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."

Insect studies on emergent intelligence in swarms of unintelligent actors has practical relevance to distributed computing, robotics, and other applications; for example, foraging insects use pheromone trails to select the shortest paths to food, a strategy that has been used to solve the famous "traveling salesman problem" in computer science. Systems with distributed collective intelligence are more robust because they can adapt quickly to a variety of situations.

Foraging ants select the shortest paths to food. They are so efficient that ant models have been used to solve the famous “traveling salesmen problem,” a classic in computer science, which concerns finding the shortest route that will take a salesman through a group of cities. Successive iterations over path networks (paths that have been discovered) results in the shortest routes getting reinforced and the longest ones getting abandoned. The outcome is an optimal path length for ant foraging.

Also, artificial ants provide the best solution to the classic quadratic assignment problem, in which the manufacture of a number of goods must be assigned to different factories so as to minimize the total distance over which the items need to be transported between facilities. There exist many such “optimization problems”, such as telephone routing. Also, individual robots have been programmed to push a box to a destination without communicating.

In another project, a model that was initially introduced to explain how ants cluster their dead and sort their larvae has become the basis of a new approach for analyzing financial data. “The ant-based approach enables the data to be visualized easily, and it boasts one intriguing feature: the number of clusters emerges automatically from the data, whereas conventional methods usually assume a predefined number of groups into which the data are then fit. Thus, antlike sorting has been effective in discovering interesting commonalties that might otherwise have remained hidden.”

Again using a biological system as a model, scientists have devised a technique for scheduling paint booths in a truck factory. The method optimizes variables like paint usage and time spent, as well as implementing load-sharing between paint booths in the case of breakdowns.

“Indeed, the potential of swarm intelligence is enormous. It offers an alternative way of designing systems that have traditionally required centralized control and extensive preprogramming. It instead boasts autonomy and self-sufficiency, relying on direct or indirect interactions among simple individual agents. Such operations could lead to systems that can adapt quickly to rapidly fluctuating conditions.”

Six Degrees begins in the beginning. Stanley Milgram's initial small world studies are analyzed. His findings in seeing if a group of people in Nebraska can get a letter to someone in Massachusetts are scrutinized. Milgram left a puzzle. Mathematically, six degrees of separation can be shown and intuitively it is appealing. But do social networks actually work that way?

Initially, Watts steps into the world of pure mathematic theory. Graph theory and random graphs are employed to build potential worlds in which connections can be made. These tools are detailed and their histories explained.

Watts and his colleagues then take the science to new levels, by introducing sociology, epidemiology, economics, and business models into this new multi-disciplinary science. Immediately, each new field of study brings with it new insights into network dynamics.

This convergence of disciplines reveals the social, transportation and technological networks that make up our world. These networks are, ultimately, made up of individuals. Individuals in turn relate back to the networks and define how they operate.

Socially, people relate to their network by clustering. Clusters are logical organizations of network elements. In a social context, we might cluster in terms of a religion, a favorite author, a school we are attending or an affinity for a type of food. Some of these have very close physical distance, while others have a social distance with members spread out over a large area.

Networks of this type are, to various extents, “scale-free” networks. If graphed these networks roughly follow a classic power law trend where the level of connectivity between two nodes in a network increases dramatically as more nodes are connected. Real-world scale-free networks tend to have highly connected hubs which rapidly, purposely, and efficiently transmit pertinent or pervasive content from one location to another. In social circles, these are networkers. In the airline network these are hub airports. In traffic they would be freeway interchanges.

Due to this architecture, the Internet and modern air transport have combined to greatly decrease the role of proximity in our social networks. This has had great impacts on commerce, tourism, cultural sensitivity and other social factors. However, it has also led to great risks in the transmission of diseases, sensitivity to distant economic fluctuations, and rapid spread of misinformation.

These dynamics create a type of network that Duncan calls simultaneously robust and vulnerable. Their strength and weakness is that, with rapid transmission from cluster to cluster, anything can move quickly from one location or group to another. He uses the example of Toyota, whose network of suppliers was organized in such a way as to quickly compensate for and recover from a potential economic catastrophe.

Stable scale-free networks do not rely on a rigid hierarchy to provide direction in times of crisis. Rather, the structure of the network itself can rapidly respond to an unforeseen situation.

Their network was arranged in such a way as to foster and reward communication. This communication helped cope with ambiguous or unplanned situations. Rather than paralyzing Toyota while people waited for a decision from a rigid hierarchy, the contractors in the network were able to analyze the calamity and provide a rapid response to it.

As mentioned above, this robustness also rapidly transmits malicious content as well. The Melissa Virus, SARS and Ebola are analyzed to show why the network did or did not transmit them and, when it did, how they eventually died out.

Watts ends this book by summarizing that the multidimensional nature of social distance is sometimes counterintuitive and subjective. People can feel close in a network sense to people they are physically distant from and, conversely, socially distant from people physically nearby.

He continues by warning that social and physical distances have shrunk. People can quickly travel from place to place and economies are highly interdependent. The sheer number of dependencies in the modern world may yield surprising results from seemingly insignificant actions.

He finishes by showing the stability of our networks with the example of how New York adapted to the 9-11 attacks. The City bounced back to semi-normal operations within a week. During the disaster, the best laid plans of emergency operations staff were scuttled by the utter unavailability of facilities and services designed to copy with disasters. The network will provide.

Humans have taken the cooperative arrangements that benefited organisms and species at the biological level to the cognitive and social levels: the capacity to play cooperative social games that benefit all was a driver of the evolution of human intellectual capacity; increased intellectual capacity manifested in both the concrete sphere of tool-making and the abstract sphere of social relationships. Once enhanced cognitive capabilities made complex social arrangements like status, reputation, gossip, persuasion, punishment, alliance possible, human social capacities became a tool for ratcheting up cooperative game-playing capacity.

Certain technologies push human societies to reorganize at a higher level of cooperation. As an example, Wright offered the Shoshone, a Native American tribe that lived in a territory with no big game to hunt but an abundance of jackrabbits at certain times of year. Because of their stark environment, the Shoshone normally existed at a simple level of social organization, with every extended family foraging for itself. When the rabbits were running, however, the families banded together into a larger, closely coordinated group, to wield a tool too large for any one family to handle or maintain — a huge net. Working together with the net, the entire Shoshone hunting group can capture more protein per person than they could working apart. Wright declared that "The invention of such technologies — technologies that facilitate or encourage non-zero-sum interaction — is a reliable feature of cultural evolution everywhere. New technologies create new chances for positive sums, And people maneuver to seize those sums, and social structure changes as a result."

Wright noted that people who interact with each other in mutually profitable ways are not always aware that they are cooperating; he cited evolutionary psychologists to assert that unconscious underpinnings of cooperation — like affection and indignation — are rooted in genetic traits:

"… natural selection, via the evolution of 'reciprocal altruism' has built into us various impulses which, however warm and mushy they may feel, are designed for the cool, practical purpose of bringing beneficial exchange."

"Among these impulses: generosity (if selective and sometimes wary); gratitude, and an attendant sense of obligation; a growing empathy for, and trust of, those who prove reliable reciprocators (also known as "friends"). These feelings, and the behaviors they fruitfully sponsor, are found in all cultures. And the reason, it appears, is that natural selection "recognized" non-zero-sum logic before people recognized it…Some degree of social structure is thus built into our genes."

"In the intimate context of hunter-gatherer life, moral indignation works well as an anti-cheating technology. It leads you to withhold generosity from past nonreciprocators, thus insulating yourself from future exploitation; and all the grumbling you and others do about these cheaters leads people in general to give them the cold shoulder, so chronic cheating becomes a tough way to make a living. But as societies grow more complex, so that people exchange goods and services with people they don't see on a regular basis (if at all), this sort of mano-a-mano indignation won't suffice; new anti-cheating technologies are needed. And, as we'll see, they have materialized again and again — via cultural, not genetic, evolution."

The cultural innovations that reorganize social interaction in light of new technologies are "social algorithms governing the uses of technology." Wright called these social methodologies "metatechnologies.". In the Middle Ages, the metatechnologies of capitalism — currency, banking, finance, insurance — pushed the hierarchical machinery of feudal society to transform into a new way of organizing social activity, the market. "The metatechnology of capitalism then combined currency and writing to unleash unprecedented social power." Wright claimed that the emerging merchant class pushed for democratic means of governance, not out of pure altruism, but in order to be free to buy and sell and make contracts. Throughout this process, powerful people always seek to protect and extend their power, but new technologies always create opportunities for power shifts, and at each stage from writing to Internet, more and more power decentralizes: "I mean that new information technologies in general — not just money and writing — very often decentralize power, and this fact is not graciously conceded by the powers that be. Hence a certain amount of history's turbulence, including some in the current era."

Bacteria colonies that migrate and forage and form joint structures via chemical signaling, social insects that engage in joint problem solving behaviors via chemical signaling, symbiotic relationships between ruminants from termites to cattle with cellulose-digesting bacteria, Margulis' evidence for the symbiogenesis of mitochondria and hypthoses that flagella originated from the joining of free-swimming spirochetes with energy-producing but less-mobile microorganisms, the probably evolution of flight from a suite of synergistic functional changes, the emergence of protohumans are all cited by Corning as evidence that synergies play a central, not a peripheral role in evolution of complex life forms: "Synergy has played a key role in the progressive evolution of complex systems in nature. However, complexity is not an end in itself; it's a consequence of the innovations that produce more potent forms of synergy. Synergy is the 'driver.'"

William E. Hamilton's papers on "The Genetical Evolution of Social Behavior" in 1964 formalized the neo-Darwinian explanation of altruistic behavior as conferring benefits on close kin, but Robert Trivers' 1964 "Evolution of Reciprocal Altruism" decoupled kinship, cooperation, and altruism by offering evidence that the helping organism acts with the assumption that low-cost, low-risk assistance to another now will be repaid later – reciprocity.

Game theoretic models were driven to more realistically match human and biological behavior than Axelrod's and Hamilton's models when zoologist Martin Nowak and mathematician Karl Sigmund created "Pavlov," a Prisoner's Dilemma strategy based on "win-stay, lose-shift" that introduces punishment. Corning objects to inclusive fitness theory, reciprocal altruism, tit-for-tat as adequate explanatory frameworks because they exclude interactions that provide synergistic combined effects and are self-policing because they are interdependent – the way two oarsman are interdependent when trying to cross a river if they each have one oar. Corning claims "The intellectual fascination of the Prisoner's Dilemma game may have led us to overestimate its evolutionary importance."

Rejecting single-cause "prime mover" hypotheses for either biological or cultural evolution, Corning lists "five maybe six distinct paths to cooperation and complexity in evolution:" altruism, reciprocity, functional interdependence, mutualism, and parasitism.

In regard to humans, Corning points to specific probable synergistic packages that enabled proto-humans to evolve from tree-dwelling primates, for language to evolve as an adaptation on precursors, for hunting and gathering culture to dominate and spread, for fire use to be culturally maintained, and for settled agriculture to take root and replace nomadic foraging and hunting as the dominant human form of social organization. Asking how a small, lightweight primate that can't fly or run very fast, lacking natural defensive weapons, but having bipedal gait, manipulative hands, omnivorous digestive system and large brain managed to shift to an earthbound habitat, broaden its resource base, and expand its range, Corning proposes that "In a patchy but relatively abundant woodland environment that was also replete with predators, competitors , and sometimes hostile groups of conspecifics, group foraging and collective defense/offense was the most cost-effective strategy. There were immediate payoffs (synergies) for collective action that did not have to await the plodding pace of natural selection….There may well have been group selection, but it was not based on altruism. It involved what the economists call 'collective goods' or 'public goods.'"

Corning agrees with Jared Diamond that the emergence of agricultural civilization, empires, and wars of conquest in the fertile crescent 10,000 years ago was due to what Diamond himself called a "package" of ecological circumstances and cultural inventions that worked together synergistically: domesticated, genetically altered plants and animals, draft animals, technologies for plowing, cutting, threshing, grinding, food transport and storage, cooking, processing hides and fibers, sewing, manufacturing tools of stone, bone, and wood, as well as access to reliable fresh water sources, abundant fuel, long-distance trade, and defense against raiders. As a result, ten to one hundred times more people can be fed from one acre than from hunting-gathering, and a settled lifestyle permitted a reduction of the spacing of births from a four year separation among nomads to two years, leading to rapid population growth.

Corning cites contemporary examples of synergistic cultural evolution involving the creation of new forms of collective action, together with new toolsets. The Igorot people of the remote mountains of Luzon, in the Philippines, use a vast, elaborate, intricately constructed combination of terraces, dams, canals, and ponds to grow rice sustainably and with remarkable efficiency. It was originally thought that the system was thousands of years old, but anthropologist Charles Drucker turned up evidence indicating that lowlanders who had practiced slash-and-burn agriculture for millennia were forced to migrate to the highlands when Spanish invaders seized choice lowlands. The sustainable high yields of Igorot rice farming depends on constant replenishment of soil nitrogen in places where there is not a natural abundant supply. The Igorot use ponds of blue-green algae that live in symbiosis with the rice plants, receiving carbon dioxide from the rice in exchange for fixing nitrogen. In order to use and maintain this new, complex technological and ecological system the former slash-and-burn lowlanders had to invent a new social and political system involving the disciplined coordination of many family groups.

The Great Basin Shoshone of North America, studied by Julian Steward in the 1930s, forage in very small family groups, with plants providing 80% of their calories. In winter, however, several families gather in larger camps near an abundant resource and trade information, teach each other skills, and find mates. During rabbit drives, groups of 75 or more coordinate efforts deploying nets hundreds of feet long. A division of labor is temporarily established between net holders and beaters, under the supervision of a temporary rabbit boss.

Work by Gintis, Bowles, Fehr and Gächter indicate that strong reciprocity among humans is egoistic, not altruistic or cooperative, and depends on aggressive punishment of cheaters. This is related to work by Boyd and Richerson on group-serving norms of "fairness." Corning notes: "…the principle of fairness came to play a central role in reconciling conflicting claims of self-interest within the groups/bands/tribes that were indisipensable to our ancestors' survival and reproductive success over many thousands of generations."