Information and memory, data and recall, are two sides of the same coin, or maybe not even. These are certainly parts of the same continuum of inputs and outputs, but whether truly opposite is debatable. Speaking in analog, the cycle is roughly as follows: We experience, we register, at some point we remember, (or not), and the memory shapes a new experience. So it goes, around and around. In more digital terms – and as we increasingly live our lives on devices, more digital nomenclature is perhaps appropriate – we search, we share, we view and listen, we interact and organize, we check in, we check out, we transact and pay, we create, we do some other things, and our action produces bits. We store these bits, or the bits are stored on our behalf, with or without our knowledge, and this is called data. There is so much of it now that we refer to it by a special name, big data, just so we know of which data we speak.
To be clear, big data refers to our collective, (rather than individual), outputs. Were we to interact digitally with our personal computing device only, this data would be private and would reside as an individual store on some hard-drive that we must remember to destroy, or not. But none of us interact digitally in this fashion, or very few of us anymore. Instead, we are online, we are mobile, and in the cloud, we socialize with the worldwide web or with an app, which more or less amounts to the same thing. And in so doing we contribute our individual profile to the collective. We become part of a demographic unit that, as a unit or as part of the bigger whole from which it is extracted, is analyzed and targeted. Thus we are offered objects or we are shown advertisements, and thus our reactions are predicted with statistical precision.
The summary presented, in any case, covers one part of the continuum, the forecast: Data is stored, analysis conducted, conclusions are reached, messages are targeted, or actions otherwise anticipated. Business intelligence – often derivative of other intelligence forms – is roughly based on this sequence. But another part of the cycle has been, so far at least, less feverishly pursued. Granted, it’s a piece that may not lead to commerce as directly as ads or predictive analysis, but it is as critical a fraction of the data-processing line as is the forward-looking vector. This is the backward arrow, the recall, or the individual’s memory. There are two sides on this coin – information and recall – as has been pointed out at the top.
We experience, we register, at some point we remember, and the memory shapes a new experience; so it goes. While big data has been a sophisticated anticipation tool, the same has not yet served as a device to help us to remember. Search functionality has been (arguably) something of the sort, but with this technique one first must remember to search… which sort of defeats the purpose, or it doesn’t fully accomplish the purpose described. A truer memory device would push historical information to an individual, helping him or her to recall what was forgotten. And the best memory device would bring back only subjects that one would care to remember… thus, both anticipating and recalling, simultaneously.
* The late Philip K. Dick once wrote a story in which a commercial enterprise enables its customers to remember (or, rather, believe that they remember) what they wish to remember. Some will recognize the story by its Hollywood variant, Total Recall. The old guy was way ahead of his time, and ours.