Designing social media and other information-rich tools for transactional memory
I have written repeatedly in this blog about social media and our increasingly ubiquitous capabilities for connecting and communicating. I have been writing of our rapidly increasing capabilities for co-creating and sharing information as a key aspect of that. You can find discussions of this in directories such as my Ubiquitous Computing and Communications – everywhere all the time and Social Networking and Business, and I add that analysis and discussion of this rapidly developing series of interconnected trends imbues this entire blog as a whole. I have also at least touched on how this change in our technological context is changing us too, and that is the general topic area that this posting falls into.
The term that I would start this posting with is transactional memory and I begin by noting that it had its origins in parallel computing whereby a group or ensemble of processors can load to and share from a single pool of instructions and/or data. I use this term here in a strictly human community context, with the notion that we can in effect store our knowledge and the raw data that would support it, outside of ourselves – with others and increasingly in the cloud.
If online social networking and our increasingly ubiquitous capacity to connect and communicate is changing how we socially network and who we can network with – the boundaries of community, it is also coming to challenge the basic limitations as to how many others we can meaningfully network with (see Robin Dunbar and the Limits to Social Networking – a fundamental question of purpose and definition.) Neither social networking or related technology-supported practices, nor the technology infrastructures that support them are in a position to fundamentally change our innate neural capacity for either social networking reach, or for any other sorts of information. But our external and community-based information infrastructures are changing what we need to know and actively remember if we can successfully tap into the transactional memory capabilities and resources that are developing around us.
They, to cite an example I have already touched upon, can significantly aid us in increasing the reach within which we can actively socially network. And in that context I would propose a Turing test analog for social networking reach. If networking technology augmentation can help someone to connect and network with another so smoothly and seamlessly that they seem to have had all of the details of that person in their active memory – in their head and that contact cannot tell that they were accessing it from outside data storage, then this first person can legitimately claim that their “artificial” networking connection to the second is genuine, and according to the same depth and completeness criteria that Dunbar would require in his social networking analyses.
But I am not simply writing here about extending active social networks well beyond the Dunbar limit of some 150 direct, close contacts through access of transactional memory resources. This same paradigm applies to extending our reach wherever we face information-intensive contexts or requirements.
• Ubiquitous computing and communications are changing us in a variety of ways and one if the most telling is in the way it is changing what we learn and remember, with a shift from learning end-point data and knowledge, to learning where we can find and access that data and knowledge when we need it – quickly and seamlessly in the context of what we are doing and why we need it.
• And as ubiquitous computing and communications increase the scope and range of what we can immediately and seamlessly access and use as information, a larger and larger percentage of what we know will in fact be indexing and access information needed for finding and connecting to these transactional memory resources.
This brings me to a fundamental question that cannot have a single, simple, clear cut answer.
• What should we be learning, and carrying around within our own heads and what can we safely and efficiently tap into in the cloud and other distributed information systems?
I will give at least a tentative framework of an answer by noting two points that I see as essential, as to what we need to internalize and learn for ourselves.
• We need to know a basic body of information that would be needed to accurately and effectively tap into and use outside information as we access it.
• And just as importantly, we need a basic grounding of internalized and within-the-head owned information that will help us to judge the accuracy, relevancy, impartiality or bias, and completeness/utility of the outside information that we find.
Together, this means we will still have to internalize and learn at least as much as we ever have, pre-computer age and pre-ubiquitous computing and communications age. It is just that the emphasis and focus of this knowledge and how we think about it is going to change.
You can find this and related postings in Social Networking and Business and in Ubiquitous Computing and Communications – everywhere all the time.