 21 Stem cells instead of cancer Organisms are just a bunch of cells. If you understand the conditions under which they cooperate, you can understand the conditions under which cooperation breaks down. Cancer is a breakdown of cooperation. When cells reach the point where they divide constantly, they are cancer cells. Instead multi- cellular organisms use a seemingly inefficient process to replace lost cells. An organ such as the skin calls upon skin-specific stem cells to produce intermediate cells that in turn produce skin cells. Although great at their job, the new skin cells are evolutionary dead ends. They cannot reproduce. Losing the ability to reproduce was part of the evolutionary path single-celled organisms had to take to become multi-cellular. What was in it for the single cells? They got to be part of something more powerful. Something that was hard to eat and good at eating other things. John W. Pepper, University of Arizona Animal Cell Differentiation Patterns Suppress Somatic EvolutionAnimal Cell Differentiation Patterns Suppress Somatic Evolution, PLoS Computational Biology Vol. 3, No. 12, (12/2007) If cells reproduce by simply making carbon-copies of themselves, their descendants are more likely to accumulate mutations. Suppressing mutations that might fuel uncontrolled growth of cells would be particularly important for larger organisms that had long lives

22. 22 Group/system-level emergence Debora Gordon on ant colonies Debora Gordon on ant coloniesBoth the termite and ant models illustrate emergence (and multi- scalarity). (See video Debora Gordon on ant colonies.)Debora Gordon on ant colonies 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. 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. You and I are each (a) entities and (b) cell colonies.

23. 23 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

24. 24 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