I only discovered this book recently but it contains some interesting insights into group decision making, providing a range of evidence to support — often counterintuitive — observations about the best conditions for knowledge creation. As such, it relates well to Alvin Goldman’s “veritistic selection practices” — social design aimed at maximising the truth value of aggregated opinion.

Produced at a time when prediction markets, blogs and wikis were attracting growing interest, it is the book’s analysis of the more traditional social collaborative processes that stood out for me.

A central idea early in the book is the Condorcet Jury Theorem, which states that — on binary and numerical judgements at least — a group is more likely to be correct than an individual under the conditions that:-

1. Majority rule is used
2. Each individual is more likely than not to be correct

Notably, only some of the group need to know the correct answer, as the rest will answer randomly preserving the effect. This is redolent of Millionaire’s “Ask the Audience” option, which another book The Wisdom of Crowds claimed is correct 91% of the time, more often than the phone a friend option. Some warn against calling this mathematical effect “wisdom”, however.

Sunstein goes on to provide a range of evidence supporting the observation that deliberation does not lead necessarily lead to more accurate outcomes than polled, statistical samples. This may be due to:-

1. “hidden profiles“, or accurate information available to a group which is not accessed in deliberation (perhaps because only a few members of the group possess it, or are reluctant to go against the grain and challenge the majority view);
2. The “common knowledge effect“, where shared knowledge has more of an influence on the group’s decision than information held individually;
3. Informational and reputational cascades, where individuals change their view or the willingness to speak out after hearing the views of others;
4. Group polarisation, where members of a group end up with more extreme views — in line with their initial tendencies — after debate.

What this all mean for knowledge creation on the social web? Perhaps that giving scores and weighting to reputation, while establishing authority and expertise, may also dissuade or detract from informed dissent, and that such dissent may also warrant recognition.

In another review of the book, Ethan Zuckerman noted:-

“A large number of the most interesting projects taking place on the internet use strategies to aggregate information from multiple users to create new knowledge …. analyzing these systems in terms of their effectiveness in getting people to reveal hidden knowledge is, in my opinion, an excellent framework for evaluation.”

This paper presents exploratory research around the topic of wisdom, exploring how it has been defined in the literature – both eastern and western – and what it means to postgraduates of information and library studies and information technology.

In their literature review, Rowley and Slack give a range of conceptions of wisdom, some more dependant than others on having knowledge as a foundation, with most seeing a role for action, judgement and foresight. Wisdom in organisations is also discussed, with the interesting idea of “Kairos time” being mentioned, or the ability to take the right action at the critical moment. Organisational strategy and wisdom is further linked with CSR, in that wise decision making today is made more complex by the ethical and social considerations of a globalized and networked world.

In a simple exploratory research design, the authors asked postgraduates to complete the sentence “wisdom is..”, then undertook content analysis on the responses to draw out key elements of the concept as understood by that population. Many – but interestingly far from all – conceptions included knowledge or knowing, experience and a sense of action or application.

At first I found it difficult to see the value of this work beyond the core concept analysis, which though interesting in its own right, didn’t seem all that useful. But I think it is in the relation to organisational learning that this work can be interestingly extended, through the characterisation of “wise” decision making and perhaps though contrasting the conceptions given here here to newer models such as crowd wisdom on the social web.