Collective Learning #Change11

The examples of collective learning by Allison Littlejohn from Caledonian Academy in her blog 'collective learning examples' which is week 4 of the Change11 MOOC draw primarily from industry. The first example is that of large companies like Amazon, Boeing, IBM, P&G and Merck which have been crowdsourcing ideas to foster innovation.

Some ideas come through proprietary channels and networks such as licensing, outsourcing, and joint ventures, but a large part come through open and amorphous social networks. The results have been very positive and produced breakthrough innovations for industry, health and the environment.

Having been a participant in a similar information jam (although it had more of a survey feel) I wanted to also express a frustration that can grow as a result of taking part. If ones idea is not one which is replicated by a fair number of other people then it is dismissed or not used. One may express oneself a number of times via an infojam or survey and if the ideas or submissions repeatedly come to nothing then the participant reaches a point where they feel there is no point in contributing. The same opinion I quite often hear about voting: 'there is no point to vote for a minority party because they will never get into power'. It maybe that part of the process involves reassuring those who take part that their contribution has value. This can be seen more clearly in he opening anecdote of The Wisdom of Crowds by James Surowiecki which 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 data was of a numerical value and in this case every guess had a value because it had an influence on the final average. The case is not the same for opinions and ideas.