In the late ’90s Marvin Minsky published a book called ‘Mentopolis’. He documented the human brain as a distributed network, consisting of a multiple agents, where each one of those agents is responsiple for just one operation. In the picture below, for example, he proposed that in order for our brain to recognize an apple all these agents should be set in motion. The ‘color’ agent should collect his information and send it to the ‘look to’ agent, who in his turn would communicate with the ‘place’ agent and so forth. My interest in this network (called the find-machine by Minsky) is not its credibility but its properties and attributes.

Emergent networks

The system Minsky composed was a typical example of an emergent network, namely a system with multiple agents dynamically interacting in multiple ways, following local rules and oblivious to any higher-level instructions. Minsky visualized a perfectly functioning system, with absolutely no central control. The nodes (meaning the agents) are interacting in order for their microbehavior (sorting color, size, etc.) to result in a macrobehavior (perceiving the object). Such organizations are present in nature (see the work of Deborah Gordon on the emergent behavior of ants), computer software and even in the structure of cities and are giving us a glimpse of networks, which correctly aggregate information.

Emergent systems function so perfectly, because they work with neighbor interaction, feedback, pattern recognition and indirect control. They are designed to learn from the ground level, to take advantage of local knowledge for an upper goal. Through interaction, they are capable of recognizing patterns and indirectly controlling the whole system.

Emergent social web

I’m not implying that the social web undertakes a completely emergent behavior. We are dealing neither with oblivious users nor with pattern recognition systems (at least not yet). But still there are perfectly functioning communities, which adopt the traits of an emergent behavior (probably slashdot, wikipedia and the linux operating system being the most profound examples). There is not any administrator – at least not in the traditional sense – leading the community. The users are self organized, sometimes each one responsible for a specific activity and always working together to provide quality material. Under that perspective we are experiencing the formation of online emergent networks, which are developing a life of their own – a life without any central control.

But what makes such behavior so successful? As I argued on my previous post regarding aggregation of knowledge (and your additions are mostly welcome on this), their success lies on:

• diversity
• independence
• indirect control
• self-organization

Conclusion

If such systems (and among them is the World Wide Web itself) manage so successfully to collect knowledge without any central power, why should we accept the control of any authority, which would define who posts which article and who links where? Years of experience show us that such ‘problems’ of the web can regulate themselves.

In following posts I will concentrate explicitly on each of the above-named traits of emergent networks with the hope of justifying my thesis, that expertise is not the only path to knowledge.

For this post the book of Steven Johnson: Emergence and of Marvin Minsky: Mentopolis (where the photo also comes from; original was in german, I translated it) where of great assistance.