* Essay: Cognitive Democracy. By Henry Farrell and Cosma Rohilla Shalizi. Crooked Timber, 2012.
Summary by Henry Farrell and Cosma Rohilla Shalizi:
“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 Josiah 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.” (crookedtimber.org/2012/05/23/cognitive-democracy/)
Excerpt 1: The key hypothesis: democracy beats markets and hierarchies at complex problem solving
“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). Democratic structures – such as political parties – that are often deplored turn out to have important cognitive advantages.
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.”
Excerpt 2: Internet and Democracy
“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.”