Smart Mobs

by Howard Rheingold

  And that precision is critical to my argument. That precision allows me to treat the human group as a collection of coupled oscillators. Oscillation is one of the standard and simplest emergent phenomena. Once a group has become coupled in oscillation, we can treat the group as a single entity. To be sure, there’s more to music than simple oscillation. But oscillation is the foundation, the starting point, and all the elaboration and complexities take place within this framework.

  In effect, in musical performance (and in dance), communication between individuals is pretty much the same as communication between components of a single nervous system. It’s continuous and two-way, and it does not involve symbolic mediation. Think of Goffman’s interaction order, but drop verbal communication from it. It is a public space that is physically external to the brains of participating individuals, but it is functionally internal to those brains.61

  Kevin Kelly traced back the new theories regarding emergent properties to William Morton Wheeler, an expert in the behavior of ants.62 Wheeler called insect colonies “superorganisms” and defined the ability of the hive to accomplish tasks that no individual ant or bee is intelligent enough to do on its own as “emergent properties” of the superorganism. Kelly drew parallels between the ways both biological and artificial “vivisystems” exhibit the same four characteristics of what he called “swarm systems”:

  the absence of imposed centralized control

  the autonomous nature of subunits

  the high connectivity between the subunits

  the webby nonlinear causality of peers influencing peers63

  Steven Johnson’s 2001 book, Emergence, shows how the principles that Kelly extrapolated from biological to technological networks also apply to cities and Amazon.com’s recommendation system: “In these systems, agents residing on one scale start producing behavior that lies on one scale above them: ants create colonies; urbanites create neighborhoods; simple pattern-recognition software learns how to recommend new books. The movement from low-level rules to higher level sophistication is what we call emergence.”64 In the case of cities, although the emergent intelligence resembles the ant-mind, the individual units, humans, possess extraordinary onboard intelligence—or at least the capacity for it.

  At this point, connections between the behavior of smart mobs and the behavior of swarm systems must be tentative, yet several of the earliest investigations have shown that the right kinds of online social networks know more than the sum of their parts: Connected and communicating in the right ways, populations of humans can exhibit a kind of “collective intelligence.” In the summer between my smart mob inquiries in Scandinavia and my expedition to Tokyo, my inquiries brought me to a fellow who seems to have discovered the underpinnings of group intelligence. Bernardo Huberman, formerly at Xerox PARC, now scientific director of Hewlett-Packard’s Information Dynamics research laboratory, was doing intriguing research on the emergence of primitive forms of collective intelligence.

  I visited Huberman in his office, located in the same Palo Alto complex as the CoolTown laboratory. Huberman is a master of thinking of new ways of looking at familiar phenomena, seeing computer networks as ecologies, markets as social computers, and online communities as social minds. Originally a physicist, Huberman presents his findings in pages of mathematical equations. When I visited him in his office, he seriously agreed that “the Internet enables us to building collective intelligence.”65 At PARC, he had directed investigations of “the ecology of computation.” As soon as I told him about smart mobs, he jumped up and exclaimed, “The social mind!” And he dug out a chapter on “The Social Mind” that he had published in 1995. Huberman thought it useful to think of emergent intelligence as a social computation:

  Intelligence is not restricted to single brains; it also appears in groups, such as insect colonies, social and economic behavior in human societies, and scientific and professional communities. In all these cases, large numbers of agents capable of local tasks that can be conceived of as computations, engage in collective behavior which successfully deals with a number of problems that transcend the capacity of any individual to solve. . . . When large numbers of agents capable of symbolic-processing interact with each other, new universal regularities in their overall behavior appear. Furthermore, these regularities are quantifiable and can be experimentally tested.66

  The interesting statement is the last one. There have been varieties of theories about the Internet as the nervous system of a global brain, but Huberman and colleagues have made clever use of markets and game simulations as computational test beds for experiments with emergent group intelligence. The fall that I visited Huberman, he and his colleagues had used “information markets” to perform experiments in emergent social intelligence and found that group forecasts were more accurate than those of any of the individual participants’ forecasts.67 In information markets, members trade symbolic currency representing predictions of public information. The Hollywood Stock Exchange, for example, uses the market that emerges from the trading of symbolic shares to predict box office revenues and Oscar winners. The HP research team makes the extraordinary claim that they have created a mathematically verifiable methodology for extracting emergent intelligence from a group and using the group’s knowledge to predict the future in a limited but useful realm: “One can take past predictive performance of participants in information markets and create weighting schemes that will predict future events, even if they are not the same event on which the performance was measured.”68

  Decades ago, computer scientists thought that someday there would be forms of “artificial intelligence,” but with the exception of a few visionaries, they never thought in terms of computer-equipped humans as a kind of social intelligence. Although everyone who understands the use of statistical techniques to make predictions hastens to add the disclaimer that surprises are inevitable, and one of the fundamental characteristics of complex adaptive systems is their unpredictability, the initial findings that internetworked groups of humans can exhibit emergent prediction capabilities are potentially profound.

  Another research group that takes emergent group intelligence seriously is the laboratory at Los Alamos, where a group of “artificial life” researchers issued a report in 1998, “Symbiotic Intelligence: Self-Organizing Knowledge on Distributed Networks, Driven by Human Interaction.”69 The premise of this interdisciplinary team is based on the view proposed by some in recent years that human society is an adaptive collective organism and that social evolution parallels and unfolds according to the same dynamics as biological evolution. 70 According to this theory, which I will revisit in the next chapter, new knowledge and new technologies have made possible the evolution of the maximum size of the functioning social group from tribes to nations to global coalitions. The knowledge and tech- nologies that triggered the jump from clan to tribe to nation to market to network all shared one characteristic: They each amplified the way individual humans think and communicate, and magnified their ability to share what they know.

  The Los Alamos team, looking at some of the same characteristics of the Internet that Huberman and his colleagues investigated and citing a range of research that has only recently begun to emerge as a discipline, claim that “self-organizing social dynamics has been an unappreciated positive force in our social development and has been significantly extended, at least in scope, by new technologies.”71 The Los Alamos group cited evidence for their hypothesis that the self-organizing social systems that have driven human social evolution will be enhanced by self-organized, distributed, information and communication systems. The research conducted directly by the Los Alamos researchers reinforced Huberman et al.’s claim that groups of humans, linked through online networks, can make collective decisions that prove more accurate than the performance of the best individual predictors in the group. If it isn’t a dead end, the lines of research opened by Huberman’s team, the Los Alamos researchers, and others could amplify the powers of
smart mobs into entirely new dimensions of possibility, the way Moore’s Law amplified the powers of computer users.

  Will self-organized, ad hoc networks of computer wearers, mediated by privacy-protecting agents, blossom into a renaissance of new wealth, knowledge, and revitalized civil society, or will the same technological-social regime provide nothing more than yet another revenue stream for Disinfotainment, Inc?

  Or is that the wrong question? Given the direction of the technological, economic, and political changes I have touched on so far, I propose the following questions:

  What do we know now about the emergent properties of ad hoc mobile computing networks, and what do we need to know in the future?

  What are the central issues for individuals in a world pervaded by surveillance devices—in terms of what we can do about it?

  What are the long-term consequences of near-term political decisions on the way we’ll use and be affected by mobile, pervasive, always- on media?

  I hope that the understandings I’ve shared from my investigations of the past two years make it clear that smart mobs aren’t a “thing” that you can point to with one finger or describe with two words, any more than “the Internet” was a “thing” you could point to. The Internet is what happened when a lot of computers started communicating. The computer and the Internet were designed, but the ways people used them were not designed into either technology, nor were the most world-shifting uses of these tools anticipated by their designers or vendors. Word processing and virtual communities, eBay and e-commerce, Google and weblogs and reputation systems emerged. Smart mobs are an unpredictable but at least partially describable emergent property that I see surfacing as more people use mobile telephones, more chips communicate with each other, more computers know where they are located, more technology becomes wearable, more people start using these new media to invent new forms of sex, commerce, entertainment, communion, and, as always, conflict.

  8

  Always-On Panopticon . . . or Cooperation Amplifier?

  There is need to reflect upon and discuss which social practices and relationships need to be sheltered from the pressure effects of global, commercial networking. At a time in which people are frantically trying to get connected, we would do well to ask: when and where does it make sense to remain unconnected? While leaving intact many of the burdens of the industrial/automotive era, we have come perilously close to achieving complete slavery to email, digital work, and the wired and wireless apparatus that surrounds us.

  —Langdon Winner, “Whatever Happened

  to the Electronic Cottage?”

  New technologies arise that permit or encourage new, richer forms of non-zero-sum interaction; then (for intelligible reasons grounded ultimately in human nature) social structures evolve that realize this rich potential— that conver t non-zero-sum situations into positive sums. Thus does social complexity grow in scope and size.

  —Robert Wright, “Nonzero:

  The Logic of Human Destiny”

  Maybe You Should Refuse It

  If the citizens of the early twentieth century had paid more attention to the ways horseless carriages were changing their lives, could they have found ways to embrace the freedom, power, and convenience of automobiles without reordering their grandchildren’s habitat in ugly ways? Before we start wearing our computers and digitizing our cities, can the generations of the early twenty-first century imagine what questions our grandchildren will wish we had asked today? Technology practices that might change the way we think are particularly worthy of critical scrutiny: High-resolution screens and broadband communication channels aren’t widget-making machinery but sense-capturing, imagination-stimulating, opinion-shaping machinery. I begin this concluding chapter with critical perspectives on smart mobs because uncritical acceptance puts us at risk of hypnotizing ourselves with the assistance of the technology we’re attempting to evaluate.

  I’ve described teenage technology enthusiasts in Shibuya, Manila, and Stockholm. Evidence of early nonadopters among younger generations is also a valuable clue. Social norms regarding technology practices might subdivide into multiple subcultures in the future, segmented according to members’ moral stance toward mobile media. Rich Ling and Per Helmer-son’s study of Norwegian teens revealed that “a certain percent of all teens, about 10%15%, have resisted adoption of the mobile telephone. Like those adults who do not purchase a television, these teens often have clear ideologies against ownership and use.”1 Nicola Green’s research in the United Kingdom revealed that the college students she studied categorized mobile telephone users as “good users,” those who adjusted their use of the phone to their physical and social context; “bad users,” those who acted inconsiderately of others in hearing range; and “incompetent users” (“most often described as ‘parents’”), those who simply don’t know how to use mobile media.2

  “Maybe you should refuse it” is a good place to start thinking about what we need to do—but not, I believe, the place to stop thinking. For some people, refusing to buy the latest gadget is the healthiest response. For most people, individual decisions about the roles of mobile and pervasive technologies in our lives are more likely to involve matters of degree than crisply binary choices. I suspect that thoughtful technology usage in the future will require each person and family to decide which settings and which times should be sequestered from the reach of communication media. Will we be wiser in our choices of how to use the small screen in our hand than we were with the TV screen in what used to be the family room? When you or your children demand the latest sport shoe that doesn’t just flash lights but receives purchase recommendations from Blue-tooth beacons at the mall, keep in mind what an Amish gentlemen told me: “It’s not just how we use the technology that concerns us. We’re also concerned about what kind of people we become when we use it.”3

  Before plunging into the darker scenarios about the ways smart mob technologies could pose threats, I will declare my personal biases: I believe we can understand how smart mob media could threaten us and how they could benefit us. We have a lot to learn about technologies of cooperation. I believe that people could use this knowledge to construct democratic power. How we use smart mob technologies and what we know about how to use it could make a decisive difference.

  Smart mob technologies pose at least three kinds of potential threats:

  Threats to liberty: Pervasive computing is converging with ubiquitous surveillance, providing the totalitarian snoop power depicted in Orwell’s 1984.

  Threats to quality of life: From individual angst to deteriorating communities, it isn’t clear whether life in the infomated society delivers convenience faster than it erodes sanity and civility.

  Threats to human dignity: As more people turn more aspects of their lives over to symbiotic interaction with machines, the more mechanical and less humane we become.

  Can Discipline Evolve?

  In 2002, BBC News reported that the image of the average urbanite is caught on closed-circuit television cameras three hundred times a day.4 In 2001, Virgin Mobile admitted that they had stored the location records of every mobile call made by each one of its 1 million customers since the service launched in 1999.5 During Super Bowl XXXV, seven months before the terrorist attacks on the United States made high-tech surveillance checkpoints a part of daily American life, the face of every person who entered the stadium was captured by digital video cameras and compared computationally to a database of wanted criminals.6 In March 2002, Motorola and Visionics, the company that created the Super Bowl facial recognition system, announced their intention to market mobile telephones that include real-time facial recognition capabilities to law enforcement personnel.7

  Every telephone call, credit card transaction, mouse-click, email, automatic bridge toll collection, convenience market video camera, and hotel room electronic key collects and broadcasts personal information that is increasingly compiled, compared, sorted and stored by an unknown and possibly u
nknowable assortment of state security agencies and people who want to sell something. Context-aware, location-based, and agent-mediated services will multiply the amount of information that citizens will broadcast in the near future. The amount of information that comes back at us is multiplying at an alarming rate as well, as everyone who spends time clearing unsolicited commercial email (“spam”) from their inboxes knows.

  Although state-sponsored surveillance and much commercially motivated data collection is conducted for the most part without the consent or knowledge of the surveillant, issues of privacy today are complicated by the voluntary adoption of technologies that disclose private information to others. How many mobile telephone users know that they don’t have to make a call for others to triangulate their location? They only need to switch on the device. Will users of mobile and pervasive technologies have the power to cloak, give away, or sell their personal data clouds—or to know who is inspecting them?

  For decades, people have feared the use of surveillance technology as a tool of repressive social control by a totalitarian state—Orwell’s “Big Brother.”8 Orwell didn’t take into account the possibility that computing and communication technologies would seduce consumers into voluntarily trading privacy for convenience. David Lyon, an astute analyst of the surveillance society, made this observation about the effect of consumerism on contemporary surveillance:

  Things have changed since Orwell’s time, and consumption, for the masses, has emerged as the new inclusionary reality. Only the minority, the so-called underclass, whose position prevents them from participating so freely in consumption, now experience the hard edge of exclusionary and punitive surveillance. Anyone wishing to grasp the nature of contemporary surveillance must reckon with this fact. Whereas the major threat, for Orwell, came from the state, today consumer surveillance poses a series of novel questions which have yet to find adequate analytical and political answers. A perfectly plausible view is that in contemporary conditions consumerism acts in its own right as a significant means of maintaining social order, leaving older forms of surveillance and control to cope with the non-consuming residue.9