This paper is a summary of an Aspen Institute sponsored in-depth roundtable session, written from the perspective of one informed conference observer (Bollier). The participants are leading thinkers in the many complex areas this paper covers (economics, systems theory, human behavior, human futures, information technology evolution, etc) and are listed on page 57. A selection of their key insights shared in the paper are listed below:

A "push" economy is geared towards mass production, anticipating consumer demand, and routing resources to the right place at the right time, to create standardized and mass produced products. By contrast, a "pull" economy is based on open, flexible production platforms that are used to orchestrate a broad range of resources. Instead of producing standardized products, "pull" model companies are demand-driven, and assemble products in customized ways that serve specialized or local needs, usually using "rapid" or "on the fly" processes.

Several global corporations are moving towards "pull" methods, and away from "push" models; ie., Toyota, Dell, Cisco, Li & Fung. These companies employ different variations of Value Network models, that share information about overall network performance and best practices for serving specialized needs, among hundreds or even thousands of partner companies that make up the network. This creates an intra-network knowledge commons. Some companies also work closely with Open Source Software projects, thereby expanding their "pull" network, and expanding their knowledge commons into a broader Open Commons via Open Source Software project contributions. Thus, "pull" business models also tend to be Network Value-Increasing, and Commons-based business models as well.

"Pull" models can also be platforms for creating "increasing returns dynamics." This is due to "pull" models being based around loose and flexible networks that are already configured to scale as growth occurs. So, growth does not incur the huge overhead costs in administration that "push" models must contend with. Pull platform key characteristics include modular and loosely-coupled networks, open channels that better harness the passion and commitment of innovation communities. "Pull" platforms also will tend to influence public policy with regards to education and innovation, as more companies tend to gravitate towards the "pull" models.

The areas where "push" models tend to succeed in business are in areas where people do not know what they want, and prefer to shop from pre-made selections (Ikea, Home Depot). However, there are even "pull" models to found here, in the form of user-driven innovation, such as mountain biking, extreme skiing, hot rodding, etc. In these pro-amateur niches, customers don't necessarily know what they want, but do want to be a participant in the "pull" network that creates the product.

How do you tax a product that is made in 23 different countries? "Pull" models are going to change the way that governments create policy as more companies gravitate toward them. This will influence laws about intellectual property, education, taxation and more.

"Pull" economies are not just centered around finding creative ways to "outsource/offshore jobs" away from one place and to the places where "labor" is "cheaper". Successful "pull" models have encouraged and aided "insourcing", where more jobs are created, for instance in the United States by "foreign sources (a total of 7 million cited by this paper), than are out sourced (a total of 600,000+ cited by this paper). This is because pull models seek out, not just the "cheapest" labor, but the best ways to add value to the production networks. So, they can scale to many participants around the world, regardless of local labor costs, to find the best participants needed for specific specialized productions.

The social dynamics of "pull" models are highly centered around creating relationships of trust, sharing knowledge, and close cooperation among network participants. In "pull" models, non-market value creation (tacit knowledge, intangible value) is generally steered towards a commons-based model. A commons is used as a "collective governance regime for managing shared resources sustainably and equitably." Many of these commons are made possible by networked information technologies (the internet).

Bollier suggests that "if online commons are going to be useful to business, companies will need to do more work to develop protocols for identity and reputation management". This is because the use of the commons is based around trust. It also due to the need for ways to measure qualitative value in intangible assets beyond money, like knowledge, individual performance and value multiplication, and network wide performance/value multiplication.

Roundtable participants also noted that "pull" models will pose challenges to current education regimes that are centered around training people to participate in "push" economies. One of the participants mentions that " Computers, software tools, and Internet resources make possible some radically new styles of learning. By using pull-based systems, students can function much like businesses in the pull environment: They can access resources they don't control and put themselves into flows of activity, rather than just building inventories of static, objectified "knowledge."

The authors distinguish between emotions that operate primarily in dyadic relationships and emotions that operate in a significant manner in collective contexts. The authors examine the evolutionary role each emotion and cite research about ways these emotions might contribute to the creation and maintenance of cooperative behaviors: "This chapter is premised on the claim that human cooperation is profoundly shaped by, and perhaps only possible because of, emotions. We will examine the manner in which different emotions shape behavior in cooperative contexts…Although framed within an evolutionary psychological perspective, our goal is not to present definitive evidence of the validity of this particular approach, but rather to spur future investigations of the role of emotions in cooperation. Toward that end, on an emotion-by-emotion basis we will both briefly describe a variety of existing findings and present a number of hypotheses, specifying discrete, testable predictions whenever possible."

Emotions that are primarily dyadic include romantic love, gratitude, anger, envy, jealousy, guilt righteousness and contempt. Romantic love is seen as a means of overcoming a barrier to the kind of cooperation we see in parenting -– the temptation to defect in the short term on a relationship that requires a long-term investment. "A number of investigators have suggested that some emotions can be understood as mechanisms design to commit people to behavior that yields long-term payoffs, thus overcoming the temptation for short-term defection. Romantic love, a universal human emotion that underpins pair bonding, appears to be such a mechanism."

Where romantic love is about how one feels about another person, gratitude addresses how one feels about somebody's behavior, and can be an emotional currency that binds one to reciprocity. "Gratitude focuses both attention and a positive, affiliative orientation on a party who has supplied the actor with a substantial benefit. In the context of its initial elicitation, gratitude seems to prompt the actor to recognize a valuable interaction partner and subsequently signal a willingness to reciprocate."

Why do people get so angry when someone cuts ahead of them in a queue or in traffic? This is clue to the evolutionary advantage of anger as a means of protecting ones own interests, but when it comes to the thus-far unexplained human propensity to punish cheaters, even at a cost to themselves, anger might be instrumental in conferring advantage to a group that requires monitoring and sanction of free riders in order to maintain a public good or create an institution for collective action: "If gratitude is elicited by receipt of a benefit, its opposite is anger, elicited by actual ar attempted exploitation or harm. More formally, anger is the response to the infliction of a cost. In addition to showing an "irrational" willingness to reward generosity, subjects in behavioral economics experiments also show an eagerness to punish uncooperative partners…Together, these results clearly demonstrate that even within the confines of finite anonymous games, angry individuals often place paramount importance on harming the transgressor, and are willing to incur substantial costs in order to do so."

Internet facilitated tools and practices reached critical mass in the 2004 elections enabling ordinary people to participate in processes that had been closed to them by top-down political organizations.

Old-style political organizations had evolved, abetted by mass media like television, into groups controlled by insiders. The mass participation that peaked in the early part of the 20th century was replaced by an increasingly uninterested, disenfranchised mass and a smaller group of wealthy special interests.

TV took politics away from the grassroots; the Internet could give it back. The people receiving the intended messages could be involved in creating them.

There are varieties of emerging tools in the political ecology: large, top-down organizations like MoveOn.org co-exist with multilayered communities like DailyKos in which peer moderation and rankings lead to the emergence of trusted sources.

Established political parties are behaving like dinosaurs, viewing the new media as tools for more efficiently doing their old work: the Internet is just a new place for a more sophisticated kind of direct mail. They are missing the true significance of the emerging tools and processes. With this attitude, they are likely to become extinct.

Old style, top-down political organizations are afraid of losing control. They are threatened by the dis-intermediation (the removal of middlemen) enabled by the new tools and visible in other commercial domains on the net.

The growth of web based social networking tools and techniques similar to those used to facilitate open source development environments are leading to peer political networks with transparency and accountability.

The Internet currently offers an ecology of interacting and competing groups on both the left and right. These currently range from the traditional party based groups through newer, still top-down groups like MoveOn.org through multilayered communities with peer evaluation and the emergence of trusted users. An example of the latter, DailyKos, has become a very efficient collaboration engine for pooling money for candidates and for rapid fact-checking, news dissemination, and brainstorming.

This evolution is generational. As younger people accustomed to life on the net and the use of social networking tools reach maturity, the replacement of the old ways of doing things will become easier.

Open-source politics is a long way off because of the resistance of the political establishment. In “open source” software development communities, any participant can see, critique, and improve the underlying code. Peer review permits steady improvement. In open-source political groups, planning and implementation of policies would be transparent and open to critique and improvement, an inherent threat to entrenched ego-centric, top-down organizations. However, the old order may have no choice in the matter.

Because of the “digital divide” and the amount of time spent online, Internet facilitated political participation is still largely a white middle- and upper-class phenomenon. Messages tend to circulate through existing social networks. However, this may be generational: younger people are growing up with the tools and shaping them to their needs and desires.

The Institutional Analysis and Development (IAD) framework developed by the Ostroms and their colleagues at Indiana University provides a foundation for studying a multitude of theories, models, and predictions of public choice behaviors in different systems of governance and organization.

Frameworks define the action arena to which it would be applied; the resulting patterns of interactions and outcomes, and the means of evaluating those outcomes.

A framework is a general language about how varying rules, physical and material conditions, and attributes of a community affect the structure of action arenas, the incentives for actors, and resulting outcomes.

Action arenas include an action situation and the actors in that situation.

An action situation includes:

• Participants
• Positions
• Outcomes
• Action-outcome linkages
• Control that participants exercise
• Information
• Cost and benefits of outcomes

Actors (individual or corporate) involve:

• Resources brought to the situation
• Values assigned to states of the world
• Methods for dealing with knowledge and information
• Selection processes for courses of action

Analysts can make strong predictions in tightly constrained situations of complete information: overuse of resources in an open commons where the actors do not share access to collective choice arenas.

Results are not as clear in situations where actors are embedded in communities with norms of fairness and conservation as well as the ability to communicate with each other.

Evaluation criteria can include a range of values for categories such as the following:

• Economic efficiency
• Fiscal equity among actors
• Redistributional equity (e.g., policies to care for poorer individuals
• Accountability
• Conformance to a general morality
• Adaptability to change

The IAD framework has been applied to various domains to make predictions of resulting behaviors in field settings. Examples of successful application include:

• Police services
• Urban public services in general
• Common-pool resources: these were studied in laboratory as well as field settings. The IAD framework was used to create a theory of behavior. Communication of participants affects behavior: if no communication was permitted, the results approximated that of non-cooperative game theory. Communication led to different, more positive, results.
• The IAD framework was used to develop extensive databases coding common-pool resources and diverse property regimes.

Theorists have posited that pure tit-for-tat strategies in iterative prisoners dilemma games were invulnerable. Is this correct? The authors seek to answer this question by examining the ability of various prisoners dilemma gaming strategies to withstand invasion by other competing strategies.

Bender and Swistak examine a gaming strategy universe that includes the strategies:

• Tit for tat - a player will initially cooperate and then in future rounds mimic the behavior of their opponent.
• Tit for 2 Tats - a player will cooperate for the first two rounds and then defect in rounds where their opponent defected in the previous two.
• Suspicious Tit for Tat - a player will initially defect and then will mimic their opponent in future rounds.
• Always Defect
• Always Cooperate
• Grim Trigger - Begin by cooperating, if opponent defects then always defect afterward.

These strategies were examined in pure conditions where only one existed, and then competing strategies were introduced. If a given strategy could withstand incursions by competing strategies it was deemed "stable".

Stability proved to be a continuum. All strategies proved to have points of equilibrium. At this point, a strategy can withstand its maximum level of incursion. That point is that strategy's maximum stability.

Chapter 1, The Problem of Cooperation. Why do people (or other actors) cooperate? "The objective of this enterprise is to develop a theory of cooperation that can be used to discover what is necessary for cooperation to emerge." It uses the Prisoner's Dilemma as a framework for testing theories about balancing self-interest and competition.

"In the Prisoners' Dilemma, the strategy that works best depends directly on what strategy the other player is using and, in particular, on whether this strategy leaves room for the development of mutual cooperation."

Chapter 2, TIT FOR TAT. "The iterated Prisoners' Dilemma has become the E. Coli of social psychology," yet people have not paid much attention to how to play the game well. Axelrod organized a computer tournament to which people familiar with PD submitted programs encoding different strategies. The winner was one of the simplest, TIT FOR TAT.

Axelrod then constructed an environment in which different programs competed, and the losing programs were eliminated: this was an ecology that rewarded high scoring programs, and punished others. "This process simulates survival of the fittest. A rule that is successful on average with the current distribution of rules in the population will become an even larger proportion of the environment of the other rules in the next generation. At first, a rule that is successful with all sorts of rules will proliferate, but later as the unsuccessful rules disappear, success requires good performance with other successful rules." In other words, the competition gets tougher.

"The analysis of the tournament results indicate that there is a lot to be learned about coping in an environment of mutual power. Even expert strategists from political science, sociology, economics, psychology, and mathematics made the systematic errors of being too competitive for their own good, not being forgiving enough, and being too pessimistic about the responsiveness of the other side."

The tournaments reveal that "there is a single property which distinguishes the relatively high-scoring entries from the relatively low-scoring entries. This is the property of being nice, which is to say never being the first to defect."

TIT FOR TAT's rules for success:

• Be nice. Don't be the first to go on the attack. This demonstrates good will, and avoids provoking others.
• Retaliate. If others attack, retaliate. Not doing so encourages bad behavior and gives niceness a bad reputation.
• Be forgiving. If others defect but then go back to cooperating, accept the opportunity to move back to a cooperative mode.
• Be clear. Others can predict what you'll do, be certain that their moves will have definite outcomes. "There is an important contrast between a zero-sum game like chess and a non-zero-sum game like the iterated PD. In chess, it is useful to keep the other player guessing about your intentions. The more the other player is in doubt, the less efficient will be his or her strategy. But in a non-zero-sum setting it does not always pay to be so clever. In the iterate PD, you benefit from the other player's cooperation."

Chapter 4, Trench Warfare. During World War I, "live and let live" arrangements emerged spontaneously between opposing units on the Western Front. Cooperation could take hold because "the same small units faced each other in immobile sectors for extended periods of time." Consequently, they had a more sustained relationship than in mobile warfare, and could develop commonly-understood rules, reciprocity and restraint in attacks, displays of strength (e.g., snipers shooting at hard targets)as well as ethics (recognition that there was an arrangement and violating it was immoral) and rituals (e.g., regular artillery firing).

"Cooperation first emerged spontaneously in a variety of contexts, such as restraint in attacking the distribution of enemy rations, a pause during the first Christmas in the trenches, and a slow resumption of fighting after bad weather made sustained combat almost impossible. These restraints quickly evolved into clear patterns of mutually understood behavior, such as two-for-one or three-for-one retaliation for actions that were taken to be unacceptable."

Chapter 6, How to Choose Effectively. Four suggestions about how to do well in PD:

• Don't be envious. In a PD, "envy is self-destructive. Asking how well you are doing compared to how well the other player is doing is not a good standard unless your goal is to destroy the other player." However, in an iterated prisoner's dilemma, you can't do better than the other player, unless they're always suckers. "In a non-zero-sum world you do not have to do better than the other player to do well for yourself. The other's success is virtually a prerequisite of your doing well for yourself."
• Don't be the first to defect (be nice). "It pays to cooperate as long as the other player is cooperating." In a short game, defection can make sense; but in a relationship, taking advantage of the other person is self-defeating.
• Reciprocate both cooperation and defection. TIT FOR TAT "does not destroy the basis of its own success. On the contrary, it thrives on interactions with other successful rules." However, the right level of forgiveness depends on the context, and the other players' strategies.
• Don't be too clever. "In a zero-sum game, such as chess it pays for us to be as sophisticated and as complex in our analysis as we can. Non-zero-sum games are not like this. The other player can respond to your own choices. And unlike the chess opponent, the other player in a PD should not be regarded as someone who is out to defeat you." "There is an important contrast between a zero-sum game like chess and a non-zero-sum game like the iterated PD. In chess, it is useful to keep the other player guessing about your intentions. The more the other player is in doubt, the less efficient will be his or her strategy. But in a non-zero-sum setting it does not always pay to be so clever. In the iterate PD, you benefit from the other player's cooperation."

Chapter 7, How to Promote Cooperation. Promoting cooperation can be thought of as an exercise in tinkering with the variables in a PD. "As long as the interaction is not iterated, cooperation is very difficult. That is why an important way to promote cooperation is to arrange that the same two individuals will meet each other again, be able to recognize each other from the past, and to recall how the other has behaved until now."

• Enlarge the shadow of the future. For cooperation to emerge, players must be in a continuing relationship, with the expectation that it will continue in the future. "Mutual cooperation can be stable if the future is sufficiently important relative to the past." "There are two basic ways of doing this: by making the interactions more durable, and by making them more frequent. [P]rolonged interaction allows patterns of cooperation which are based on reciprocity to be worth trying and allows them to become established," Making interactions more frequent makes "the next interaction occur sooner, and hence the next move looms larger than it otherwise would." You might do this by enforcing isolation, or constructing hierarchies or organizations, which are "especially effective at concentrating the interactions between specific individuals."
• Change the payoffs. Make defection less attractive, by enforcing laws, or growing the value of long-term incentives.
• Teach people to care about each other.
• Teach reciprocity. Reciprocity "actually helps not only oneself, but others as well. It helps others by making it hard for exploitative strategies to survive."
• Improve recognition abilities. "The ability to recognize the other player from past interactions, and to remember the relevant features of those interactions, is necessary to sustain cooperation. Without these abilities, a player could not use any form of reciprocity and hence could not encourage the other to cooperate."

Chapter 8, The Social Structure of Cooperation.
The social structure of cooperation involves labels, reputation, regulation, and territoriality.

• Labels are fixed characteristics of an agent that are observable by other agents. Labels affect reciprocity and retaliation via assumptions of group similarity and stereotypes.
• Reputation is others' belief about the strategies an agent will employ. Reputation may be based on past behavior or on rumours, i.e. reputation can be accurate or merely believed. Reputation affects whether or not other agents will cooperate or defect with you.
• Regulation involves setting the stringency of a standard of behavior "high enough to get most of the social benefits of regulation, and not so high as to prevent the evolution of a stable pattern of voluntary compliance from almost all of the companies" (or regulated agents).
• Territoriality refers to both physical and conceptual spaces that can be 'invaded' by agents of differing strategies. Territoriality establishes boundaries within which behaviors will be reinforced or retaliated against depending on prevailing norms. Also, the boundary provides an 'inside' for agents that comply with the norms, and an 'outside' to which they can be expelled if they do not comply.

Chapter 9, The Robustness of Reciprocity.

• Cooperation can get started by even a small cluster of individuals who are willing to reciprocate cooperation, even in a world where no one else will cooperate.
• Once cooperation is establish, it protects itself from invasion by non-cooperative strategies.
• The foundation of cooperation is the durability of the relationship, which allows agents to learn about each other in order to cooperate.

Dan Bricklin examines ways to induce a pool of users to contribute to a commons without extra effort, using the architecture of the commons (as in Napster's default to sharing in the way download directories are available) and leveraging user's self-interest. The key to understanding the success of Napster and other file-sharing technologies resides not in their 'peer-to-peer' nature but in the fact that they provide users with access to a database of desirable things and enable people to create a public good in the process of seeking their own interests.

Bricklin identifies three ways to fill a database: organized manual, organized mechanical, and volunteer manual.

CDDB succeeded at motivating volunteer manual data entry because it leveraged the desire for users to have their data in the database so that CDDB-aware programs could access it, for example when a user would insert a CD into their computer.

Bricklin calls this "harnessing the power of individual selfishness."

Napster cleverly avoided manual data entry by automatically indexing anything in the user's 'Shared Music' directory. Thus "storing the copy in the shared music directory [was] a natural by-product of the user's work with the songs."

Sharing is the default. This results in users "adding to the value of the database without doing any extra work."