I spent a great couple of days this week discussing ideas around Social Software with some people who are researching, developing and thinking about it.  A lot has been discussed under a blanket NDA however so unfortunately no names or product mentioned here.

A really interesting comment that came up which I hadn’t really thought about too much before, was that social software is inherently selfish software.  The idea behind this is that ultimately the tools and mechanisms that drive social software adoption are really self serving.  The beauty of course is that why social software works is that my selfish behaviour drives a collective good, but ultimately it’s selfish.

Let’s consider a few of these:

• Technorati lets blog authors track their authority and relevance.  Why do I ping them, because it lets me know who’s linking to me.
• Tagging of any form — tagging is about helping me find me content again.
• Blogging — because it’s the easiest way to (be heard; say something; speak to a crowd; insert your reason here).

The feedback mechanism that encourages users to participate on most social software type sites is also a selfish one in the sense the reward you derive is a personal satisfaction.  How many comments did I get? How many friend requests? How many notifications? How many links and ping-backs?  Would you keep blogging if no-one read what you had to say?

I went searching to find some sites that support this idea, but didn’t come up with too many standouts, however I did like this one:

• http://12frogs.com/12/work/iasummit2006/ I love the poster on this site as it really shows the circular nature of the software and how increasing usage feeds itself.

If I re-word selfishness, I’d say it’s self-reward that promotes the use of social software.  The best social software promotes me to interact and share with others because there is a direct link to a personal reward.

I’ve just returned from LotusSphere 2008 and had a great time.  While the presentations and demos are interesting, I found the most insightful part of the time there was spent in the Innovation and Development labs talking with developers about the advances they are making.  In the Innovation lab in particular, deep conversations can develop and you walk away feeling that some of the concepts will make it into a code.

 Loosely speaking, you can categorise a lot of the Web 2.0 tools and concepts into two very high level, broad categories like:

• Organisational Networks - LinkedIn, FaceBook, MySpace, Digg, Del.i.cious etc.
• Collaborative Creation  (Wisdom of Crowds type tools) - Wiki’s, Blogs etc.

What’s clear from LotusSphere is that IBM are clearly taking these broad brush categories (perhaps more or less) and building out tool sets like Quickr and Connections that apply these into the corporate world.

There are many reasons why this is appealing to corporates, not least command and control within the firewall on what is going on, but the most interesting idea is how it relates to Knowledge Management (KM). 

In my nearly 20 years in IT, I’ve been involved in various projects in different companies that again and again have tried to address the issue of KM.  What these Knowledge Management 1.0 efforts have all had in common, and why they’ve failed, is that they try and formalise the capturing of knowledge that is expressed and documented.  When I have to consciously make an effort, through modifying my natural processes and procedures, to share with you, then ultimately the effort will fail.  It fails because ultimately, the value in it for me, is not as great as the value in it for you.  Once the latest KM drive loses steam, I’ll drift back to my old ways and the path of least resistance.

In KM terms this type of knowledge is called Explicit knowledge.

Nickols, F. W. (2000). The knowledge in knowledge management. In Cortada, J.W. & Woods, J.A. (Eds) The knowledge management yearbook 2000-2001 (pp. 12-21). Boston, MA: Butterworth-Heinemann.
It’s worth taking a moment to browse the citation as it gives an excellent summary of the three main types of Knowledge as described in KM terms, I’ve paraphrased what I think are the key three here:

• Explicit - What has been expressed and captured
• Implicit - What can be expressed, but isn’t captured
• Tacit - What can’t be expressed (so by definition isn’t captured).

As an aside, I suspect the categories of Tacit knowledge are decreasing over the years (biometrics probably couldn’t be expressed years ago, but now we have computers that can recognise faces in crowds).  Anyway, my point is this, while the Web 2.0 world and the categories of tools bring real value to corporations, one form of value I haven’t heard expressed until recently is that they will help corporations capture Implicit knowledge by mining my behaviours and actions.

When Lotus Connections 2.0 announced at LotusSphere promises to deliver a Colleagues version of the friending concept, it’s really building an Implicit knowledge network that can be mined for real information that is accessible to all users across the organisation.  Atlas mines your e-mail for your connections and expertise. Spock mines social networks for Implicit knowledge on who you are and who you know.  Wiki’s mine the knowledge of the crowd through the creation process. 

When corporations ask what value in Web 2.0 concepts and social networking, they are undervaluing what most would say is their greatest asset - the collective knowledge of their employees.  I believe that the real value in a lot of what we call Web 2.0 will be realised when these tools begin delivering ways for corporations to finally tackle Knowledge Management 2.0 — non-intrusive KM, captured by tools that work the way people work and ensure that the Implicit knowledge of the organisation is captured effortlessly by people simply doing their job in the way they want to do it.

Based on this, my final three thoughts are simply that:

1. The reason Collaborative Creation tools are being adopted by corporations today (and will be at an increasing pace) is because they deliver a form of Implicit knowledge that corporations (slowly and eventually) “get”.  Content is delivered in a relatively concrete way that mimics a document to some degree.  The stretch is less.
2. Social Collaboration tools will begin to boom as Corporations realise that they are a promising solution to unlock the Implicit knowledge within their organisations that they can’t see.
3. Discovery and Surfacing tools (of which Spock, Atlas and Particls are all examples of) will become even more critical.  Smart ways of unleashing the networks and information people are building to capture and deliver value that was not easily attainable before.

I’ve been interested in visualisation and prediction markets for a while now, so this post from Google is right up my alley combining two areas of interest.  It’s a fascinating read if you have the time, particular the paper which Bo Cowgill, the author of the post, co-authored.

I’ll leave the blog for you to read, but I will pull out the key thing I took away and found fascinating.

1. The Power of Visualisation

There is a great heat map of a Google Office, showing how profitable trades cluster together, demonstrating the way groups of employees share knowledge.  While this is not all there is to say, it is a powerful graphic that sums up much of the article.  I’ve seen this kind of geographic heat map used in marketing type applications, layering results on to suburb level or post code level type information, but this micro-geographic use is very powerful. 

Link to the graphic (for some reason I can’t insert the image here directly properly…

In my experience employee surveys (as one example) typically break responses down by group or business unit.  While this undoubtably represents some value, what might the responses reveal if there was a heat map cluster of good and bad sentiment?  This is a powerful tool for correlating location which I suspect is an equally important part of the picture.

2. Prediction Markets are going to grow

One I’ve been looking at for a while now and really like is Inkling Markets.  My own experience of trying to evangalise a prediction market had limited success last year, but the more knowledge that enters the world from serious players like Google, the more others will want to pick these up, take them seriously and want to have a look too.

In my opinion, prediction markets are yet another tool in the rich set of collaborative tools like blogs and wikis that promote a new way of knowledge sharing; and like blogs and wikis, it will no doubt take mainstream companies a while to get their heads around it all.  Solid research like this from Google can only help ease the path for others in this regard.

A resurgance once again in the local press about the wisdom, or lack of it, in crowds.  I’ve posted here about this a little, and that was added to very eloquently by Chris Saad of Particle who pointed out that media is additive.  There is place for both wise crowds and smart people. So what more to add to the debate? Well I was sufficiently impressed by the differences and the power of both Google Streets and Microsoft Lives Photo Synth to want to contrast them here in this context.

What’s interesting about this when it comes to the Crowds Vs. Expert debate is that both do a similar thing — street level perspectives of our world, yet they tackle the problem in different ways.

Googles view of the world in Google Streets is high quality, “expert” imagery taken presumably from a car with a special camera and then stitched together. 

Microsofts PhotoSynth uses Flickr (or presumably any photo source with a sufficiently high level of detail) to locate photos as “points” in space, pulling the wisdom of crowds to give us a point by point overview of the object in question.

Both give a very different view of the world.  Googles is a seamless experience, where you can browse from one end of the street to the other, rotate and view in any direction.  Microsofts points give an eerie overview of the object, with detail highlighted where it’s of interest and gaps where there is nothing that is worthy.

Both are amazing pieces of technology, regardless of their respective perspectives on the world.

Ultimately the power of the new web is the power of information - with Google Streets, users will be able to not only tag their favourite restauraunt, but also show a picture of its front door.  Photosynth enables a virtual tour of buildings and places and provides context to endless Flickr photos, not just on a map, but in space as well.

Crowds and experts live will together in the new world and more fool the journalist who tries to seperate the two.  To paraphrase Chris once more, the long tail of information means that there are consumers for all views of the world.

As Elias pointed out on my last post, evidence of the semantic web is emerging all around us.