Seven Principles of Social Networking

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What emerged from the discussion were a set of principles which might provide some clues on how to develop Social Networking Applications that really do work, and how to establish processes that could enable and encourage effective networking in organizations. Here are the principles we came up with:

1. Social Relationships Must Meet Four Preconditions: Willingness to establish a relationship with someone presupposes the existence of mutual trust, respect, context, and self-disclosure between the parties. These qualities are exceedingly difficult to achieve without face to face contact. Social Software tries valiantly but for the most part unsuccessfully to provide a basis and framework for these qualities to emerge, using systems of recommendations and endorsements to create reputation, and degrees-of-separation referrals to create verification. The best these tools seem to provide is a rough filter of inappropriate candidates for relationships, a ‘negative assurance’ that there is no reason to believe you should not enter into a relationship with someone. But we tend to be distrustful of people’s online identities because they are so easy to fake and exaggerate. Online, no one knows you’re a dog. Weblogs seem to work better to establish credibility, perhaps because of their relative permanence and self-disclosure, but they demand a major investment in time and energy to maintain. It’s just a lot easier and faster to set up a face to face meeting and let the chemistry work (or not). Perhaps the next generation will find ways to do this virtually and more easily, but technology changes faster than culture, and I’m not optimistic that better software design can overcome our cultural resistance to share bits before we share atoms.
2. Relationships Require a Conversational Ice-Breaking: Conversations are much denser and hence more efficient and effective ways of transferring a lot of information while filling in context, than asynchronous communication mechanisms. Likewise, interviews are much more powerful ways to glean information from a subject than surveys. Even telephony lacks the face and body language clues that convey so much information in in-person conversations. Skype seems to convey more voice nuance than regular telephony, but, strangely, videoconferencing seems to add very little to the information content of virtual conversations. Perhaps this is due to bandwidth constraints or brief time delays in video transmission, but I suspect that chemical atoms passing between the parties in face to face conversations play a greater role than we’d care to admit — even technophiles confess that it’s much easier to get to ‘know’ a stranger in person than using even the most powerful technologies.
3. First Impressions Matter: Our quick Blink judgements about a person, an event or an idea (provided they fit with our frames of understanding and belief) are critically important, and seem very difficult to dislodge with later  information, no matter how compelling. Perhaps that’s why visual clues about strangers are so highly valued in establishing trust, context, disclosure and respect. “Sniff, sniff, it’s OK, he’s one of us”. Once we have established an impression or initial judgement, what we seem to seek most is reassurance that this initial assessment was valid. This introduces some obvious dangers: ideological echo chambers, groupthink and the proliferation of conspiracy theories for example. And just to make the situation worse. we tend to ignore and turn off information that we cannot (or don’t want to) change, which further entrenches those first impressions and judgements. Physical appearance hence becomes an icon of our identity.
4. Information Conveyed by Observation Counts More Than That Conveyed by Language: We instinctively give enormous credibility to our direct sensory observations, while we tend to consider what we’re told skeptically. Observation is a rich source of fast understanding and shared context. Our senses simply have much more information-processing bandwidth than the part of our brain that processes the spoken and written word. As a result, it may actually be more important to a relationship to see the other person’s environment than to see them. As Dave Snowden says: “We can always know more than we can tell, and we can always tell more than we can write down”. Observation allows us to mine data that the person to whom we are speaking cannot convey in words, or may not even be aware of. “Don’t tell me, show me.”
5. Collaboration is the Miracle Glue of Relationships: Doing something together, the more participatory and challenging the better, immediately establishes deep trust, respect, shared context, disclosure, even a shared identity (e.g. Lennon-McCartney). Collaboration is also an essential precondition to real community, far more effective than any amount of shared gossip, online chat and head-nodding agreement. Until we’ve worked on something together, our agreements may be simply politeness, insufficient to form the basis for a strong and lasting relationship. “We did that!“
6. Every Interaction Carries the Burden of Our Entire Networks: Throughout any relationship, conversation or interaction our brains are processing a series of social constructs: (a) Information (what am I learning from this interaction?), (b) Meaning (so what — what does this mean to me?) and (c) Implications (what should I do, decide or expect as a result?) Information, meaning and implications are rarely just personal — in each interaction we are considering how to forward or explain information and its meaning to others in our networks, how to justify and discuss its implications with others in our networks, and how to motivate others to take what we think are appropriate actions or decisions as a consequence. So there is a huge invisible ‘audience’ for each network interaction beyond the direct participants in it. Social Networking Applications need to recognize and involve this audience (by recording and forwarding the interaction, by inviting others affected to join in etc.) “I appreciate what you’re telling me, but how am I going to explain and work this out with A, B and C?”
7. Social Networks are Complex Systems: Social Software is designed as a solution to a complicated, rather than a complex, problem. We hope that we can one day in some way completely diagram, understand, and optimize use of our complete social networks, but the best we can hope for are possibly dangerous oversimplifications. The complexity of our networks simply cannot be fully known, explained or applied in any predictive way — there are too many variables and nuances of relationship to fully know, depict, or expect complicated-system software to handle. We should probably therefore be humbler about what we hope Social Networking Applications will be able to do for us. Their goal should perhaps be simply to better understand how our networks benefit us, how we can use them more effectively, and how to improve the quality and value of conversations and other interactions.

So as a result, these are the types of questions I think the designers and proponents of Social Networking Applications should be addressing:

• How is it that some people are able to manage larger and more sophisticated networks of people than others? What are those people doing that we should all learn about?
• If the costs of travel (financial, social, environmental) reach the point that face to face meetings between people farther away than the next community become prohibitively expensive, how can we best design simple virtual presence tools that simulate as richly as possible in-person conversations and other interactions?
• How can we enrich the experience of virtual collaboration so that it becomes almost as powerful, intuitive and adhesive as face to face collaboration?
• How can we design ‘cameras’ that allow the remote person, rather than the person in the same room, in a virtual conversation to control them, much as they would control their own eyes were they in that room, so they can observe what they want and not what the observed person wants?
• How can we make all of this technology essentially invisible and automatic to the users, so that they can focus fully on the conversation or other interaction instead of being constantly distracted by the technology?
• How can we identify simple rules that can explain complex systems like Social Networks, so that we can better understand how to make our networks and our social behaviours more effective, instead of trying to rely on massive databases, network maps and other ‘merely complicated’ system tools that pursue the impossible task of trying to describe these systems?
• How can we (likewise using complex systems techniques instead of hopelessly inadequate sociological and psychological models) understand the rules that influence the effective achievement of (or impede) trust, respect, mutual context and self-disclosure, so that we can build these more easily and recover when they are absent or lost?
• How can we learn to be better conversationalists and interviewers (which means better understanding the different information, communication and networking behaviours of different people)?
• How can Social Networking Applications allow us to easily bring in and drop off people from conversations and other interactions whose information or insight is highly pertinent, who are affected by the outcomes of the interactions, or who otherwise need to be temporary participants, so that we can actually leapfrog the physical limitations that currently constrain face to face meetings, so that in at least this respect virtual meetings will actually be more effective and robust (almost like the continuous interactions of bees or ants)?
• How can we learn to better understand the differences between how our brains work (collecting, organizing, applying and disseminating information within a single organism) and how our collective intelligence (our network) works?

These are not questions for programmers, analysts, sociologists or psychologists, but rather questions for cultural anthropologists, complex adaptive systems experts, and those knowledgeable about heuristics, neural networks and the Wisdom of Crowds. We need to develop much more skill in these emerging disciplines, because the old disciplines and the ‘merely complicated’ mechanisms for addressing these critical human challenges simply aren’t up to the job. As Einstein said, our current problems are not going to be solved using the same thinking that has given rise to them.