Created on Jan. 15, 2013, 9:48 a.m. by antonkulaga & updated on Jan. 15, 2013, 10:36 a.m. by Hevok
A system is not a simple the sum of its components. Collective intelligence_, the intelligence of teams, communities and society as a whole is not a simple sum of intelligences of its members.
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People are connected in social graphs, in which they communicate, coordinate, and collaborate. They are like neurons in the brain. The smarter this social brain is the better scientific and social results it produces.
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Every transaction there has its cost, so called transaction cost by reducing this costs we let "neurons" make more connections, transmit more syignals, do it faster and with less distortions. Different software systems and pProject methodologies may be used for such kinds of improvements. For instance Semantic </span><del style="background:#ffe6e6;">w</del><ins style="background:#e6ffe6;">W</ins><span>eb in conjunction with mMachine lLearning algorithms, sSemantic qQuering, visualizations, text-mining and autosuggessions may improve how the knowledge is shared and transformed.
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Every individual mind is augmented and extended by the means that s/he uses and people s/he shares and improves its ideas with. It is called Extended </span><del style="background:#ffe6e6;">m</del><ins style="background:#e6ffe6;">M</ins><span>ind concept. It means that an intelligence of a person with search, wWikipedia and abilities to communicate and take advice from others is extended and s/he may solve much more complex tasks and create better ideas and decisions than the same person without this means avalilable. We can use knowledge management and eExpert systems, that will allow to augment everyones intelligence in a better way. We can also provide artificial </span><del style="background:#ffe6e6;">i</del><ins style="background:#e6ffe6;">I</ins><span>ntellige</span><ins style="background:#e6ffe6;">n</ins><span>t </span><del style="background:#ffe6e6;">a</del><ins style="background:#e6ffe6;">A</ins><span>gents that may do some work interacting with both people and knowledge (like bots in wWikipedia). We can also tackle not only augmentation part byut natural part as well by providing better means of education and training. Good models and practisces (i.e. argumentation techniques [http://www.semantic-web-journal.net/sites/default/files/swj138.pdf ]) with their support in our software may also come in handy.
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People collaborate and share results of their effort not randomly but in accordance to some institutions, formal and informal rules, protolocols and mechanisms of how controlling how the rules are performed, By improving this rules and protocols we may rewire the social brain and make it work more productively. Reputation currencies that partially replace money and other market institutions, collaborative filtering and other fancy means may be come in handy here.
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So, we arrive to a conclustions that software in combination with different orgraninzation and knowledge management techniques may greatly improve collective ingtelligence of teams, communities and society that ion its bturn will boost science.
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Being a pProgrammer it is easy to arrive at this conclusion byut it is hard to make something that really cChanges the state of the aArt. Different pProjects and communities int this field exist, but their results are not too powerful. There are ma lof ofny reasons for that.
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One of which is that most of them stew on their own juice, there is no tight collaboration between different communities. We see a lot of pProjects in sScience, tech and business that try to do something in the field, i.e. sSemantic wWeb pProjects, reputation currencies etc. But they do it separately with weak resulsts exchange of results.
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We want to change the state of the aArt. What we need is...:
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0). Understanding, what techniques and algorithmes are applicable for which cases.
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1). Bricks. Opens Source libraries (like NLP, hypegraphs, autosuggessions, logical inference etc.), piublic APIs and oOntologies that can be easily used in different pProjects.
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2). Experiments. We must try different bricks together and see how the work too improve them and their usage.
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3). Real world Projects that heavily use all this stuff. Projects like Denigma, for instance. They are the main purpose and ending result. We have to find such pProjects, define whatow similar they havre, let them exchange data where possible, create/use bricks for them, join efforts on the bricks that we have.
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4). Foundation. People and teams of people that rResearch, create, promote and fund all of this.
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5). Better collaboration inside of foundation teams. A shoemaker without shoes is defineitely not the option for us. We do complex things and we must try to become more productive with means we develop as soon as possible to engage more people and to do more.
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¶We create it out of bricks. Opens Source modules that can be easily mixed together through open APIs.
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