The Inevitable Rise Of The Social Machine

Social Machines

Truly Unlocking The Potential Of Social

Everyone is talking about being social. Social this, social that. Enter the Social Machine – neatly described by Professor Nigel Shadbolt as:

‘Methods of supporting purposeful human interaction on the World Wide Web. These are collaborations that are empowering, as communities identify and solve their own problems, harnessing their commitment, local knowledge and embedded skills, without having to rely on remote experts or governments.’

This reality is changing the way we need to think about business. Everyone seeks to solve the paradox. “How can we be agile, rigorous, adaptive and achieve high performance in a world that is constantly changing and deliver our goals – without risk?” Well the answer is you probably can’t but you most certainly can be creative and ingenious about how to think about it and in the process leverage what is actually going on.

Thinking socially and systemically around a platform that is very much a machine is powerful.

It’s also crucially central to how we behave as organizations and businesses struggle to understand how to empower employees and eco-systems to overcome the traditional concretized business structures that no longer work. For a long while now business in all its forms has recognized that they need to understand the social phenomenon and develop new ways to leverage the power of the talent and the network that they have created but haven’t tapped.

This kind of collaborative/participatory system interaction is characterized by a new kind of emergent, collective problem solving, in which 4 dynamics are of vital importance

  1. Problems are being solved by very large scale human participation via the Web
  2. Access to, or the ability to generate, large amounts of relevant data using open data standards
  3. There is more confidence in the quality of the data
  4. The inexorable rise in the performance of more intuitive interfaces.

Machine is a very mechanical word – best defined as – ‘A powered  tool consisting of one or more parts that is constructed to achieve a particular goal.’ In technology (and everyday context) ‘machines’ used to be built/programmed by programmers and used by users – this is now changing.

The Web, and the massive participation in it, has dissolved the boundary between man and machine. They are definitely becoming interwoven. We now see configurations of people interacting with content and each other, typified by the plethora of social web sites, applications and platforms. Rather than dividing between the human and machine parts of the collaboration (as computer science has traditionally done), we should draw a line around them and treat each such assembly as a ‘machine’ (or critical component thereof) in its own right comprising digital and human components – a Social Machine.

This crucial transition in thinking acknowledges the reality of today’s ‘socio-technical’ systems. This view is of an ecosystem not of humans and computers but of co-evolving Social Machines. Participatory, authentic and meaningful for all. The implication for everyone is revolutionary and whilst few businesses today really understand what to do about it they are learning fast that to ignore it is suicidal.

SOCIAMVisit The Site

The ambition of SOCIAM is to enable us to build social machines that solve the routine tasks of daily life as well as the emergencies. Its aim is to develop the theory and practice so that we can create the next generation of decentralised, data intensive, social machines. Understanding the attributes of the current generation of successful social machines will help us build the next.

The research undertakes four necessary tasks.

1. Discovering how social computing can emerge given that society has to undertake much of the burden of identifying problems, designing solutions and dealing with the complexity of the problem solving. Online scalable algorithms need to be put to the service of the users.

2. Providing seamless access to a Web of Data including user generated data.

3. Understand how to make social machines accountable and to build the trust essential to their operation.

4. Design the interactions between all elements of social machines: between machine and human, between humans mediated by machines, and between machines, humans and the data they use and generate.

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