Aigents Social Computing for personalized social connectivity and reputation
Why do you think personalized social connectivity and reputation is so important? What’s the use of monitoring of social dynamics in online networks? We will talk about this, but let me ask you few more questions first.
Do you think we all are kinds of sensors, motors and processors connected to huge planetary computer? Do you think we need to have some understanding of what is the program being executed by it, what is its purpose, and what are our roles in such program? After all, do we all need to have any sort of control over the program being execution by us?
To understand this well, let’s consider notion of social computing. Social computing is principle underlying collective intelligence. It enables multiple independent agents to integrate their individual cognitive capabilities and cooperate towards reaching some goal, beneficial for entire community. This is the way microbiota in human body assumes wellness of its carrier. This is the way society of neurons in human brain controls successful operation of the entire body. This is the way ants reach consensus while pulling a wand towards ant hill. This is the way entire humanity moves forward making the life more safe and pleasant for most of its members.
The social computing principles appears on different levels. For instance, it is found how neural columns in brain do kind of voting when making decisions for our perceptions and actions. For another instance, all forms of human organization, including tyranny, democracy and anarchy are just different algorithms of reaching consensus. It is amazing that scales of the two instances are comparable. Number of neurons in neocortex is just few times greater than number of people on Earth. Nearly the same time is needed to send signal across segments of brain cortex and between human users in different computer network segments. The same hierarchical organization takes place in both cases, so fraction of percent of cells in the body actually control its operation and fraction of percent of Earth population execute control over the vast majority of people.
Moreover, development of computers make this more interesting. Long time over the biological evolution, memory capacity of individual agents was measured by DNA capacity which was increasing till appearance of primates. At that point, growth of genetic memory has stopped and evolution has switched to growth of neural memory, reaching the end point at human level. From this point, humans invented all sorts of artificial memories and artificial ways of knowledge transmission. Now, the capacities of computer systems and networks outperform ones of single human, making it part of the whole.
Let’s look how it works. Humans submit posts, comments, and queries to online networks and update it with their status changes. They send email and chat messages filtered and directed by the system. They obtain search results and push notifications which guide their behavior. These guiding search results and notifications contain payload computed by the system, based on user’s preference as we well as marketing and political agenda supplied by those who invest their power and money into maintenance of the whole thing.
Namely, must of such computer networks employ business model, where service is given to most of audience for free, but the limited fraction of customer audience is paying to gain control over the entire system, collecting sensory inputs from the audience computing the state of entire society which can be used for operation planning. Based on that, same power agents can be driving operations of the mass audience by means of paid ads delivering marketing or political news agenda.
It is a challenge for every member of such network to gain control over the situation — in one of the two possible ways. Either any end user should be given a way to implement that social computing in existing communication networks, or new decentralized networks should be created. In such distributed networks, the control of the network is performed by every user by technique called distributed consensus.
This technique has multiple implementations solving the one problem — how multiple independent agents in peer-to-peer network can reach the consensus in respect to any decision that they have to make. There are multiple approaches to this, with one of them widely used in modern distributed cryptocurrency networks such as Bitcoin and Ethereum. It is called “Proof-of-Work”, where agents vote for any decision with value of computing resources that they possess. This is also similar to governance in ancient societies where the most forceful male was leading the group. This technique makes possible to takeover the management of community just by collecting brute force resources in one hands. More advanced technique is called “Proof-of-Stake”, where power belongs to those who own more money at stake. It is similar to current organization of capitalist society with its own obvious drawback that richer become reacher and poor become poorer. What we are looking for is better form of consensus called “Proof-of-Reputation” where value of an agent is computed on the basis of reputation earned in his or her interactions with peers over the time, with account of reputation of the other peers themselves, hierarchically, building the reputation system from bottom o top.
To solve this problem, we are working to create personal agents for users of online networks. We do it with Aigents social computing platform which supports old social networks such as Facebook and Google Plus as well as new networks and blockchains such as Steemit and Ethereum. With such agent, you monitor changes in your social environment online and study how your own reputation changes over time, depending on your interactions with communication peers.
To try it, you just go to https://aigents.com web site, register with any of social networks, order your report and study your social graph at any time frame.
To build up this report, Aigents social computing platform considers posts and comments that you make along with comments made by your peers. It also accounts for likes or votes you make towards your posts and comments each to another, with your friends and colleagues.
For given period, these interactions are used to compute social values of your communication peers, such as best followers that track you, opinion leaders that you listen to or rather good friends and colleagues that you have tight mutual cooperation with.
This makes it possible to derive whole bunch of social relationships inferred from communiciation logs and dynamics of them being tracked in the time frames and over the time scale.
For one instance, you can track how amount of attention that you attract online and reputation that you gain changes based on topics that you discuss online and which of your friends and colleagues are contributing to the changes.
For another example, you can check which sociological type you are — whether you are leader, or follower, or you are surrounded with lots of peers with same level of reputation as you, or your are social hub connecting multiple opinion leaders with audience of your followers.
Further, in new social networks and blockchains like Steemit and Ethereum, you can browse reputation networks computed from posts, comments, votes and financial transactions from one user to another, figuring out top influencers in social networks or leading financial institutions on the financial networks.
Finally, now we work on account for sentiment and emotions involved in computing social relationships, so positive and negative impacts of communications can be studied in context of reputation networks. If this works, one could use our personal agent to make sure the relationship are not destroyed accidentally and avoid social engineering attempts directed towards us.
All that said, we do operate as part of social computing systems powered by computational networks with powers exceeding cognitive capabilities of our brains. Moreover, most of us don’t have any tools to measure impact of the system to us while those who do are able to do such manipulation. Now, we are making this kind of tools available for everyone.
Thank you for attention, try our work and let us know how we can make it better.