I am reading the book “Wisdom of Crowds by James Surowiecki“. Equity Market 3.0 and Economic Development 4.0 aim to create global Web 3.0 networks that aggregate communities of common interest to focus effort and make collective decisions using the Wisdom of Crowds. The Wisdom of Crowds aggregated through Web 3.0 networks are likely to make wiser collective decisions than those currently made by single members of the group. Web 3.0 networks facilitate the four conditions necessary to facilitate wise collective decision making – diversity of opinion, independence, decentralisation and aggregation. In summary, we can rely on the Wisdom of Crowds to run the world using Web 3.0 networks on the Critical Path to Economic Development 4.0.
I have extracted some paragraphs for your convenience, but encourage you to purchase the book from Amazon and read the book.
Extract from Wikipedia entry “Wisdom of Crowds“
I have extracted the following paragraphs from Wikipedia :
- The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations, published in 2004, is a book written by James Surowiecki about the aggregation of information in groups, resulting in decisions that, he argues, are often better than could have been made by any single member of the group. The book presents numerous case studies and anecdotes to illustrate its argument, and touches on several fields, primarily economics and psychology.
- The opening anecdote relates Francis Galton’s surprise that the crowd at a county fair accurately guessed the weight of an ox when their individual guesses were averaged (the average was closer to the ox’s true butchered weight than the estimates of most crowd members, and also closer than any of the separate estimates made by cattle experts).
- The book relates to diverse collections of independently-deciding individuals, rather than crowd psychology as traditionally understood. Its central thesis, that a diverse collection of independently-deciding individuals is likely to make certain types of decisions and predictions better than individuals or even experts, draws many parallels with statistical sampling, but there is little overt discussion of statistics in the book.
Four elements required to form a wise crowd:
- diversity of opinion (each person should have some private information, even if its just an eccentric interpretation of known facts),
- independence (people’s opinions are not determined by the opinions of those around them)
- decentralization (people are able to specialise and draw on local knowledge)
- aggregation (some mechanism exists for turning private judgements into a collective decision)
According to Surowiecki, these key criteria separate wise crowds from irrational ones:
Based on Surowiecki’s book, Oinas-Kukkonen captures the wisdom of crowds approach with the following eight conjenctures:
- It is possible to describe how people in a group think as a whole.
- In some cases, groups are remarkably intelligent and are often smarter than the smartest people in them.
- The three conditions for a group to be intelligent are diversity, independence, and decentralization.
- The best decisions are a product of disagreement and contest.
- Too much communication can make the group as a whole less intelligent.
- Information aggregation functionality is needed.
- The right information needs to be delivered to the right people in the right place, at the right time, and in the right way.
- There is no need to chase the expert.
You can read the Wikipedia entry here.
Additional extract directly from the book:
“If a group satisfies those conditions, its judgement is likely to be accurate. Why? At heart, the answer rests on a mathematical truism. If you ask a large enough group of diverse, independent people to make a prediction or estimate a probability, and then average those estimates, the errors each of them makes in coming up with an answer will cancel themselves out. Each person’s guess, you might say, has two components: information and error. Subtract the error, and you’re left with the information.” (p.10)
“Truly successful decision making, ofcourse, demands more than just a picture of the world as it is. It demands in addition a picture of the world as it will (or at least may) be. Any decision-making mechanism therefore has to be good under conditions of uncertainty.” (p.11)