CES 2017: The Need for a “Connective Architecture” for Data

Data about your heart. Data about your workout. Data about your sleep. Data about your posture, your focus, your shoes, your pictures, your wallet, your fridge, your front door, your light bulb, your bike, your neighbor, your chair, your car, your desk, your tea, your bikini (?!)… Walking the aisles of CES 2017 last week was a bit like peering into a dystopian feedback loop hell where every single physical object we touch is touching us back — with petabytes of fragmented data and exactly zero intelligence. Here lies the dilemma: While everyone is invested in building the sensor network, nobody is building the brain.

Even Alexa or Google Home, the two celebrated “winners” of CES 2017, do not seem interested in tackling this issue. Their architecture does not — for now — allow for the aggregation and analysis of all the data and insights generated by their various “skills” (don’t call them apps) together in a way that creates meaningful and frictionless value.

This new generation of “smart assistants” feels like a strange re-hash of the extreme fragmentation of applications that has been plaguing our smartphones … and draining our relationships.

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What is missing is a “connective architecture” for all this data — the personalized intelligence that will connect these trillions of dots to generate real, powerful intelligence to make us healthier, more informed, more productive and more aware.

The foundation of that connective architecture, of course, is artificial intelligence. True AI — the likes of which was barely, if at all, seen at CES — will be capable not only to merge this data (expressed in different classes, formats and taxonomies) autonomously into real knowledge, but will be able to leverage this knowledge to truly “reason” about what we need, how we need it and when.

This superior intelligence would be frictionless and would augment us and our own intelligence in ever-expanding ways, even perhaps lifting the veil on the nature of our own lives and our own reality.

But what about purpose? This is where this concept of “connective architecture” becomes really interesting. AI is only one part of this “connective architecture.” AI can reason about the whats, whens and hows, but not so much (at least not now) about the whys. The whys are our individual and collective narratives, the stories of our lives — real and imagined — that drive who we are, who we were, who we want to be, who we will be.

Stories drive our processes of identity, and these in turn play a foundational role in our actions. This is an area where the entertainment industry should play in the next few years: nobody is better at telling story than Hollywood. Nobody knows us better, really. Imagine a Pixar-educated AI agent that can reason about what inputs or feedback loops we need, but also why we need them.

This is transformational, and it is coming.