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Witology: Collective Mind to Respond to Intellectual Challenges

No large project can be done by one person. Since the time of the Egyptian pyramids construction the success of any enterprise has depended on appropriately organized collaborative efforts of large numbers of people. During wars and peacetime, hierarchical schemes have proved to be good, and information technologies have brought them almost to perfection over the past quarter of a century. However, as far as innovations are concerned, it all depends on the personal experience and creative intelligence of individuals. Hence, there are risks associated with astronomical fees of top managers whose intuition should compensate for the lack of a technology to recover the implicit knowledge.

If organized in the same way as a neural network, collective intelligence is likely to produce qualitatively new results.

But how can we effectively harness the intellectual power of a large number of people? Councils and committees are not smarter and more original than their most creative and competent members. Large groups of experts are conservative, slow and unoriginal. So, it turns out that intelligence as the ability to find unconventional solutions is non-additive, isn’t it? It was believed so until recently. Hope for a breakthrough lies in a brain analogy. If interactions between neurons give rise to individual human intelligence, then people can be probably organized in such a way that their collective intelligence is better than individual intelligence. So, you just have to find an appropriate architecture design enabling your business to make use of the tacit knowledge that can not be transferred from people’s heads into corporate databases. The development of such social business applications will govern the development of information technologies over the next decade.

There are two types of the architecture of collective intelligence, which are conventionally called social and semantic ones. The former is focused on people brought together in a social network that in the course of communication detects leaders and helps improve their proposals. Within the framework of this type, the techniques of brainstorming, foresight, and organizational activity games have emerged, but they all are unstable in terms of productivity and non-scalable in terms of the number of participants. The second approach puts emphasis on messages that contain ideas. Relations between messages make a semantic network, and analysis of the network reveals the key ideas. A system of scientific publications is created in this way, as well as the indexes of search engines and the rating systems for blog’s posts. But semantic networks are liable to various instabilities, such as wrapping, flames, and flash mobs.

Stabilization and scalability is achieved via combining social and semantic networks. Even the simplest technical means of their integration (for example, «friends + comments») give rise to proto-intellectual phenomena such as media viruses and «smart crowds». At the heart of the phenomena lies information dissemination riding on waves of strong emotions, and this has already found application in commerce and politics. A little closer to collective intelligence is crowdsourcing, when companies engage thousands of people in some activities in exchange for prizes or even participation in profits. The collaborative development of free software and information aggregation tools, such as Web 2.0 sites or prediction markets, is even more complex. Here, the participants exchange their modest contributions for respect of the community or other advantages.

The architecture of a platform to address diverse problems should combine social and semantic networks.

Successful collective intelligence applications are still unique, i.e. they are created based on intuition for particular projects. But general architecture principles are more or less clear, which means that soon there will be versatile tools to tap into collective intelligence to work systematically on a wide range of problems. In this new area, most successful will be those who start first with a right architecture.

Experiences of using different crowdsourcing models have shown that effective scalable collective intelligence can not emerge through individual techniques of working together cooperatively, as most of pioneering projects have demonstrated. It is essential to combine a variety of methods effective in their specific fields, into one system. As a result, thanks to the synergy effect of the combination, solutions can be found to problems for which uncoordinated social engineering technologies are inefficient or inapplicable.

Published research papers and competitive analysis show that such complex tools for creative collaboration will be available within 1-2 years. With the new generation of products, networked collective intelligence will acquire features of «big technology», when success is determined by the competent combination of proven methods of social engineering with innovative know-hows.

At first, crowdsourcing was chiefly to demonstrate its prospects. That is why most successful were the projects aimed at engaging mass audiences (blog-hosting services, Wikipedia, free software). The next generation collective intelligence technologies will provide large companies with competitive advantages. They will enable them to better use manpower resources to identify and solve important problems and quickly detect smart people and create for them additional opportunities for social uplift.

Witology is a leader of the fundamentally new class of social collaboration applications.

An example is the Witology platform that is now ready for beta testing. In terms of theory, the platform is based on social psychology and nonlinear dynamics. In practical terms, the platform rests upon on the current developments in the field of idea management, prediction markets, e-recruting, and other crowdsourcing methodologies, combining them with a number of proprietary core know-hows. Collective intelligence emerges on the basis of the socio-semantic network and a proprietary mechanism called «controlled chaos of ideas». Together they form a controlled environment in which solutions to a problem posed by the customer are generated and evolutionarily selected.

Collective intelligence created on the Witology platform is employed to find solutions to real-world problems, such as creating new products and identifying new markets, choosing innovation priorities based on the experience of a large number of people, using tacit knowledge to improve the efficiency and scalability of best practices, and finding bright, unexpected solutions that run counter to the established rules.
Wit-projects imply the multi-level parallel identification of the best ideas and smart people.

A simplified scheme of collective intelligence application is as follows. The facilitator on behalf of the customer set the community a task. In doing so, the facilitator encourages the participation of all potentially useful people who are directly or indirectly connected with the company. Then the task domain is structured, key problems being identified. All further work depends on this step, and the technologies applied at this stage determine, to a large extent, the success of the collective intelligence system as a whole. Then, to find solutions to the identified problems, the participants put forward ideas and contra ideas (in the form of texts), which are discussed, getting quotations like market ones. By betting on promising ideas, participants earn reputation that increases their influence on the community and makes them outstanding in the eyes of the facilitator. In that way runs the multi-level parallel filtering of ideas and people, customized for a specific task. The result is not only a solution to the problem, but also the formation of a relatively small, well-matched and well-established community of practice, which is capable of solving similar problems.

Tools of the socio-semantic network allow the facilitator to compensate for avalanche-like network effects, control the formation of clans, and stop speculative games that do not lead to any result. The reputation earned can be the basis for remuneration of the participants on the customer’s side. This increases the motivation of all participants, as opposed to the crowdsourcing models when the prize goes only to the person who has completed the solution. The reputation with regard to the nature of activity (creativity, criticism, provocation, precognition, etc.), as well as the topics of the problems solved, is the basis for invitation to new projects.

Organizations can use wit-projects as a means to improve their performance, answer to challenges and manage human capital in an intelligent way.

In large companies and organizations, the employees usually have clearly defined functions, and therefore their creativity is underutilized. Creative functions are concentrated among a few expensive specialists and top managers, which becomes a bottleneck for the development of innovative potential of the company.

Collective intelligence based on the socio-semantic network allows you reduce the deficiency in and cost of creativity, make use of the non-verbalized tacit knowledge of employees, and strengthen their loyalty. Collective intelligence is an innovative technology that improves the efficiency of corporate governance in the key sphere of innovations. Therefore, it is collective intelligence systems that will be a zone of the rapid development and intense competition of large companies and organizations in the coming years.