Exploring How Many Minds Produce Knowledge

One of the quotes I go back to often is a quote from a 1945 paper by the economist Hayek where he says:

The economic problem of society … is not merely a problem of how to allocate ‘given’ resources – if ‘given’ is taken to mean given to a single mind … It is rather a problem of how to secure the best use of resources known to any of the members of society … a problem of the utilization of knowledge which is not given to anyone in its totality. (Friedrich Hayek, The Use of Knowledge in Society, American Economic Review, No 35 (September, 1945) pp. 1 – 18)

I am fascinated by the timing of this quote (1945) and the insight that Hayek brings to a problem we still face today — getting the “many minds” in our organizations (or in society) to produce knowledge. So when I saw the title of Cass Sunstein’s book Infotopia and its subtitle (how many minds produce knowledge) and the one word endorsement from Lawrence Lessig (Extraordinary) I was drawn to purchase and read this book (Sunstein, 2006). At writing, Sunstein was Felix Frankfurter Professor of Law at Harvard Law School — a perspective that will interest many Slawyers and Slaw readers.

Given my research and practice interests, I am fascinated by anyone exploring the notion of human networks, collectives or connectives for the production of knowledge. This includes a collections of authors such as: Levy’s work around Collective Intelligence (Levy, 1997); Derrick De Kerckhove and his work exploring Connected Intelligence (De Kerckhove, 1997) – note that Derrick makes a distinction about the collective versus the connective; Fisher and Fisher’s work on the Distributed mind (note again the reference to collective intelligence) (Fisher & Fisher, 1998); and, Surowieki’s book on the Wisdom of Crowds (Surowiecki, 2004). To this list, I can now add Sunstein’s Infotopia (Sunstein, 2006).

In Infotopia, Sunstein explores and builds explicitly on the Hayekian view of markets as a means of producing knowledge. More specifically, the emerging uses of prediction markets inside organizations (e.g. Google, Microsoft, HP) and in public spheres (e.g. the Iowa Electronic Market). He explores and eclectic collection of technologies and techniques as a means for knowledge production in groups: wikis; prediction markets; open source software; and (almost as an afterthought) blogs. It is an interesting selection, which, with hindsight, one might broaden. Nevertheless, his exploration is worthy of review and examination.

With prediction markets (a form of knowledge marketplace) he shows how reasonably broad (not thin) prediction markets have demonstrated eerily accurate predictions on broad subjects. Organizations use them to examine their external environments as well as to predict and explore future scenarios they may face. They have also outstripped polls and surveys as a way to predict outcomes – even, for example, in elections.

He marvels at Wikis as a democratic way of aggregating and producing knowledge. He uses the obvious example of Wikipedia; but also uses a number of other examples where wikis provide the basis for knowledge aggregation – where no one has the knowledge in its totality.

He explores open source software as a movement and the rewards of reputation and rank that come through performance. While I pick at his use of terms such as “open source science” and open source biotechnology” (I prefer to drop the term ‘source’ and refer to these as “open science”; “open biotechnology” since there is no source code involved) this language does not detract significantly from his underlying arguments. However, he misses the movement towards open access to academic publications and notions such as open innovation. Perhaps this too is the difference of three years of activity and hindsight. He misses as well, in my estimation, the role strong leadership and community play in successful open source initiatives (for every successful open source project there are many failed ones and my hypothesis is that leadership is at the core of these successes).

He speaks to jury decisions and explores the Condorcet Jury Theorem. Sunstein deals with the near-real-time production of knowledge involved with things like decision making and policy setting. This is opposed to our large focus in KM communities on the collection, storage and retrieval and re-use of knowledge over time. He speaks to both sides of the coin – the good and the bad of knowledge creation within groups. Building optimistically on a Hayekian view of the markets and an efficient means of knowledge aggregation and production; while exploring the dark side of groups (e.g. groupthink; mob psychology; the suppression of dissenting viewpoints through social influences and informational signaling in groups.

He explores in some detail “four big problems” with groups:

…They amplify the errors of their members. They do not elicit the information their members have. They are subject to cascade effects, producing a situation in which the blind lead the blind. Finally, they show a tendency to group polarization, by which groups go to extremes. (Sunstein, pg. 75)

He draws distinctions between statistical groups (Surowiecki’s Wisdom of Crowds) and deliberating groups (where positions can become more entrenched through things like information cocooning and the echo chambers of thought created by homogenous cognitive models). He explores, in some detail, the reasons why deliberating groups amplify cognitive errors and result in super-entrenched positioning.

He touches on the needs for rewards and incentives to encourage the sharing of information that individuals have; noting that often the sharing of information does not benefit the discloser but usually the group – while disincentives can outweigh these dramatically. This leads to the under-explored area of knowledge economics.

He promotes the emphasis and development of strong norms of critical thinking. He encourages organizations to embrace, not suppress, information diversity through a variety of explicit techniques. He focuses on the role of the Internet in supporting both a utopian and dystopian view of groups and knowledge. And, in so doing, offers antidotes to protect against some of the potential pitfalls.

While this book feels a bit dated, it is well worth reading. Finally, I am interested if you have other books of resources that fall into this line of thought – exploring the connections between us mere mortals or experts. If you have any contributions to make to this expanding list of authors and the literature, I would be happy to hear from you.

De Kerckhove, D. (1997). Connected intelligence : the arrival of the Web society. Toronto: Somerville House.

Fisher, K., & Fisher, M. D. (1998). The distributed mind : achieving high performance through the collective intelligence of knowledge work teams. New York: AMACOM.

Levy, P. (1997). Collective intelligence : mankind’s emerging world in cyberspace. Cambridge, Mass.: Perseus Books.

Sunstein, C. R. (2006). Infotopia: how many minds produce knowledge: Oxford University Press.

Surowiecki, J. (2004). The wisdom of crowds : why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations (1st ed.). New York: Doubleday :.