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Cognitive Democracy

- May 23, 2012

Over the last couple of years, Cosma Shalizi and I have been working together on various things, including, _inter alia_, the relationship between complex systems, democracy and the Internet. These are big unwieldy topics, and trying to think about them systematically is hard. Even so, we’ve gotten to the point where we at least feel ready to start throwing stuff at a wider audience, to get feedback on what works and what doesn’t. Here’s a paper we’re working on, which argues that we should (for some purposes at least), think of markets, hierarchy and democracy in terms of their capacity to solve complex collective problems, makes the case that democracy will on average do the job _a lot better_ than the other two ways, and then looks at different forms of collective information processing on the Internet as experiments that democracies can learn from. A html version is under the fold; the PDF version is here. Your feedback would very much be appreciated – we would like to build other structures on top of this foundation, and hence, really, _really_ want criticisms and argument from diverse points of view (especially because such argument is exactly what we see as the strength of democratic arrangements).

Cognitive Democracy

Henry Farrell (George Washington University) and Cosma Rohilla Shalizi (Carnegie-Mellon/The Santa Fe Institute)

In this essay, we outline a cognitive approach to democracy. Specifically, we argue that democracy has unique benefits as a form of collective problem solving in that it potentially allows people with highly diverse perspectives to come together in order collectively to solve problems. Democracy can do this better than either markets and hierarchies, because it brings these diverse perceptions into direct contact with each other, allowing forms of learning that are unlikely either through the price mechanism of markets or the hierarchical arrangements of bureaucracy. Furthermore, democracy can, by experimenting, take advantage of novel forms of collective cognition that are facilitated by new media.

Much of what we say is synthetic – our normative arguments build on both the academic literature (Joshua Cohen’s and Joshua Ober’s arguments about epistemic democracy; Jack Knight and James Johnson’s pragmatist account of the benefits of a radically egalitarian democracy and Elster and Landemore’s forthcoming collection on Collective Wisdom), and on arguments by public intellectuals such as Steven Berlin Johnson, Clay Shirky, Tom Slee and Chris Hayes. We also seek to contribute to new debates on the sources of collective wisdom. Throughout, we emphasize the cognitive benefits of democracy, building on important results from cognitive science, from sociology, from machine learning and from network theory.

We start by explaining social institutions should do. Next, we examine sophisticated arguments that have been made in defense of markets (Hayek’s theories about catallaxy) and hierarchy (Richard Thaler and Cass Sunstein’s ‘libertarian paternalism’) and discuss their inadequacies. The subsequent section lays out our arguments in favor of democracy, illustrating how democratic procedures have cognitive benefits that other social forms do not. The penultimate section discusses how democracy can learn from new forms of collective consensus formation on the Internet, treating these forms not as ideals to be approximated, but as imperfect experiments, whose successes and failures can teach us about the conditions for better decision making; this is part of a broader agenda for cross-disciplinary research involving computer scientists and democratic theorists.

Justifying Social Institutions

What are broad macro-institutions such as politics, markets and hierarchies good for? Different theorists have given very different answers to this question. The dominant tradition in political theory tends to evaluate them in terms of justice – whether institutions use procedures, or give results, that can be seen as just according to some reasonable normative criterion. Others, perhaps more cynically, have focused on their potential contribution to stability – whether they produce an acceptable level of social order, which minimizes violence and provides some modicum of predictability. In this essay, we analyze these institutions according to a different criterion. We start with a pragmatist question – whether these institutions are useful in helping us to solve difficult social problems.1

Some of the problems that we face in politics are simple ones (not in the sense that solutions are easy, but in the sense that they are simple to analyze). However, the most vexing problems are usually ones without any very obvious solutions. How do we change legal rules and social norms in order to mitigate the problems of global warming? How do we regulate financial markets so as to minimize the risk of new crises emerging, and limit the harm of those that happen? How do we best encourage the spread of human rights internationally?

These problems are pressing — yet they are difficult to think about systematically, let alone solve. They all share two important features. First, they are all social problems. That is, they are problems which involve the interaction of large numbers of human beings, with different interests, desires, needs and perspectives. Second, as a result, they are complex problems, in the sense that scholars of complexity understand the term. To borrow Scott Page’s (2011, p.25) definition, they involve “diverse entities that interact in a network or contact structure.2 They are a result of behavior that is difficult to predict, so that consequences to changing behavior are extremely hard to map out in advance. Finding solutions is difficult, and even when we find one, it is hard to know whether it is good in comparison to other possible solutions, let alone the best.

We argue that macro-institutions will best be able to tackle these problems if they have two features. First, they should foster a high degree of direct communication between individuals with diverse viewpoints. This kind of intellectual diversity is crucial to identifying good solutions to complex problems. Second, we argue that they should provide relative equality among affected actors in decision-making processes, so as to prevent socially or politically powerful groups from blocking socially beneficial changes to the detriment of their own particular interests.

We base these contentions on two sets of arguments, one from work on collective problem solving, the other from theories of political power. Both are clarified if we think of the possible solutions to a difficult problem as points on a landscape, where we seek the highest point. Difficult problems present many peaks, solutions that are better than the points close to them. Such landscapes are rugged — they have some degree of organization, but are not so structured that simple algorithms can quickly find the best solution. There is no guarantee that any particular peak is globally optimal (i.e. the best solution across the entire landscape) rather than locally optimal (the best solution within a smaller subset of the landscape).

Solving a complex problem involves a search across this landscape for the best visible solutions. Individual agents have limited cognitive abilities, and (usually) limited knowledge of the landscape. Both of these make them likely to get stuck at local optima, which may be much worse than even other local peaks, let alone the global optimum. Less abstractly, people may settle for bad solutions, because they do not know better (they cannot perceive other, better solutions), or because they have difficulty in reaching these solutions (e.g. because of coordination problems, or because of the ability of powerful actors to veto possible changes).

Lu Hong and Scott Page (2004) use mathematical models to argue that diversity of viewpoints helps groups find better solutions (higher peaks on the landscape). The intuition is that different individuals, when confronting a problem, “see” different landscapes — they organize the set of possible solutions in different ways, some of which are useful in identifying good peaks, some of which less so. Very smart individuals (those with many mental tools) have better organized landscapes than less smart individuals, and so are less likely to get trapped at inferior local optima. However, at the group level, diversity of viewpoints matters a lot. Page and Hong find that “diversity trumps ability”. Groups with high diversity of internal viewpoints are better able to identify optima than groups composed of much smarter individuals with more homogenous viewpoints. By putting their diverse views together, the former are able to map out more of the landscape and identify possible solutions that would be invisible to groups of individuals with more similar perspectives.

Page and Hong do not model the social processes through which individuals can bring their diverse points of view together into a common framework. However, their arguments surely suggest that actors’ different points of view need to be exposed directly to each other, in order to identify the benefits and drawbacks of different points of view, the ways in which viewpoints can be combined to better advantage, and so on. These arguments are supported by a plethora of work in sociology and elsewhere (Burt, Rossman etc). As we explain at length below, some degree of clumping is also beneficial, so so that individuals with divergent viewpoints do not converge too quickly.

The second issue for collective problem solving is more obvious. Even when groups are able to identify good solutions (relatively high peaks in the solution landscape), they may not be able to reach them. In particular, actors who benefit from the status quo (or who would prefer less generally-beneficial solutions) may be able to use political and social power to block movement towards such peaks, and instead compel movement towards solutions that have lower social and greater individual benefits. Research on problem solving typically does not talk about differences in actors’ interests, or in actors’ ability successfully to pursue their interests. While different individuals initially perceive different aspects of the landscape, researchers assume that once they are able to communicate with each other, they will all agree on how to rank visible solutions from best to worst. But actors may have diverse interests as well as diverse understandings of the world (and the two may indeed be systematically linked). They may even be working in such different landscapes, in terms of personal advantage, that one actor’s peak is another’s valley, and vice versa. Moreover, actors may differ in their ability to ensure that their interests are prosecuted. Recent work in political theory (Knight 1992, Johnson and Knight 2011), economics (Bowles and Naidu, 2008), political science (Hacker and Pierson 2010) and sociology details how powerful actors may be able to compel weaker ones to accept solutions that are to the advantage of the former, but that have lower overall social benefits.

Here, relative equality of power can have important consequences. Individuals in settings with relatively equal power relations, are, ceteris paribus more likely to converge on solutions with broad social benefits, and less likely to converge on solutions that benefit smaller groups of individuals at the expense of the majority. Furthermore, equal power relations may not only make it easier to converge on “good” solutions when they have been identified, but may stimulate the process of search for such solutions. Participating in the search for solutions and in decision-making demands resources (at a minimum, time), and if those resources are concentrated in a small set of actors, with similar interests and perspectives, the solutions they will find will be fewer and worse than if a wide variety of actors can also search.

With this in mind, we ask whether different macro-institutions are better, or worse at solving the complex problems that confront modern economies and societies. Institutions will tend to do better to the extent that they both (i) bring together people with different perspectives, and (ii) share decision-making power relatively equally. Our arguments are, obviously, quite broad. We do not speak much to the specifics of how macro-institutions work, instead focusing on the broad logics of these different macro-institutions. Furthermore, we do not look at the ways in which our desiderata interact with other reasonable desiderata (such as social stability, justice and so on). Even so, we think that it is worth clarifying the ways in which different institutions can, or cannot, solve complex problems. In recent decades, for example, many scholars and policy makers have devoted time and energy to advocating markets as the way to address social problems that are too complex to be solved by top-down authority. As we show below, markets, to the extent that they imply substantial power inequalities, and increasingly homogenize human relations, are unlikely to possess the virtues attributed to them, though they can have more particular benefits under specific circumstances. Similarly, hierarchy suffers from dramatic informational flaws. This prompts us to reconsider democracy, not for the sake of justice or stability, but as a tool for solving the complex problems faced by modern societies.

Markets and Hierarchies as Ways to Solve Complex Problems

Many scholars and public intellectuals believe that markets or hierarchies provide better ways to solve complex problems than democracy. Advocates of markets usually build on the groundbreaking work of F. A. von Hayek, to argue that market based forms of organization do a better job of eliciting information and putting it to good work than does collective organization. Advocates of hierarchy do not write from any such unified tradition. However, Richard Thaler and Cass Sunstein have recently made a sophisticated case for the benefits of hierarchy. They advocate a combination of top-down mechanism design and institutions designed to guide choices rather than to constrain them – what they call libertarian paternalism – as a way to solve difficult social problems. Hayek’s arguments are not the only case for markets, and Thaler and Sunstein’s are not the only justification for hierarchy. They are, however, among the best such arguments, and hence provide a good initial way to test the respective benefits of markets, hierarchies and democracies in solving complex problems. If there are better arguments, which do not fall victim to the kinds of problems we point to, we are not aware of them (but would be very happy to be told of them).

Hayek’s account of the informational benefits of markets is groundbreaking. Although it builds on the insights of others (particularly Michael Polanyi), it is arguably the first real effort to analyze how social institutions work as information-processors. Hayek reasons as follows. Much of human knowledge (as Polanyi argues) is practical, and cannot be fully articulated (“tacit”). This knowledge is nonetheless crucial to economic life. Hence, if we are to allocate resources well, we must somehow gather this dispersed, fragmentary, informal knowledge, and make it useful.

Hayek is explicit that no one person can know all that is required to allocate resources properly, so there must be a social mechanism for such information processing. Hayek identifies three possible mechanisms: central planning, planning by monopolistic industries, and decentralized planning by individuals. He argues that the first and second of these break down when we take account of the vast amount of tacit knowledge, which cannot be conveyed to any centralized authority. Centralized or semi-centralized planning are especially poor at dealing with the constant flows of major and minor changes through which an economy (or, as Hayek would prefer, a catallaxy) approaches balance. To deal with such changes, we need people to make the necessary decisions on the spot — but we also need some way to convey the appropriate information about changes in the larger economic system to him or her. The virtue of the price system, for Hayek, is to compress diffuse, even tacit, knowledge about specific changes in specific circumstances into a single index, which can guide individuals as to how they ought respond to changes elsewhere. I do not need to grasp the intimate local knowledge of the farmer who sells me tomatoes in order to decide whether to buy their products. The farmer needs to know the price of fertilizer, not how it is made, or what it could be used for other than tomatoes, or the other uses of the fertilizers’ ingredients. (I do not even need to know the price of fertilizer.) The information that we need, to decide whether to buy tomatoes or to buy fertilizer, is conveyed through prices, which may go up or down, depending on the aggregate action of many buyers or suppliers, each working with her own tacit understandings.

This insight is both crucial and beautiful3, yet it has stark limits. It suggests that markets will be best at conveying a particular kind of information about a particular kind of underlying facts, i.e., the relative scarcity of different goods. As Stiglitz (2000) argues, market signals about relative scarcity are always distorted, because prices embed information about many other economically important factors. More importantly, although information about relative scarcity surely helps markets approach some kind of balance, it is little help in solving more complicated social problems, which may depend not on allocating existing stocks of goods in a useful way, given people’s dispersed local knowledge, so much as discovering new goods or new forms of allocation. More generally, Hayek’s well-known detestation for projects with collective goals lead him systematically to discount the ways in which aggregate knowledge might work to solve collective rather than individual problems.

This is unfortunate. To the extent that markets fulfil Hayek’s criteria, and mediate all relevant interactions through the price mechanism, they foreclose other forms of exchange that are more intellectually fruitful. In particular, Hayek’s reliance on arguments about inarticulable tacit knowledge mean that he leaves no place for reasoned discourse or the useful exchange of views. In Hayek’s markets, people communicate only through prices. The advantage of prices, for Hayek, is that they inform individuals about what others want (or don’t want), without requiring anyone to know anything about anyone else’s plans or understandings. But there are many useful forms of knowledge that cannot readily be conveyed in this way.

Individuals may learn something about those understandings as a by-product of market interactions. In John Stuart Mill’s description:

But the economical advantages of commerce are surpassed in importance by those of its effects which are intellectual and moral. It is hardly possible to overrate the value, in the present low state of human improvement, of placing human beings in contact with persons dissimilar to themselves, and with modes of thought and action unlike those with which they are familiar. Commerce is now what war once was, the principal source of this contact.

However, such contact is largely incidental — people engage in market activities to buy or to sell to best advantage, not to learn. As markets become purer, in both the Hayekian and neo-classical senses, they produce ever less of the contact between different modes of life that Mill regards as salutary. The resurgence of globalization; the creation of an Internet where people who will only ever know each other by their account names buy and sell from each other; the replacement of local understandings with global standards; all these provide enormous efficiency gains and allow information about supply and demand to flow more smoothly. Yet each of them undermines the Millian benefits of commerce, by making it less likely that individuals with different points of view will have those perspectives directly exposed to each other. More tentatively, markets may themselves have a homogenizing impact on differences between individuals and across societies, again reducing diversity. As Albert Hirschman shows, there is a rich, if not unambiguous, literature on the global consequences of market society. Sociologists such as John Meyer and his colleagues find evidence of increased cultural and social convergence across different national contexts, as a result of exposure to common market and political forces.

In addition, it is unclear whether markets in general reduce power inequalities or reinforce them in modern democracies. It is almost certainly true that the spread of markets helped undermine some historical forms of hierarchy, such as feudalism (Marx). It is not clear that they continue to do so in modern democracies. On the one hand, free market participation provides individuals with some ability (presuming equal market access, etc.) to break away from abusive relationships. On the other, markets provide greater voice and choice to those with more money; if money talks in politics, it shouts across the agora. Nor are these effects limited to the marketplace. The market facilitates and fosters asymmetries of wealth which in turn may be directly or indirectly translated into asymmetries of political influence (Lindblom). Untrammeled markets are associated with gross income inequalities, which in turn infects politics with a variety of pathologies. This suggests that markets fail in the broader task of exposing individuals’ differing perspectives to each to each other. Furthermore, markets are at best indifferent levelers of unequal power relations.

Does hierarchy do better? In an influential recent book, Richard Thaler and Cass Sunstein suggest that it does. They argue that “choice architects”, people who have “responsibility for organizing the context in which people make decisions,” can design institutions so as to spur people to take better choices rather than worse ones. Thaler and Sunstein are self-consciously paternalist, claiming that flawed behavior and thinking consistently stop people from making the choices that are in their best interests. However, they also find direct control of people’s choices morally opprobrious. Libertarian paternalism seeks to guide but not eliminate choice, so that the easiest option is the “best” choice that individuals would make, if they only had sufficient attention and discipline. It provides paternalistic guidance through libertarian means, shaping choice contexts to make it more likely that individuals will make the right choices rather than the wrong ones.

This is, in Thaler and Sunstein’s words, a politics of “nudging” choices rather than dictating them. Although Thaler and Sunstein do not put it this way, it is also a plea for the benefits of hierarchy in organizations and, in particular, in government. Thaler and Sunstein’s “choice architects” are hierarchical superiors, specifically empowered to create broad schemes that will shape the choices of many other individuals. Their power to do this does not flow from, e.g., accountability to those whose choices get shaped. Instead, it flows from positions of authority within firm or government, which allow them to craft pension contribution schemes within firms, environmental policy within the government, and so on.

Thaler and Sunstein’s recommendations have outraged libertarians, who believe that a nudge is merely a well-aimed shove — that individuals’ freedom will be reduced nearly as much by Thaler and Sunstein’s choice architecture, as it would be by direct coercion. We are also unenthusiastic about libertarian paternalism, but for different reasons. While we do not talk, here, about coercion, we have no particular normative objection to it, provided that it is proportionate, directed towards legitimate ends, and constrained by well-functioning democratic controls. Instead, we worry that the kinds of hierarchy that Thaler and Sunstein presume actively inhibit the unconstrained exchange of views that we see as essential to solving complex problems.

Bureaucratic hierarchy is an extraordinary political achievement. States with clear, accountable hierarchies can achieve vast and intricate projects, and businesses use hierarchies to coordinate highly complex chains of production and distribution.4 Even so, there are reasons why bureaucracies have few modern defenders. Hierarchies rely on power asymmetries to work. Inferiors take orders from superiors, in a chain of command leading up to the chief executive officer (in firms) or some appointed or non-appointed political actor (in government). This is good for pushing orders down the chain, but notoriously poor at transmitting useful information up, especially kinds of information superiors did not anticipate wanting. As scholars from Max Weber on have emphasized, bureaucracies systematically encourage a culture of conformity in order to increase predictability and static efficiency.

Thaler and Sunstein presume a hierarchy in which orders are followed and policies are implemented, but ignore what this implies about feedback. They imagine hierarchically-empowered architects shaping the choices of a less well-informed and less rational general population. They discuss ordinary people’s bad choices at length. However, they have remarkably little to say about how it is that the architects housed atop the hierarchy can figure out better choices on these individuals’ behalf, or how the architectures can actually design choice systems that will encourage these choices. Sometimes, Thaler and Sunstein suggest that choice architects can rely on introspection: “Libertarian paternalists would like to set the default by asking what reflective employees in Janet’s position would actually want.” At other times, they imply that choice architects can use experimental techniques. The book’s opening analogy proposes a set of experiments, in which the director of food services for a system “with hundreds of schools” (p. 1), “who likes to think about things in non-traditional ways,” experiments with different arrangements of food in order to discover which displays encourage kids to pick the healthier options. Finally, Thaler and Sunstein sometimes argue that choice architects can use results from the social sciences to find optima.

One mechanism of information gathering that they systematically ignore is active feedback from citizens. Although they argue in passing that feedback from choice architects can help guide consumers, e.g., giving information about the content of food, or by shaping online interactions to ensure that people are exposed to others’ points of view, they have no place for feedback from the individuals whose choices are being manipulated to help guide the choice architects, let alone to constrain them. As Suzanne Mettler (2011) has pointed out, Thaler and Sunstein depict citizens as passive consumers, who need to be guided to the desired outcomes, rather than active participants in democratic decision making.

This also means that Thaler and Sunstein’s proposals don’t take advantage of diversity. Choice architects, located within hierarchies which tend generically to promote conformity, are likely to have a much more limited range of ways of understanding problems than the population whose choices they are seeking to structure. In Scott Page’s terms, these actors are may very “able” — they will have sophisticated and complex heuristics, so that each individual choice architect is better able than each individual member of the population to see a large portion of the landscape of possible choices and outcomes. However, the architects will be very similar to each other in background and training, so that as a group they will see a far more limited set of possibilities than a group of randomly selected members of the population (who are likely to have less sophisticated but far more diverse heuristics). Cultural homogeneity among hierarchical elites helps create policy disasters (the “best and brightest” problem). Direct involvement of a wider selection of actors with more diverse heuristics would alleviate this problem.

However, precisely because choice architects rely on hierarchical power to create their architectures, they will have difficulty in eliciting feedback, even if they want to. Inequalities of power notoriously dampen real exchanges of viewpoints. Hierarchical inferiors within organizations worry about contradicting their bosses. Ordinary members of the public are uncomfortable when asked to contradict experts or officials. Work on group decision making (including, e.g., Sunstein 2003) is full of examples of how perceived power inequalities lead less powerful actors either to remain silent, or merely to affirm the views of more powerful actors, even when they have independently valuable perspectives or knowledge.

In short, libertarian paternalism is flawed, not because it restricts peoples’ choices, but because it makes heroic assumptions about choice architects’ ability to figure out what the actual default choices should be, and blocks their channels for learning better. Choice architects will be likely to share a narrow range of sophisticated heuristics, and to have difficulty in soliciting feedback from others with more diverse heuristics, because of their hierarchical superiority and the unequal power relations that this entails. Libertarian paternalism may still have value in situations of individual choice, where people likely do “want” e.g. to save more or take more exercise, but face commitment problems, or when other actors have an incentive to misinform these people or to structure their choices in perverse ways in the absence of a ‘good’ default choice. However, it will be far less useful, or even actively pernicious, in complex situations, where many actors with different interests make interdependent choices. Indeed, Thaler and Sunstein are far more convincing when they discuss how to encourage people to choose appropriate pension schemes than when they suggest that environmental problems are the “outcome of a global choice architecture system” that could be usefully rejiggered via a variety of voluntaristic mechanisms.

Democracy as a way to solve complex problems

Is democracy better at identifying solutions to complex problems? Many — even on the left — doubt that it is. They point to problems of finding common ground and of partisanship, and despair of finding answers to hard questions. The dominant tradition of American liberalism actually has considerable distaste for the less genteel aspects of democracy. The early 20th century Progressives and their modern heirs deplore partisanship and political rivalry, instead preferring technocracy, moderation and deliberation (Rosenblum 2008). Some liberals (e.g., Thaler and Sunstein) are attracted to Hayekian arguments for markets and libertarian paternalist arguments for hierarchy exactly because they seem better than the partisan rancor of democratic competition.

We believe that they are wrong, and democracy offers a better way of solving complex problems. Since, as we’ve argued, power asymmetries inhibit problem-solving, democracy has a large advantage over both markets and technocratic hierarchy. The fundamental democratic commitment is to equality of power over political decision making. Real democracies do not deliver on this commitment any more than real markets deliver perfect competition, or real hierarchies deliver an abstractly benevolent interpretation of rules. But a commitment to democratic improvements is a commitment to making power relations more equal, just as a commitment to markets is to improving competition, and a commitment to hierarchy (in its positive aspects) is a commitment to greater disinterestedness. This implies that a genuine commitment to democracy is a commitment to political radicalism. We embrace this.

Democracy, then, is committed to equality of power; it is also well-suited to exposing points of view to each other in a way that leads to identifying better solutions. This is because democracy also involves debate. In competitive elections and in more intimate discussions, democratic actors argue over which proposals are better or worse, exposing their different perspectives to each other.

Yet at first glance, this interchange of perspectives looks ugly: it is partisan, rancorous and vexatious, and people seem to never change their minds. This leads some on the left to argue that we need to replace traditional democratic forms with ones that involve genuine deliberation, where people will strive to be open-minded, and to transcend their interests. These aspirations are hopelessly utopian. Such impartiality can only be achieved fleetingly at best, and clashes of interest and perception are intrinsic to democratic politics.

Here, we concur with Jack Knight and Jim Johnson’s important recent book (2011), which argues that politics is a response to the problem of diversity. Actors with differing — indeed conflicting — interests and perceptions find that their fates are bound together, and that they must make the best of this. Yet, Knight and Johnson argue, politics is also a matter of seeking to harness diversity so as to generate useful knowledge. They specifically do not argue that democracy requires impartial deliberation. Instead, they claim that partial and self-interested debate can have epistemological benefits. As they describe it, “democratic decision processes make better use of the distributed knowledge that exists in a society than do their rivals” such as market coordination or judicial decision making (p. 151). Knight and Johnson suggest that approaches based on diversity, such as those of Scott Page and Elizabeth Anderson, provide a better foundation for thinking about the epistemic benefits of democracy than the arguments of Condorcet and his intellectual heirs.

We agree. Unlike Hayek’s account of markets, and Thaler and Sunstein’s account of hierarchy, this argument suggests that democracy can both foster communication among individuals with highly diverse viewpoints. This is an argument for cognitive democracy, for democratic arrangements that take best advantage of the cognitive diversity of their population. Like us, Knight and Johnson stress the pragmatic benefits of equality. Harnessing the benefits of diversity means ensuring that actors with a very wide range of viewpoints have the opportunity to express their views and to influence collective choice. Unequal societies will select only over a much smaller range of viewpoints — those of powerful people. Yet Knight and Johnson do not really talk about the mechanisms through which clashes between different actors with different viewpoints result in better decision making. Without such a theory, it could be that conflict between perspectives results in worse rather than better problem solving. To make a good case for democracy, we not only need to bring diverse points of view to the table, but show that the specific ways in which they are exposed to each other have beneficial consequences for problem solving.

There is micro-level work which speaks to this issue. Hugo Mercier and Dan Sperber (2011) advance a purely ‘argumentative’ account of reasoning, on which reasoning is not intended to reach right answers, but rather to evaluate the weaknesses of others’ arguments and come up with good arguments to support one’s own position. This explains both why confirmation bias and motivated reasoning are rife, and why the quality of argument is significantly better when actors engage in real debates. Experimentally, individual performance when reasoning in non-argumentative settings is ‘abysmal,’ but is ‘good’ in argumentative settings. This, in turn, means that groups are typically better in solving problems than is the best individual within the group . Indeed, where there is diversity of opinion, confirmation bias can have positive consequences in pushing people to evaluate and improve their arguments in a competitive setting.

When one is alone or with people who hold similar views, one’s arguments will not be critically evaluated. This is when the confirmation bias is most likely to lead to poor outcomes. However, when reasoning is used in a more felicitous context, that is, in arguments among people who disagree but have a common interest in the truth, the confirmation bias contributes to an efficient form of division of cognitive labor. When a group has to solve a problem, it is much more efficient if each individual looks mostly for arguments supporting a given solution. They can then present these arguments to the group, to be tested by the other members. This method will work as long as people can be swayed by good arguments, and the results reviewed … show that this is generally the case. This joint dialogic approach is much more efficient than one where each individual on his or her own has to examine all possible solutions carefully (p. 65).

A separate line of research in experimental social psychology (Nemeth et al. (2004), Nemeth and Ormiston (2007), and Nemeth (2012)) indicates that problem-solving groups produce more solutions, which outsiders assess as better and more innovative, when they contain persistent dissenting minorities, and are encouraged to engage in, rather than refrain from, mutual criticism. (Such effects can even be seen in school-children: see Mercer, 2000.) This, of course, makes a great deal of sense from Mercier and Sperber’s perspective.

This provides micro-level evidence that political argument will improve problem solving, even if we are skeptical about human beings’ ability to abstract away from their specific circumstances and interests. Neither a commitment to deliberation, nor even standard rationality is required for argument to help solve problems.[^nemeth] This has clear implications for democracy, which forces actors with very different perspectives to engage with each others’ viewpoints. Even the most homogenous-seeming societies contain great diversity of opinion and of interest (the two are typically related) within them. In a democracy, no single set of interests or perspectives is likely to prevail on its own. Sometimes, political actors have to build coalitions with others holding dissimilar views, a process which requires engagement between these views. Sometimes, they have to publicly contend with others holding opposed perspectives in order to persuade uncommitted others to favor their interpretation, rather than another. Sometimes, as new issues arise, they have to persuade even their old allies of how their shared perspectives should be reinterpreted anew.

More generally, many of the features of democracy that skeptical liberals deplore are actually of considerable benefit. Mercier and Sperber’s work provides microfoundations for arguments about the benefits of political contention, such as John Stuart Mill’s, and of arguments for the benefits of partisanship, such as Nancy Rosenblum’s (2008) sympathetic critique and reconstruction of Mill. Their findings suggest that the confirmation bias that political advocates have are subject to can have crucial benefits, so long as it is tempered by the ability to evaluate good arguments in context.

Other work suggests that the macro-structures of democracies too can have benefits. Lazer and Friedman (2007) find on the basis of simulations that problem solvers connected via linear networks (in which there are few links) will find better solutions over the long run than problem solvers connected via totally connected networks (in which there all nodes are linked to each other). In a totally connected network, actors copy the best immediately visible solution quickly, driving out diversity from the system, while in a linear network, different groups explore the space around different solutions for a much longer period, making it more likely that they will identify better solutions that were not immediately apparent. Here, the macro-level structure of the network does the same kind of work that confirmation bias does in Mercier and Sperber’s work – it preserves diversity and encourages actors to keep exploring solutions that may not have immediate payoffs.5

This work offers a cognitive justification for the macro-level organization of democratic life around political parties. Party politics tends to organize debate into intense clusters of argument among people (partisans for the one or the other party) who agree in broad outline about how to solve problems, but who disagree vigorously about the specifics. Links between these clusters are much rarer than links within them, and are usually mediated by competition. Under a cognitive account, one might see each of these different clusters as engaged in exploring the space of possibilities around a particular solution, maintaining some limited awareness of other searches being performed within other clusters, and sometimes discreetly borrowing from them in order to improve competitiveness, but nonetheless preserving an essential level of diversity (cf. Huckfeldt et al., 2004). Such very general considerations do not justify any specific partisan arrangement, as there may be better (or worse) arrangements available. What it does is highlight how party organization and party competition can have benefits that are hard or impossible to match in a less clustered and more homogenous social setting. Specifically, it shows how partisan arrangements can be better at solving complex problems than non-partisan institutions, because they better preserve and better harness diversity.

This leads us to argue that democracy will be better able to solve complex problems than either markets or hierarchy, for two reasons. First, democracy embodies a commitment to political equality that the other two macro-institutions do not. Clearly, actual democracies achieve political equality more or less imperfectly. Yet if we are right, the better a democracy is at achieving political equality, the better it will be, ceteris paribus, at solving complex problems. Second, democratic argument, which people use either to ally with or to attack those with other points of view, is better suited to exposing different perspectives to each other, and hence capturing the benefits of diversity, than either markets or hierarchies. Notably, we do not make heroic claims about people’s ability to deliberate in some context that is free from faction and self-interest. Instead, even under realistic accounts of how people argue, democratic argument will have cognitive benefits, and indeed can transform private vices (confirmation bias) into public virtues (the preservation of cognitive diversity)6. Democratic structures – such as political parties – that are often deplored turn out to have important cognitive advantages.

Democratic experimentalism and the Internet

As we have emphasized several times, we have no reason to think that actually-existing democratic structures are as good as they could be, or even close. If nothing else, designing institutions is, itself, a highly complex problem, where even the most able decision-makers have little ability to foresee the consequences of their actions. Even when an institution works well at one time, the array of other institutions, social and physical conditions in which it must function is constantly changing. Institutional design and reform, then, is unavoidably a matter of more or less ambitious “piecemeal social experiments”, to use the phrase of Popper (1957). As emphasized by Popper, and by independently by Knight and Johnson, one of the strengths of democracy is its ability to make, monitor, and learn from such experiments.7 (Knight and Johnson particularly emphasize the difficulty markets have in this task.) Democracies can, in fact, experiment with their own arrangements.

For several reasons, the rise of the Internet makes this an especially propitious time for experimenting with democratic structures themselves. The means available for communication and information-processing are obviously going to change the possibilities for collective decision-making. (Bureaucracy was not an option in the Old Stone Age, nor representative democracy without something like cheap printing.) We do not yet know the possibilities of Internet-mediated communication for gathering dispersed knowledge, for generating new knowledge, for complex problem-solving, or for collective decision-making, but we really ought to find out.

In fact, we are already starting to find out. People are building systems to accomplish all of these tasks, in narrower or broader domains, for their own reasons. Wikipedia is, of course, a famous example of allowing lots of more-or-less anonymous people to concentrate dispersed information about an immense range of subjects, and to do so both cheaply and reliably8. Crucially, however, it is not unique. News-sharing sites like Digg, Reddit, etc. are ways of focusing collective attention and filtering vast quantities of information. Sites like StackExchange have become a vital part of programming practice, because they encourage the sharing of know-how about programming, with the same system spreading to many other technical domains. The knowledge being aggregated through such systems is not tacit, rather it is articulated and discursive, but it was dispersed and is now shared. Similar systems are even being used to develop new knowledge. One mode of this is open-source software development, but it is also being used in experiments like the Polymath Project for doing original mathematics collaboratively9.

At a more humble level, there are the ubiquitous phenomena of mailing lists, discussion forums, etc., etc., where people with similar interests discuss them, on basically all topics of interest to people with enough resources to get on-line. These are, largely inadvertently, experiments in developing collective understandings, or at least shared and structured disagreements, about these topics.

All such systems have to face tricky problems of coordinating their computational architecture, their social organization, and their cognitive functions (Shalizi, 2007; Farrell and Schwartzberg, 2008). They need ways of of making findings (or claims) accessible, of keeping discussion productive, and so forth and so on. (Often, participants are otherwise strangers to each other, which is at the least suggestive of the problems of trust and motivation which will face efforts to make mass democracy more participative.) This opens up an immense design space, which is still very poorly understood — but almost certainly presents a rugged search landscape, with an immense number of local maxima and no very obvious path to the true peaks. (It is even possible that the landscape, and so the peaks, could vary with the subject under debate.) One of the great aspects of the current moment, for cognitive democracy, is that it has become (comparatively) very cheap and easy for such experiments to be made online, so that this design space can be explored.

There are also online ventures which are failures, and these, too, are informative. They range from poorly-designed sites which never attract (or actively repel) a user base, or produce much of value, to online groupings which are very successful in their own terms, but are, cognitively, full of fail, such as thriving communities dedicated to conspiracy theories. These are not just random, isolated eccentrics, but highly structured communities engaged in sharing and developing ideas, which just so happen to be very bad ideas. (See, for instance, Bell et al. (2006) on the networks of those who share delusions that their minds are being controlled by outside forces.) If we want to understand what makes successful online institutions work, and perhaps even draw lessons for institutional design more generally, it will help tremendously to contrast the successes with such failures.

The other great aspect for learning right now is that all these experiments are leaving incredibly detailed records. People who use these sites or systems leave detailed, machine-accessible traces of their interactions with each other, even ones which tell us about what they were thinking. This is an unprecedented flood of detail about experiments with collective cognition, and indeed with all kinds of institutions, and about how well they served various functions. Not only could we begin to just observe successes and failures, but we can probe the mechanisms behind those outcomes.

This points, we think, to a very clear constructive agenda. To exaggerate a little, it is to see how far the Internet enables modern democracies to make as much use of their citizens’ minds as did Ober’s Athens. We want to learn from existing online ventures in collective cognition and decision-making. We want to treat these ventures are, more or less, spontaneous experiments10, and compare the success and failures (including partial successes and failures) to learn about institutional mechanisms which work well at harnessing the cognitive diversity of large numbers of people who do not know each other well (or at all), and meet under conditions of relative equality, not hierarchy. If this succeeds, what we learn from this will provide the basis for experimenting with the re-design of democratic institutions themselves.

We have, implicitly, been viewing institutions through the lens of information-processing. To be explicit, the human actions and interactions which instantiate an institution also implement abstract computations (Hutchins, 1995). Especially when designing institutions for collective cognition and decision-making, it is important to understand them as computational processes. This brings us to our concluding suggestions about some of the ways social science and computer science can help each other.

Hong and Page’s work provides a particularly clear, if abstract, formalization of the way in which diverse individual perspectives or heuristics can combine for better problem-solving. This observation is highly familiar in machine learning, where the large and rapidly-growing class of “ensemble methods” work, explicitly, by combining multiple imperfect models, which helps only because the models are different (Domingos, 1999) — in some cases it helps exactly to the extent that the models are different (Krogh and Vedelsby, 1995). Different ensemble techniques correspond to different assumptions about the capacities of individual learners, and how to combine or communicate their predictions. The latter are typically extremely simplistic, and understanding the possibilities of non-trivial organizations for learning seems like a crucial question for both machine learning and for social science.

Conclusions: Cognitive Democracy

Democracy, we have argued, has a capacity unmatched among other macro-structures to actually experiment, and to make use of cognitive diversity in solving complex problems. To make the best use of these potentials, democratic structures must themselves be shaped so that social interaction and cognitive function reinforce each other. But the cleverest institutional design in the world will not help unless the resources — material, social, cultural — needed for participation are actually broadly shared. This is not, or not just, about being nice or equitable; cognitive diversity is itself a resource, a source of power, and not something we can afford to waste.

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  1. Two qualifications are in order. First, we don’t think that justice and social order are unimportant. If our arguments imply social institutions that are either profoundly unjust or likely to cause socially devastating instability, they are open to challenge on these alternative normative criteria. Second, our normative arguments about what these institutions are good for should not be taken as an empirical statement about how these institutions have come into being. Making institutions, like making sausages and making laws, is usually an unpleasant process.[return to main text]

  2. Much more could of course be said about the meaning of the term “complexity”. In particular, it may later be useful to look at formal measures of the intrinsic complexity of problems in terms of the resources required to solve them (“computational complexity” theory, see Moore and Mertens), or the degree of behavioral flexibility of systems, such as interacting decision-makers (Badii and Politi; Shalizi, Klinkner and Haslinger). We should also note here that several decades of work in experimental psychology indicates that groups are better at problem-solving than the best individuals within the group (Laughlin, 2011). We do not emphasize this interesting experimental tradition, however, because it is largely concerned with problems which are, in our terms, rather simple, and so suitable to the psychology laboratory.[return to main text]

  3. Imagine trying to discover whether a locally-grown tomato in Pittsburgh is better, from the point of view of greenhouse-gas emission, than one imported from Florida. After working out the differences in emissions from transport, one has to consider the emissions involved in growing the tomatoes in the first place, the emissions-cost of producing different fertilizers, farm machinery, etc., etc. The problem quickly becomes intractable — and this is before a consumer with limited funds must decide how much a ton of emitted carbon dioxide is worth to them. Let there be a price on greenhouse-gas emission, however, and the whole informational problem disappears, or rather gets solved implicitly by ordinary market interactions.[return to main text]

  4. “Thus bridges are built; harbours open’d; ramparts rais’d; canals form’d; fleets equip’d; and armies disciplin’d every where, by the care of government, which, tho’ compos’d of men subject to all human infirmities, becomes, by one of the finest and most subtle inventions imaginable, a composition, which is, in some measure, exempted from all these infirmities.” — Hume, Treatise of Human Nature, book III, part II, sect. vii.[return to main text]

  5. Broadly similar results have come from experiments on learning and problem-solving in controlled networks of human subjects in the laboratory (Mason et al., 2008; Judd et al., 2010; Mason and Watts, 2012). However, we are not aware of experiments on human subjects which have deliberately varied network structure in a way directly comparable to Lazer and Friedman’s simulations. We also note that using multiple semi-isolated sub-populations (“islands”) is a common trick in evolutionary optimization, precisely to prevent premature convergence on sub-optimal solution (Mitchell, 1996).[return to main text]

  6. This resonates with Karl Popper’s insistence (1957, 1963) that, to the extent science is rational and objective, it is not because individual scientists are disinterested, rational, etc. — he knew perfectly well that individual scientists are often pig-headed and blinkered — but because of the way the social organization of scientific communities channels scientists’ ambition and contentiousness. The reliability of science is an emergent property of scientific institutions, not of scientists.[return to main text]

  7. Bureaucracies can do experiments, such as field trials of new policies, or “A/B” tests of new procedures, now quite common with Internet companies. (See, e.g., the discussion of such experiments in Pfeffer and Sutton.) Power hierarchies, however, are big obstacles to experimenting with options which would upset those power relations, or threaten the interests of those high in the hierarchy. Market-based selection of variants (explored by Nelson and Winter, 1982) also has serious limits (see e.g., Blume and Easley). There are, after all, many reasons why there are no markets in alternative institutions. E.g., even if such a market could get started, it would be a prime candidate efficiency-destroying network externalities, leading at best to monopolistic competition. (Cf.¬ Shapiro and Varian’s advice to businesses about manipulating standards-setting processes.)[return to main text]

  8. Empirically, most of the content of Wikipedia seems to come from a large number of users each of whom makes a substantial contribution or contributions to a very small number of articles. The needed formatting, clean-up, coordination, etc., on the other hand, comes disproportionately from a rather small number of users very dedicated to Wikipedia (see Swartz, 2006). On the role of internal norms and power in the way Wikipedia works, see Farrell and Schwartzberg (2008).[return to main text]

  9. For an enthusiastic and intelligent account of ways in which the Internet might be used to enhance the practice of science, see Nielsen. (We cannot adequately explore, here, how scientific disciplines fit into our account of institutions and democratic processes.)[return to main text]

  10. Obviously, the institutions people volunteer to participate in on-line will depend on their pre-existing characteristics, and it would be naive to ignore this. We cannot here go into strategies for causal inference in the face of such endogenous selection bias, which is pretty much inescapable in social networks (Shalizi and Thomas, 2011). Deliberate experimentation with online institutional arrangements is attractive, if it could be done effectively and ethically (cf. Salganik et al., 2006).[return to main text]